EPA-230/1-75-036
SEPTEMBER 1975
ECONOMIC ANALYSIS OF
INTERIM FINAL AND PROPOSED
EFFLUENT GUIDELINES
CANNED, FROZEN AND PRESERVED
FRUITS AND VEGETABLES INDUSTRY
(PHASE II)
QUANTITY
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Planning and Evaluation
Washington, D.C. 2O46O
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This document is available through the National Technical
Information Service, U.S. Department of Commerce, 5285 Port
Royal Road, Springfield, Virginia 22161.
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ECONOMIC ANALYSIS OF
INTERIM FINAL AND PROPOSED EFFLUENT GUIDELINES
CANNED AND PRESERVED
FRUITS AND VEGETABLES INDUSTRY
Canned Fruits and Vegetables, Frozen Fruits and Vegetables
Canned Specialties, Pickles, Sauces and Salad Dressings
Dehydrated Fruits and Vegetables, Potato and Corn Chips
Raymond E. Seltzer
Marvin H. Almond
Robert 0. Buzenberg
Prepared for
Office of Planning and Evaluation
Environmental Protection Agency
Washington, D. C. 20460
September, 1975
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PREFACE
The attached document is a contractor's study prepared with the supervision
and review of the Office of Planning and Evaluation of the U.S. Environmental
Protection Agency (EPA). Its purpose is to provide a basis for evaluating
the potential economic impact of effluent limitations guidelines and stand-
ards of performance established by EPA pursuant to sections 304(b) and 306
of the Federal Water Pollution Control Act.
The study supplements an EPA technical "Development Document" issued in
conjunction with the promulgation of guidelines and standards for point
sources within this industry category. The Development Document surveys
existing and potential waste treatment and control methods and technologies
within this category and presents the investment and operating costs associ-
ated with various control technologies. This study supplements that analysis
by estimating the broader economic effects (including product price increases,
continued viability of affected plants, employment, industry growth and
foreign trade) of the required application of certain of these control tech-
nologies.
This study has been submitted in fulfillment of Contract No. 68-01-1533,
Task Order No. 17, by Development Planning and Research Associates, Inc.
Work was completed as of September, 1975.
This report represents the conclusions of the contractors. It has'been re-
viewed by the Office of Planning and Evaluation and approved for publication.
Approval does not signify that the contents necessarily reflect the overall
views of the Environmental Protection Agency. The study has been considered,
together with the Development Document, information received in the form of
public comments on the proposed regulation, and other materials in the
establishment of final effluent limitations guidelines and standards of
performance.
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CONTENTS
I. INTRODUCTION 1-1
A. Scope 1-1
B. Organization 1-3
C. Data Sources 1-3
II. INDUSTRY SEGMENTATION II-l
A. Characteristics of Fruit and Vegetable
Canning, Freezing and Dehydrating Industries
1. Value of Production by Segment II-l
2. Size and number of firms II-3
3. Degree of integration II-7
4. Industry Diversification and Specialization II-7
5. Concentration of Production in the Fruit
and Vegetable Processing Industry II-9
6. Total Employment in the Industry 11-10
B. Number of Plants and Employees in Each Segment 11-14
• C. Characteristics of Fruit and Vegetable Canning,
Freezing and Dehydrating Plants 11-14
1. Number and Location of Plants .11-16
2. Size of Plants 11-16
3. Single Plants vs. Multiplant Firms 11-19
4. Number of Plants by Type of Product 11-19
5. Number of Products by Type of Plant 11-19
6. Age of Plants and Level of Technology ' 11-24
7. Plant Efficiency 11-24
D. Importance of Specific Products Relative to the
Industry 11-28
1. Specific Vegetable Products Relative to the
Canned Vegetable Industry • 11-28
2. Specific Vegetable Products Relative to the
Vegetable Freezing Industry 11-29
3. Specific Canned Fruit Products Relative to the
Canned Fruit Industry 11-29
4. Specific Fruit Products Relative to Frozen
Fruit Industry 11-30
5. Specific Products Relative to the Dehydrating
Industry H-30
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CONTENTS (continued)
E. Significant Impacts on the Industry
1. Capacity of Low Cost Producers Relative
to High Cost Producers
2. Factor Dislocation Within the Industry
3. Reasons for Dislocations
4. Narrowing the Study Scope
III. FINANCIAL PROFILE
A. Model Plants by Segment
1. Seasonality
2. Style of Pack
B. Model Plant Configuration
1. Sales
2. Variable Costs
3. Fixed Costs
4. Total Costs
5. Investment
6. Values and Costs Per Ton
C. Model Plant Income
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
Corn Canning Plants - Table I11-11
Cherry Freezing Plants - Table 111-12
Mushroom Canning Plants • Table 111-13
Pickle Canr.inc Plants - Table 111-14
Ting - Table 111-15
- Table 111-16
,g Plants - Table 111-17
ng Plant - Table 111-18
Bean-Carrot Canning Plant
Sauerkraut
Tomato Cc.nninr
Corn-Pea Cann
Cc^n-Pea Fr^ez
Corn-Pea-Greet.
Table 111-19
Corn-Pea-Green Bean-Carrot Freezing Plant -
Table IJ.I-20
Broccoli-Caulif!ower-Lima Beans-Spinach
Freezing Plant - Table 111-21
Tomato-Dry Bean Canning Plants - Table 111-22
Cherry-Green Bean-Pear-Plum Canning Plants -
Table 111-23
Potato Chip Plants - Table 111-24
D . Return on Investment
^ !ble Impacts
11-31
11-32
11-33
11-.34
III-l
III-l
III-3
III-3
III-3
III-6
111-10
111-10
III-ll
iii-n
III-ll
111-16
in-16
111-16
111-16
111-17
III-17
III-l7
III-l/
111-17
111-17
111-18
111-18
111-18
111-18
111-18
111-33
IIT-33
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CONTENTS (continued)
E. Value of Assets • 111-33
1. Book Value 111-36
2. Salvage Value 111-36
3. Replacement Value 111-37
IV. PRICING EFFECTS IV-1
A. Demand IV-1
1. Trends in Demand IV-1
2. Per Capita Consumption IV-2-
3. Government Purchases IV-11
4. Foreign Trade IV-13
5. Demand Characteristics IV-15
B. Supply IV-24
1. Pack IV-24
2. Carryin IV-30
3. Imports IV-33
C. Industry Pricing Processes IV-33
1. Market Competition and Price Determination IV-36
2. Grower Contracts IV-38
3. Marketing Agreements and Marketing Orders IV-39
D. Processing and Marketing Margins IV-41
1. Margins - Specific Products - Grower -
Processor - Wholesale & Retail IV-42
2, Margins- - Grower - Processor Only IV-45
E. Expected Price Changes IV-45
1. Demand Factors - IV-47
2. Supply Factors IV-47
3. Industry Organization and Competition IV-48
4. Anticipated Price Impacts of Effluent
Control Programs IV-48
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CONTENTS (continued)
Page
V. ECONOMIC IMPACT ANALYSIS METHODOLOGY
A. Fundamental Me j: ho dp 1 o gy V-l
1. Returns V-5
2. Investment V-5
3. Cost of capital - after-tax V-6
4. Construction of the cash flow V-7
B. Price Effects V-8
c- Shutdown Analysis V-9
D. Production Effects V-10
E • Il'lP1 oyment Effects V-10
F- Ccp-.-nur.ity Effects - V-10
G, (Jl\.er_:i'ff ects_ - _Fp_re_i3LJllM^. ^-11
VI. P'/^UTJO:, CONTROL REQUIREMENTS AND COSTS
A. ~£ i 1 j. t i on Con trol__Rsgulrements VI -1
B- Pov::.t1:ifi Co..:rl Costs VI-4
• i s U-a.rn on Sales ViT
j' At tor-tax Return on Investe-: Capital VT!-P
••. t 3sh p"* •«'-' VII-b
j. Nee :" pseht value VII-8
6. R-ni 'e fu- Use o, "'-veraye Year1' Profit-
aD'i] J VI1-9
7 Avaiii 1 ity or Capita'' VJI-1U
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CONTENTS (continued)
Page
C. Production Effects VII-25
1. Segmentation of Industry to Model Plants VII-25
a. Classification of plants and com-
modities VII-25
b. Total number of industry plants VII-27
c. Sizing of industry plants • VII-27
2. Baseline Closures VII-40
a. Total industry VII-40
b. Industry groups VII-40
3. Closure Criteria VII-50
4. Closure Evaluation Procedure VII-52
5. Projected Plant Closures VII-52
6. New Source Performance Standards VII-56
7. Production Losses VII-57
D. Employment Effects ^ VII-60
1. Employment Trends VII-60
2. Employment - Sales Relationships by Plant
Size VII-60
3. Employment and Payroll Impacts VII-60
4. Possibilities for re-employment VII-63
E. Community Impacts VII-66
F. Balance-of-Payment Impacts 'VII-68
VIII. LIMITS OF THE ANALYSIS
A. General Accuracy VIII-1
B. Possible Range of Error . VIII-3
C. Critical Assumptions VIII-3
APPENDIX A - SURVEY FORM
Industry survey conducted by Industry Trade
Associations
APPENDIX B - SUPPLEMENTAL TABLES
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LIST OF TABLES
Table No. Title Page
II-l Value of industry production, by segment, Census years,
1958-1972 II-2
II-2 Size distribution of fruit and vegetable canning firms,
1974 II-5
II-3 Size distribution of fruit and vegetable freezing firms,
1974 II-6
II-4 Fruit and vegetable processing establishments by number
of employees and industry segment, Census years,
1954-1972 II-8
II-5 Percent of value of shipments accounted for by largest
companies in industry segments 11-11
II-6 Number of plants and employees by industry segment, 1972 11-15
II-7 Number of fruit and vegetable canning and freezing plants
by type and economic region, 1972 11-17
II-8 Number of fruit and vegetable processing plants by Census
region, 1972 11-18
II-9 Summary of number of plants and ranges of values per
plant by size group for annual tons of production,
annual value of production, and employment, 1972 11-20
11-10 Number fruit and vegetable single and multi-plant firms,
by type of plant 11-21
11-11 Types of fruit and vegetable processing plants by type of
product, 1974 11-22
11-12 Number of products by type of plant 11-23
11-13 Percent of canning plants in various age groupings by
location and commodity and years s^ice last major
expansion • 11-25
11-14 Summary of factors affecting utilization of capacity
within fruit and vegetable processing plants 11-26
III-l Summary of model "plant characteristics: commodities
and sizes III-2
III-2 Monthly volume of production: single commodity plants
and specialty plants > III-4
111-3 Monthly volume of production, multi-commodity plants 111-5
III-4 Estimated sales, variable and fixed costs and relation-
ships for industry segments based on model plants -
single commodity, 1973 III-7
III-5 Estimated sales, variable and fixed costs and relationships
for industry segments based on model plants, multi-
commodity, 1973 111-8
III-6 Estimates sales, variable and fixed costs and relationships
for industry segments based on model plants -
specialty commodity plants, 1973 III-9
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rate
corn
rate
of return on average
canning plants, 1973
of return on average
rate of return on average
pickle canning plants,
rate of return on average
sauerkraut canning plants,
rate of return
tomato canning
on average
plants.,
LIST OF TABLES (continued)
Table No. Title
II1-7 Estimates investment for industry segments based on
model plants - single commodity, 1973
III-8 Estimated investment for industry segments based on
model plants - multiple commodity plants, 1973
III-9 Estimated investment for industry segments based on
model plants - specialty commodity plants, 1973
111-10 Relationship between size of plant and costs per ton
fruit and vegetable canning and freezing plants,
1973
III-ll Estimated annual cash flow and
invested capital for model
111-12 Estimated annual cash flow and
invested capital for model mushroom canning plants,
1973
111-13 Estimated annual cash flow and
invested capital for model
1973
111-14 Estimated annual cash flow and
invested capital for model
1973
II1-15 Estimated annual cash flow and
invested capital for model
1973
111-16 Estimated annual cash flow and
invested capital for model
1973
111-17 Estimated annual cash flow and
invested capital for model
carrot canning plants, 1973
111-18 Estimated annual cash flow and rate of return on average
invested capital for model corn-pea-carrot-green bean
freezing plants, 1973
111-19 Estimated annual cash flow e. d rate of return on average
invested capital for mod-,1! broccol i-cauliflower-lima
bean-spinach freezing plants, 1973
111-20 Estimated annual cash flow and rate of return on average
invested capital for modal tomato-dry bean canning
plants, 1973
111-21 Estimated annual cash flow a :d
invested capital for model
canning plants, 1973
111-22 Estimated annual cash flow arid
invested capital for model
freezing plants, 1973
111-23 Estimated annual cash flow and
invested capital for mod"!
dressings and ^auces pla.ts
111-24 Estimated annual cash flow and rate of
invested capital for mod'l brined
rate of return on average
corn-pea canning plants,
rate of return on average
corn-pea- green bean-
rate of return on average
cherry-green bean-pear-plum
rate of return on average
cherry-strawberry-caneberry
rate of return on average
nickle, tomato-dry bean-
1973
return on average
prnuu^t plant, 1973
111-12
111-13
111-14
111-15
111-20
111-21
111-22
111-23
III24
111-25
111-26
111-27
111-28
111-29
111-30
111-31
111-32
111-33
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LIST OF TABLES (continued)
Table No. Title Page
111-25 Estimated annual cash flow and rate of return on average
invested capital for model potato chip plants, 1973 111-34
111-26 Model plants return on investment, 1973 111-36
II1-27 Comparison of book and salvage values of fixed assets
of model plants, 1973 111-37
IV-1 Commercially-produced vegetables: civilian per capita
consumption, United States, 1950-73 IV-3
IV-2 Civilian per capita consumption - selected vegetables,
by product form, 1950, 1960, 1965, 1970, and 1973 IV-5
IV-3 Processed fruits: per capita civilian consumption,
United States, 1950-74 IV-8
IV-4 Civilian per capita consumption, selected fruits and fruit
juices, by product form, 1950, 1962, 1966, 1970 and 1973 IV-9
IV-5 Government purchases of canned fruits, vegetables and
juices, 1966-1973 IV-12
IV-6 Government purchases of frozen fruits, vegetables and
juices, 1966-1973 IV-12
IV-7 Export volume, processed fruits and vegetables, general
catefories, 1967-1973 IV-14
IV-8 Exports of major canned and frozen fruits and juices,
1970-1973 IV-16
IV-9 Exports of major canned vegetables and frozen fruits and
vegetables, 1970-1973 IV-18
IV-10 Fruit and vegetable expenditures ad a proportion of retail
food and total expenditures IV-21
IV-11 Selected fruit and vegetable demand and income elasticities IV-22
IV-12 Summary of canned vegetable packs, 1969-1974 IV-26
IV-13 Summary of canned fruit and fruit juice packs, 1969-1973 IV-28
1V-14 Summary of frozen vegetable packs, 1969-1973 ' IV-29
IV-15 Summary of frozen fruit packs, 1969-1973 IV-31
IV-16 Summary of frozen fruit juice packs, 1969-1973 IV-31
IV-17 Carryin, selected canned fruits and vegetables, 1969-1973 IV-32
IV-18 Carryin, selected frozen fruits and vegetables, 1969-1973 IV-34
IV-19 United States' imports of canned and frozen fruit and
vegetable products, 1970-1972
IV-20 Canners of f.o.b. price, major canned fruits and vegetables,
by quarters, 1970-71 and 1972-73 IV-37
IV-21 Marketing margins for selected canned and frozen fruits
and vegetables, 1965-1973 IV-43
IV-22 Farmers' share of canner's price, selected fruits and
vegetables for processing, 1973-74, 1970-71 and
1967-68 IV-46
VI-1 Average raw wasteload parameters and average daily waste-
water volume during period of maximum wasteload for
model fruit and vegetable processing plants IV-2
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LIST OF TABLES (continued)
Table No. Title Page
VI-2 Summary of treatment components for alternative effluent
reduction systems in fruit and vegetable processing
plants VI-5
VI-3 Summary of additional treatment units required with
activated sludge in model plants of the fruit and
vegetable processing industry VI-6
VI-4 Estimated total investment (I) and total annual costs
(AC) for Best Practical Control Technology (BPT)
and Best Available Control Technology (BAT) for
wastewater effluent treatment for model plants of the
fruit and vegetable processing industry VI-7
VI-5 Effluent treatment costs per ton of raw product procer
by commodity, plant type and size VI-8
VI-6 Estimated present and future percent of fruit and vege-
table processors using each type of disposal system VI-11
VI-7 Estimated percentages of direct discharging fruit and
vegetable processing plants with various levels of
control systems in place and corresponding per-
centages of additional systems cost to reach BPT VI-12
VI-8 Estimated direct discharging plants in relation to
industry group and model plants VI-14
VI-9 Total number of plants and direct dischargers by type
and degree of control system currently in place,
baseline conditions as of July, 1974 VI-15
VII-1 Price increases required to offset incremental pollution
control costs, aerated lagoon and activated sludge
at three in-place treatment levels VII-3
VII-2 Limits to price increase, direct dischargers, as estab-
lished by largest plants, no system in-place VII-6
VII-3 Pre-tax return on sales, canned fruits and vegetables
industry, 1961-1973 unaudited VII-14
VII-4 After-tax income, model plants, baseline condition and
after BPT and BAT controls, three levels of in-place
treatment ($000) VII-15
VII-5 After-tax return-on-sales model plants, baseline con-
dition and after BPT and BAT controls, three levels
of in-place treatment (%) VI1-17
VII-6 After-tax retorn-on-investment, baseline condition and
after BPT and BAT controls, three levels of in-place
treatment (%) VT-10
VII-7 Estimated annual cash flow, model plants, baseline con-
ditions and after BPT and BAT controls, ;three levels
of in-place treatment ($000) VII-21
VII-8 Net present values of model plants, baseline condition
and after BPT and BAT controls, three levels of in-
place treatment ($000) VII-23
VII-9 Classification of commodities into processing functions VII-26
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LIST OF TABLES (continued)
Table No. Title Page
VII-10 Number of industry plants, listed in Directory, grouped
into representative model plant processing functions
and commodities by model, for canning plants VII-28
VH-11 Number of industry plants, listed in Directory, grouped
into representative model plant processing functions
and commodities by model, for freezing plants VII-29
VII-12 Number of industry plants, listed in Directory grouped
into representative model plant processing functions
and commodities by model for dehydrating plants VI1-30
VI1-13 Grouping of industry plants listed in Directory by model
plant and extrapolation to 1972 Census industry group
with both sets of data adjusted to exclude apples,
citrus and potatoes VII-31
VII-14 Summary comparison of canned specialties, industry group
(2032) to representative model plants—plants, pro-
duction, employment, payroll, and value of production,
1972 . VII-33
VII-15 Summary comparison of canned fruit and vegetables, in-
dustry group (2033) to representative model plants--
plants, production, employment, payroll, and value of
production, 1972 VII-34
VII-16 Summary comparison of pickles, dressings and sauces, in-
dustry group (2035) to representative model plants--
production employment, payroll and value of pro-
duction, 1972 VII-35
VII-17 Summary comparison of frozen fruits and vegetables,
industry group (2037) to representative model plants--
plants, production, employment, payroll and value of
production, .1972 ' VII-36
VII-18 Summary comparison of dehydrated fruit, vegetables and
soup mixes, industry group (2034) to representative
model plants—plants, production, employment, payroll,
and value of production, 1972 VII-37
VII-19 Summary comparison of potato and corn chips, industry
croup (20992) to representative model plants—plants,
production, employment, payroll, and value of pro-
duction, 1972 VII-38
VII-20 Summary of basic assumptions of percent and number of
total plants, production, value of production, em-
ployees and payroll by size group for the canned
specialties (2032) industry group for 1972 and trends
to 1977 and 1983 VII-44
VII-21 Summary of basic assumptions of percent and number of total
plants, production, value of production, employees and
payroll by size group for the canned group for 1972 and
trends to 1977 and 1983 VI1-45
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LIST OF TABLES (continued)
Table No. Title Page
VII-22 Summary of basic assumptions of percent and number of
total plants, production, value of production,
employees and payroll by size group for 1972 and
trends to 1977 and 1983 VII-46
VII-23 Summary of basic assumptions of percent and number of total
plants, production value of production, employees and
payroll by size group for 1972 and trends to 1977 and
1983 VI1-47
VI1-24 Summary of basic assumptions of percent and number of
total plants, production, value of production,
employees and payroll, by size group for the dehy-
drated fruit and vegetable (2034) industry group
for 1972 and trends to 1977 arid 1983 VII-48
VII-25 Summary of basic assumptions of percent and number of
total plants, production, value of production,
employees and payroll by size group for the chip
portion of food preparations (2099) industry group
for 1972 and trends to 1977 and 1983 VII-49
VII-26 Estimated plant closures, direct dischargers, model plant
groups, BPT and RAT guidelines VII-53
VII-27 Estimated plant closures, direct dischargers, industry
groups, BPT and BA" guidelines VII-55
VII-28 Production lost due to ~>lant closures,, industry groups,
aerated lagoon systems VII-58
VII-29 Production lost due to plant closures, industry groups,
activated sludge systems VII-59
VI1-30 Employment in the canned, frozen and preserved fruit and
vegetable proc , ing industry (excluding citrus and
applies) 1958-! H2 VI? -61
VII-31 Employme-t-sales re -ti is lips, fruit and vegetable pro-
ces">,g inuuutry b S'ze of plant M
VII-32 Employment looses 1i<. + pianc closures, industry groups,
aerated '• agoon -: c.t rns Vli-fr-
VI1-33 'Employment susses -iut \ p:ar closures, industry groups,
activated sludge <=; tei.is VII-65
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LIST OF FIGURES
Figure No. Title Page
V-J Schematic of impact analysis of effluent control
guidelines V-2
VI-1 Selection of effluent treatment systems by direct
dischargers VI-9
VII-1 Major regions with above U.S. average of "Small"
canning and freezing plants, 1970 VII-67
VII-2 States with above U.S. average of "Small" canning
and freezing plants, 1970 VII-67
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ECONOMIC ANALYSIS OF INTERIM FINAL AND PROPOSED EFFLUENT GUIDELINES
CANNED AND PRESERVED FRUITS AND VEGETABLES INDUSTRY
EXECUTIVE SUMMARY
I. INTRODUCTION
This study analyzes the economic impacts of interim final and proposed
effluent control guidelines on direct discharging plants in selected
segments of the canned and preserved fruits and vegetables industry.
Based upon an economic analysis of representative industry model plants,
the study delineates the economic and financial impacts which will result
within the industry as affected direct discharging plants assume the
costs of the proposed effluent controls.
A. Scope
The complexity of so large an industry as the canned and preserved fruits
and vegetables industry required that the model plant configurations re-
flect the economic and financial characteristics of single and multi-
commodity and speciality products plants which directly discharge their
effluents to surface waters. The 53 model plants analyzed in the study
reflect the industry's representative processing volumes, product mixes,
production processes, plant effluents, and the economic and financial
characteristics of various segments of the industry contained with SIC
classifications 2032 through 2035 and SIC 2037 and 2099.
B. Organization
This study is organized as follows:
I. Introduction
II. Industry Organization and Segmentation
III. Financial Profiles — Model Plants
IV. Pricing Effects
V. Economic Impact Methodology
VI. Pollution Control Requirements and Costs
VII. Economic Impact Analysis
VIII. Limits of the A.'ialysis
C. Data Sources
The study made extensive use of published industry data from pertinent
government, industry, and institutional research organizations. Ad-
ditionally the study employed data resulting from an extensive, coopera-
tive industry survey designed to facilitate the present analysis. Sup-
plementary data were based upon personal contacts with representatives
of industry firms and trade associations and specialists in industry,
government, and public and private research organizations.
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II. INDUSTRY SEGMENTATION
This chapter characterizes the firms, plants and products in the follow-
ing fruit and vegetable canning, freezing, and dehydrating industries:
SIC
2032 Canned specialties (soups, dry beans, and baby foods only)
2033 Canned fruits and vegetables (excluding apples and citrus*)
2034 Dehydrated fruits, vegetables, and soup mixes (excluding potatoes
and apples*)
2035 Pickled fruits and vegetables, vegetable sauces, seasonings and
salad dressings
2037 Frozen fruits and vegetables (excluding apples, citrus, potatoes,
and frozen specialties*)
2099 Food preparations, potato and corn chips only
The data included in this chapter are generally discussed by processing
type: canning, freezing, and dehydrating.
A. Characteristics of Fruit and Vegetable Canning,
Freezing and Dehydrating Industries
This section describes the value of production, size and number of firms,
integration, diversification, concentration, employment, and payrolls of
the considered industry segments.
1. Value of Production by Segment
The value of production for most of the fruit and vegetable processing
industry analyzed in this report increased from $4.2 billion in 1958 to
$8.5 billion in 1972, an increase of 102%. The canning segments'- value
of production during this period declined from 79% to 73% of the total
value of production of the fruit and vegetable processing industry; the
freezing segment's proportion of total value increased slightly from 8
to 9% the dehydrating segment's relative value remained at a constant 6%.
2. Size and Number of Firms
.Data indicating firm size by daily production volumes (necessary for an
accurate comparable measure among plants of varying volumes and seasonal
operations) were unavailable for this study; thus, comparisons relied
Because of their inclusion in a prior study (see p. 1-1), the apple,
citrus, and potato segments of this irdustry are generally excluded
from this analysis. Unless otherwise noted, industry data is exclusive
of these three products
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upon data for annual pack volumes for canning and freezing firms.
a. Canners: Fifty-four percent of the surveyed 657 plants had annual
packs less than 500,000 cases; 24% packed over 2,000,000 cases; 8%, over
5,000,000 cases annually. As the study indicates, fruit and vegetable
firms tend to be canners only. The survey indicates that among canning
firms, only 15% had additional plants for freezing and/or dehydrating.
Some can and freeze within the same plant.
b. Freezers: The study considered data from 216 fruit and vegetable
freezing firms. Approximately 55% of those firms processed fewer than
10 million pounds per year; 18% had volumes in excess of 50 million
pounds; 10% had annual packs exceeding 100 million pounds. Of all
firms studied, slightly more than one-quarter did all or some freezing
of fruits and vegetables, and 55% of those plants processed frozen pro-
ducts only. The remaining firms (111) had plants, 45%, that also canned
and dehydrated fruits and vegetables within or among firm plants and 69%
both canned and froze products in the same plants.
c. Dehydrators: The 1974-75 Directory data (the survey data source
referred to for canners and freezers) incl.ude too few dehydration firms
(only 13) to provide significant, comparable data on firm size.
3. Degree of Integration
Little vertical integration exists in the fruit and vegetable processing
industries (8% of canners and 9% of freezers procure raw products from
owned or rented land). Approximately two-thirds of the industry firms
purchase raw products on contract (thus minimizing supply variations).
A similar number also distribute their processed volumes under broken
contracts.
4. Industry Diversification and Specialization
Most fruit and vegetable processing firms are not diversified beyond the
products considered in this report; however, the industry plants are
highly diversified into multiple products and lives of fruits, vegetables,
and juices. Much of this intra-industry specialization is location-
oriented, depending in large part on raw product or specialized equip-
ment procurement. Industry plant specialization ratios are generally
80+ percent for canners and freezers and 90+ percent for dehydration
plants.
5. Concentration of Production
Production concentration by region is negligible in the industry. The
industry is characterized by relatively few firms in each SIC industry
group, of which the largest 50 (by value of production) account for
70% to 99% of the total value of shipments. Among canners in SIC 2032,
TM
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2033, and 2034, the four largest firms accounted for one-third of the
value of production and the largest 50, 78% in 1967. The four largest
freezers accounted for one-third of the 1967 value of shipments and
the largest 50, 93%. The dehydration industry has higher degrees of
concentration.
6^ Total Employment in the Industry
The fruit and vegetable canning, freezing, and dehydration industries
are major employers in their operating areas, especially of low-skilled,
seasonal workers. Industry curtailment would severely affect local area
employment and agriculturally related or dependent enterprises.
a. Number of Employees
Canning: The total 1972 employment in the three considered segments was
139,700, down from 152,000 in 1957, and 86% of the 1972 total were pro-
duction workers. Plants employing more than 20 persons constitute
slightly more than half of the industry plants and account for 63% of
the total six segment industry employment.
Freezing: Employment in frozen fruits and vegetable plants and frozen
specialty products increased from 39,500 in 1958 to 81,200 in 1972.
Freezing plants tend to have larger employee numbers than do canned
plants and tend toward increasingly larger work-forces, a measure of
the increasingly larger scale of operations of the freezing industry.
Production workers represent 88% of total employees. Ninety-one percent
of the frozen fruit and vegetable plants employed 20 or more people in
1972 or 19% of the total six segment employment numbers.
Dehydrating: This industry segment employed 12,400 in 1972, 6% of the
total six segment employment. In 1972, 85% of the employees -were produc-
tion workers. Potato and corn chips, curls, and related product plants
employed 27,200 in 1972. This represented 15% of the six segment employ-
ment.
b. Industry Payrolls
The 1972 industry payrolls were as follows:
Industry
Canning
Freezing
Dehydrating
Payroll
$923,900,000
$261,800,000
$ 84,300,000
Prod. % of Payroll
78%
80%
74%
Average payroll
per employee
$6,526
$6,102
$6,768
IV
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B. Number of Plants and Employees in Each Segment
The numbers of plants and employees are basic in this analysis and are
based on the 1972 census year.
Canners comprise 75% of all plants and 70% of all employees in the com-
bined six segments of this study; freezers of fruits and vegetables (ex-
cluding specialty products, comprise 6% of the plants and 9% of the
employees; dehydration plants makeup 19% of the plants and 21% of the
employees.
C. Characteristics of Fruit and Vegetable Canning, Freezing
and Dehydrating Plants
Because many decisions apropos of and consequent to effluent control
costs are based upon individual plant rather than firm characteristics,
this section discusses plant sizes, location, number, utilization, and
efficiency.
1. Number and Location of Plants
A summary of the 1974-75 Directory of the Canning, Freezing and Preserv-
ing Industry indicates that there are ,390 such plants in the U.S.: 994
fruit and vegetable canners, 229 fruit ~nd vegetable freezers, and 111
that can can or freeze fruit and or vec Cables; 56 plants are able to
can, freeze, and/or dehydrate. Althougi some regional concentration is
apparent, the plants are generally dispensed throughout the country.
L.
Size of Plants
The study grouped plants into five size categories and, although each
industry was so categorize-d individually, the size groups followed a
general pattern. Industry production concentration resulted in a
relatively few plants in the extra-large group and a consequently large
number of plants in the extra small and small plant groups.
3. Single Plants vs. Multiple Plants
Directory data indicate that 78% of all canner, freezer, or combination
plants are operated by single plant, firms. Comparable data are not
available for dehydration firms.
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4. Number of Plants by Type of Product
Approximately 45% of all canners process only vegetable; 5%, only fruit;
6% only fruit and vegetables; and 26% process fruits and/or vegetables
and additional products (i.e., juices, baby foods, specialties). Among
freezers, 33% process only vegetables, 23% only fruits, and 30% process
specialized products as well as fruits and vegetablers.
5. Number of Products by Type of Plant
To realize production and utilization advantages, 61% of all canning,
freezing, and combination plants are mutli-product plants.
6. Age of Plants and Level of Technology
Levels of plant technology are difficult to determine since industry
plants have frequently up-dated their processing equipment as it has
become economically inefficient. In the short run, fewer plants will
continue such improvements because of present economic conditions and
increased investments required by government regulations;
A recent survey of 200 plants (including apples, citrus, potato, seafood,
and speciality plants) by the National Canners Association indicated that
only 13% were less than 10 years of age and 8% were from 10-19 years old.
Seventy-nine percent of the plants were located at the same site for more
than 20 years; 62% had undergone a major expansion in the last five years;
an additional 19% had done so since 1960. Nineteen percent had not ex-
panded since 1959.
7. Plant Efficiency
Plant efficiency rtHects such production .determinants as plant age, level
of technology, utilization, and capacity, and the extensive variables
which, in turn, affect such determinants prevent the precise measuring
of a plant's efficiency. Plant capacity, a measure of plant output
and a major criterion of plant efficiency, was examined for industry
plants on the basis of a National Canners Association survey. In brief,
the study indicated that, little excess capacity exists in the canning
and freezing industries and that, in general, capacity utilization is
higher in the larger plants and in intensive commercial production areas.
CL Importance of Specific Products Relative to the Industry
This section indicates the importance of individual products in the canning,
freezing, and dehydrating fruits and vegetables processing industries. Too
lengthy to be summarized here in detail, the appropriate data do indicate
-------
that the products included in this study's analysis constitute major
portions of the three considered processing industries.
E. Significant Impacts on the Industry
The unique structure and competitiveness of the considered industries
make increased costs due to pollution controls critical for many industry
firms. Though specific impacts will depend upon such factors as capital
availability, profitability, plant location, and the availability of low
cost control strategies, plant size will constitute a major determinant,
and generally, the smaller plants will be the most seriously affected.
Increased user assessments for plants which utilize municipal effluent
treatment services will, of course, affect industry firms, local business
communities, and consumers; however, this analysis is directed primarily
to those plants which directly discharge their effluents to navigable
surface waters--324 plants or 15% of 2,159 plants.
1. Capacity of Low Cost Producers Relative to High Cost Producers
Economies of scale are important in the industries under consideration
and the relative importance of the larger plants (i.e., the larger third
of the canning plants pack 80% of industry volume and the lower third
only 5%) indicates that imposition of costly effluent controls will
further aggravate the diseconomies of scale characteristic of small
plants. (If such plants shut down, the larger plants can eventually
offset their capacity loss.) Important, also, will be plant location,
for the regional distribution of plant sizes is not uniform; hence, ,
significant dislocations in processing can be expected wherever a major
percentage of an area's work force is dependant upon small processing
plants that are seriously impacted.
2. Factor Dislocation Within the Industry
As earlier indicated the impact of abatement controls will be dependant
upon a variety of plant characteristics. Wherever marginal production
units cannot finance added costs, unemployment'and the loss of markets
to farmers and local businessmen will result. Multi-plant firms presumably
can absorb some workers discharged by the closing firm plants, but this
condition will not always result. The previously noted downward trend
in plant numbers will also accelerate employment losses in the industry.
3. Reasons for Dislocations
In addition to plant and firm profitability, industry dislocations will
also depend upon a plant's access to available investment capital. Gen-
erally such funds come from commercial capital sources of from the
investment of profits.
VI 1
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For the considered industries and the plants which characteristically
will need additional funds, the essential measure of capital availability
will be the individual firm's projected net returns under an expanded
investment program. Such a measure indicates the difficulty which small,
marginal plants will have in securing either long or short term capital;
thus, their inability to obtain these funds will contribute to the closing
of such marginal operations.
Firms which are able to pass through increased costs will be able to ac-
quire funds for increased investment to expand or to acquire new plant
capacity. It should be noted that inflation and the general economic
conditions will play significant roles in a plant's ability to pass
through its increased costs.
III. FINANCIAL PROFILE
Necessary to an understanding of the overall impact of interiir final and
proposed pollution controls on the industries analyzed in this study is
the assessment of the financial effects that those controls will have on
representative plants. Because economies of scale are present, this study
will determine the per unit cost of abatement for the study's representative
model plants.
The model plant data and the financial profiles used were developed largely
from an industry-wide survey designed for this study and conducted by
industry trade associations. The developed cost and returns data were
compared with and confirmed by other industry studies and other secondary
sources. The model plants were based on these data and represent condi-
tions characteristic of the industry.
A. Model Plants by Segment
Determined uy the segment analysis of Chapter II, the 53 model plants
used in the study were constructed to reflect the survey and other source
data. Three types of nlants are specified: sinnle commodity plants multi-
product plants, and special*v processing plants (i.e., potato chip -u-
ce^sing dchydratio- j/icnu). Additional y the models reflect indusc.-y
plant sizes representative of actual ope ating industry canning and
freez ng plants. Al^^jgh no one model s intenaed to represent any
spec" "ic ndustry , ant, the analysis is DC- 'H, no" on a hypothetical
mode; ~" ^lant costs ^.nd returns but, ra htr upon the performance data
for actual sales, costs, profitability, and .iv'estn.dnts of reported industry
olants.
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Two characteristics should be borne in mind in analyzing model plant data.
First, the industry plants differ substantially in seasonality. That is,
some single product plants - corn, for instance—operate for only one
two-month season while others—multi-product plants—process a diversity
of products and have year-round operations. Second, industry plants
vary greatly in product styles. (The survey data did not always clearly
denote these variations.) The model plants represent averages or ranges
and include data from plants having a broad spectrum of product styles
(i.e., tomato plant product styles may include peeled whole tomatoes,
pastes, sauces, catsup, and juices).
B. Model Plant Configuration
The model plant cost and sales data assume an industry utilization factor
common for the industry in 1973. Sales figures, for instance, are repre-
sentative for these plants as they operated under 1973 prices. All plant
sizes were based on total annual tons of raw materials processed.
The use of 1973 cost and sales data underlie all models. The year was an
especially favorable one (less than 5% of'the survey respondents reported
losses) for fruit and vegetable processors, and as one industry study of 31
canners showed, the" industry had an average pre-tax return on sales of 5.5
percent compared to a comparable return of 4.4 percent over the 1961-1973
period for essentially the same firms.
The 53 model's cost and profitability data are stated in annual terms, a
basis which eliminates seasonal factors, month-to-month variations, and
plant utilization variances.
f
1. Sciles
Sales values are primarily influenced by plant size; however, the data
indicate that pack styles,- especially among small tomato plants, can in-
fluence the ratio of dollars worth of sales to tons of products processed.
2. Variable Costs
Variable costs include (1) the cost of the raw product delivered to the
plants for processing and (2) all other direct costs, including labor,
packaging materials, and other materials and supplies, and direct charges
not associated with overhead costs.
In general, most processing plants had raw product costs ranging from 20
percent to 30 percent of the total plant sales; however, these costs were
subject to wide variation by com/nodity (i.e., cabbage products ranged
between 17 percent and 19 percent and cherries processed in freezing plants
averaged approximately 59 percent). Similar variations held true for other
direct costs. (Some of these variations undoubtedly stemmed from plant
accounting and data reporting practices.)
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3. Fixed Costs
The wide variation among plants and products in the allocation procedures
for overhead and administrative expenses made difficult the determination
of model plant data for fixed costs; however, this wide variation was not
a limitation on the study's validity because of the study's use of reliable
data on profitability and sales.
4. Total Costs
Total costs varied by commodity and plant size; however, total costs were
less than 100 percent of sales for all cases. Survey data indicated that
a few plants operated at a loss in 1973, but these were offset when averaged
with all similar size plants.
5. Investment
Land is generally a minor part of fixed investment. Depreciation, when
related to total depreciable assets, shows ranges of from 6 percent to 16
percent, and single commodity plants generally grouped around 8 percent.
The higher depreciation ratios for multi-product plants probably reflect
their newer plants with current higher costs and possibly rapid deprecia-
tion schedules. Working capital estimates (based on a ratio of working
capital to sales derived from 1973 annual reports) show a fairly consistent
relationship of 23.2 percent (some variation exists by commodity).
6. Values and Costs Per Ton
The study analyzed the relationships for the 53 models between processed
volumes, sales, and costs per ton. Generally, for most commodities, total
costs decreased as size of plant increased. Raw product costs were usually
consistent within f-^oduct categories, but apparent differences did stem
from raw product procurement procedures (i.e., contract vs open-market
purchases or local area supply cmditions). Other direct costs generally
decreased with size or showed lictle variation among size groups.- Fre-
quently, overhead per ton of product processed increased with size (extra-
small plants had the lowest overhead ratios), and interest and depreciation
costs per ton tended to decrease.
C. Model Plan. Income
Though too detailed to be reflected in this summary, the study presented
a complete income statement for all model plants which were derived from
industry surveys and which feature sales, c'^ect and indirect costs, income,
profitability, and cash flow. All mode~; p^n's achieved a positive cash
flow for all plant sizes and for all co-morii, combinations.
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D. Return on Investment
The study's analysis of the model plants' returns on invested capital
yielded several general conclusions:
1. Multi-product plants have better returns than do single commodity
and specialty product plants.
2. Freezing plants average higher returns than do canning or de-
' hydrating plants (i.e., pre-tax ROI: freezers, 13.5%, canners,
11.7%; dehydrators, 5.9%).
3. Most model plant groups show rising rates of return by size of
plants (4 of the 15 groups are exceptions, however).
Possible Impacts
The ROI analysis indicated that serious potential impacts may stem from
added pollution control costs for plants with marginal (less than 6%} returns.
Most seriously impacted are the mushroom, corn, and potato chip plants.
Less potentially, but still seriously, impacted are pickle plants of all
s'izes and the three smaller tomato plants.
E. Value of Assets
The study utilized the industry survey of plants to evaluate the model
plants' salvage, book, and replacement values. The data indicated that
the recoverable value of total fixed assets ranges from 11 percent to 25
percent. Normal salvage rates would range from 12 percent to 15 percent,
and the high 25 percent appears unique to the small pickle plant where
land value is a uniquely high proportion of fixed asset value. Replacement
values average five times book values.
IV. PRICING EFFECTS
This chapter examines the pricing determinants of the fruit and vegetable
processing industries. To the extent that processors are unable to pass
through to consumers and suppliers the costs of added pollution controls,
those costs will intensify the economic impact of pollution controls on
the industries considered in this study. The chapter considers industry
demand, supply, pricing processes, processing and marketing margins, and
the anticipated price effects resulting from the imposition of effluent
guidelines.
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A. Demand
1. Trends in Demand
Long-run fruit and vegetable demand changes result from technological shifts,
population growth, diet trends and consumer taste and preference shifts,
and income changes. Short-term demands are closely related to supply-price
relationships. They are subject to seasonal variations, but once the carryin
and pack are established, the variations are moderate.
Some consumption trend indicators are (1) population, (2) per capita con-
sumption, (3) government purchases, (4) foreign trade, and (5) total pack
and carry-over by major product lines.
2. Per Capita Consumption
Vegetables. The study indicated that processed vegetable consumption by
"civilians" increased in the 1950-1974 period. As fresh vegetable con-
sumption decreased, total per capita processed consumption rose from 45 to
79 pounds, a 76 percent gain. Canned consumption during the period increased
by 33 percant and frozen per capita consumption by 582 percent.
The changing rates resulted, in part, from changing family living styles
which emphasized the need for convenience foods and less formal, less
heavy meals. Additionally, the technically improved home freezers and
freezer-refrigerator combinations made frozen products accessible to most
families.
However, 1974 saw a shift toward a decrease in processed food consumption.
The recent popularity of home gardens and the social and economic effects of
the recent ecological movement's interest in honid food preparation have con-
tributed to this trend. The 1974 decrease in overall processed fruit and
vegetable per capita consumption followed the general 1967-1973 period of
consumption shift leveling, a period which saw the gradual acceptance of
such products and major technological changes in home process food storage
appliances.
Fru its. Civilian per capita consumption of processed fruits also rose
between 1950 and 1973. Significant consumption trends were:
1. A continuing decrease in per capita consumption of fresh fruits,
2. A constant per ,apita consumption of canned fruits,
3. A gradual increc-e in that consumption for canned and chilled
juices (mostly the latter), and
4. A substantial, continuing increase in per capita consumption
of frozen fruits and juices with 88 percent of the increase
accounted f. v~ : . frozen citru, juices,
1 i i
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The changing pattern is, again, a reflection of the desire for convenience
foods. Too, the general increase in canned juice consumption stems in
large part fro.n the increasing use of apple juice for infants and children.
Though the consumption of canned fruits has increased generally, canned
juice consumption shows a more marked increase. Frozen fruits and juices
per capita consumption increased by 160 percent between 1950 to 1973 with
frozen citrus juices showing the greatest increase (403'") and organge juices
accounting for 92 percent of total consumption. Per capita consumption
tended to level off from 1967 to 1973. Dried fruits per capita consumption
has tended downward since 1950; however, since 1967, the rate has slowed.
3. Government Purchases
The government purchases of processed foods for the military, veterans,
child nutrition and needy family programs, though substantial for specific
fruit and vegetable products, are not major influences over processed food
demands. The reduction of military forces will result in reducing this
influence even further.
4. Exports
Although export figures for canned and frozen fruits and vegetables since
1967 show occasionally, heavy exports and sharp differentiations by product
(i.e., canned fruits and canned and frozen juices are most important; canned
vegetables and frozen fruits and vegetables are least significant), the
amounts represent only a small part of the total U.S. pack. Exports of
canned product^ are but 2.2 percent of the total U.S. canning pack, and of
frozen fruits and vegetables, only 1.1 percent of the total frozen pack.
5. Demand Characteristics
Too technical to be suniiiiarized here, this study examined the-demand and
price elasticities of the applicable processed fruit and vegetable products.
Generally speaking, the analysis based, in part, on the latest published
research, revealed product demand responsiveness to price increases, to
intra-industry product competition (i.e., product substitution),.and to
changes in consumer income levels.
In relationship to consumer expenditures, fruits and vegetables each
accounts for approximately 8 percent of total food expenditures and 1.9 per-
cent of total consumer expenditures. As a group, such food expenditures
were roughly equal to those for dairy, cereal, and bakery product segment
expenditures and half of those for meat. Data for 1955 to 1966 showed that
while fruits maintained their relative importance, vegetables had decreased
slightly.
xm
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B. Supply
The supply of processed fruits, vegetables and juices consists of three
parts: domestic pack, carryin from previous year's pack and imports. During
the past five years, total canned vegetable pack has increased 9.1 percent,
canned fruit packs were down 19 percent and canned fruit juice packs were
steady. Frozen vegetable packs were up strongly, up 41 percent, frozen
fruit packs were relatively steady and frozen juice packs (primarily frozen
orange concentrate) were up 61 percent.
Carryins for canned and frozen fruits, vegetables and juices for 1973-74 were
generally below levels of the past five years. Imports are not generally an
important supply source for most commodities, but are important in a few
products (e.g. mushrooms, pineapple, blueberries, etc.).
C_. Industry Pricing Processes
The fruit and vegetable canning, freezing and preserving industry is large
and complex in terms of the number and diversity of firms and plants and
is geographically scattered. It is highly competitive, both in terms of
product sales and raw product procurement. Due to the need for a predictable-
flow of uniform, high-quality products, it often negotiates production con-
tracts with growers which gives it a measure of control over quantities,
varieties and production conditions for raw products. In some states, pri-
marily in California, it operates under marketing orders which permit a
measure of control over the volume and/or quality of raw fruits and vegetables
used for processing.
D. Processing and Marketing Margins
The consumer's food dollar must pay for ill the materials and services in-
volved in producing, processing and distributing food. Large cost increases
in nearly all phases of processing and marketing—including labor, packaging
and transportation—are a major factor in widening margins and rising retail
prices.
Margins for different commodities and for different marketing functions vary
widely among products due, mainly, to differences in the amount and type
of processing, packaging ant. bulkiness.
Retail prices of most cann J and frozen fruits and vegetables increased in
1972-73. Higher prices for most processed deciduous fruits were mainly the
result of reduced supplies. Both the season's pack and carryin were below
xiv
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the previous year. Canned and frozen vegetable supplies were about the
same as a year earlier; however, higher processing costs and strong demand
resulted in price increases at the retail level. The marketing spread in-
creased, in absolute values, for most processed fruits and vegetables--
in some cases at a higher rate than the retail price increase. Overall,
the farmer's share of the retail food dollar for processed fruits and veg-
etables for 1973 averaged about 19 percent—about the same as in 1972.
E. Industry Organization and^Competition
Although a relatively small number of large, multi-plant, multi-product
firms process and distribute a high percentage of the total fruit and veg-
etable pack, the industry is still very competitive, no one firm being
dominant. There are large numbers of medium and small plants and while for
some products production is concentrated geographically, for others produc-
tion and processing is scattered throughout the United States. Plants tend
to specialize along functional (e.g. canning) and commodity (e.g. tomatoes)
lines. Although one product may be predominant, most plants pack two or
more different products through the same facility. Although specialized
canning or freezing plants exist, plants V;hich both can and freeze are
common. Processor share of the retail price normally account for 40 to 60
percent, with the 40 to 50 percent range being the most common.
Two major institutional factors exist in the fruit and vegetable processing
industry which affect raw products supplies and prices for fruits and
vegetables for processing. State marketing orders give growers and pro-
cessors a measure of control over the volume of products processed, either
through volume or grade and size proration. Grower-processor contracts tend
to establish prices packers will pay for raw products and introduce rigidities
into the raw product price.
F. Anticipated Price Impacts of Effluent Control Programs
Possibility of lower raw product prices — For most fruits and vegetables for
processing, grower margins are relatively low and have been decreasing. In
addition, growers have other production alternatives and in some commodities,
grower bargaining associations, grower-processor contracts and State market
orders tend to fix the price on the supply of raw product for his plant. In
addition, rising per capita and total demands put increasing pressures on
packers to expand supplies or to add to existing sources of supplies of raw
products for their plants. As a result of these forces, it is doubtful that
processors would be successful in efforts to compensate for increased costs
of effluent controls by lowering prices paid to growers for raw products.
Possibility of passing forward costs to consumer as higher prices--Two situ-
ations exist when consideration is given to the possibility of passing effluent
control costs forward to the consumer as higher prices:
xv
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1. In the short-run, there would appear to be little opportunity
for such cost transfer. The fruit and vegetable processing in-
dustry is extremely competitive and although large firms exist,
no one is dominant.
2. In the long-run, the ability of processors to pass forward cost
increases in the form of higher consumer prices will be dependent
on the demand characteristics for the individual products. In
general, better opportunities for price increases would exist
for those products having relatively low demand elasticities.
Even under long-run conditions, it is not expected that a complete
pass-through of costs will be possible since competitive con-
ditions in the industry coupled with consumer resistance to in-
creasing prices would restrict opportunities for price increases.
As a result, processors would be forced to absorb out of profits
most of the increased costs of effluent controls.
V. ECONOMIC IMPACT ANALYSIS METHODOLOGY
A. Fundamental Methodology
The economic impact analysis utilizes the basic data developed on industry
segments, financial profiles and price effects, together with pollution
abatement technology and costs developed by EPA. Impacts analyzed include:
Price effects
. Financial effects
Production effects
Employment effects
Community effects
Foreign trade effects
The determining force of plant shutdowns on these impacts is crucial; con-
sequently, the financial and production effects which most immediately
reflect plant shutdowns, were given most emphasis in this analysis.
In general, the approach used can be singly stated as the problem of deciding
whether a commitment of time or money tc a project is worthwhile in terms of
the expected benefits. The primary fact rs involved in assessing the finan-
cial and production impact of pollution onrpol are profitability changes
and these, in turn, are a function of th cost of pollution control and the
ability to pass along these costs as hig er prices. In reality, of course,
closure decisions are seldom made on the basi:; of well-defined economic rules.
Such decisions invariably include a wide rang - of personal values, external
forces such as the ability to obt^'n fin ncir;< r the role of the production
unit in an integrated larger cost center
xvi
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However, the analysis was made on the premise that economic returns in the
industry would be the primary determinants of plant closures. In the most
fundamental case, a plant will close when variable expenses (Vc) are greater
than revenues (R). A more probable situation is the case in which Vc < R,
but revenues are less than variable costs plus fixed, short-run cash over-
head expenses (TCc). In this situation a plant would likely continue to
operate in the short-run but would be forced out over a longer period of
time. Necessary to such a situation is the firm's expectation that revenues
will increase to cover total cash outlay. Identification of plants where
TCc > R but Vc < R leads to an estimate of plants that should eventually
close if revenues do not increase.
The next level of analysis, where TCc < R, involves estimating the earnings
before and after investment is pollution abatement. Under conditions in
which TCc < R, it seems likely that investment in pollution control will be
made and that plant operations will continue so long as the capitalized
value of earnings (CV) is greater than the salvage value of the sunk invest-
ment of the plant. Computation of CV involves discounting the future earnings
flow to the present worth. Discounted internal rates of return (the computed
discount rate, or yield, which produces a zero present value of the cash flow)
was the measure of profitability used. These rates of return, with and
without pollution controls and the estimated salvage values of plant, equip-
ment and land were the_major factors used to determine potential plant shut-
downs.
B. Price Effects
In order to provide a standard to reflect pri-ce effects, an estimated
price adjustment sufficient to offset required pollution control costs
was calculated. Application of the discounted cash flow procedure to pc^lu-
tion control costs yields present values and from this the price increase
required to pay for pollution control was calculated by the formula:
P = PVP (100)
V (1-T) (PVRT
where:
P = required percentage increase in price
PVP = present value of pollution control costs
PVR = present value of gross revenue starting in the year
pollution control is imposed
. T = tax rate appropriate following imposition of pollution
control.
xvii
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C. Shutdown Ana1ysi s
The study financial analyses were applied to model plant configurations
both before and after the imposition of pollution controls to determine
their effect upon a plant's ability to continue production. Based on the
results of the NPV of model plants, likely plant closures are identified
where NPV < 0.
D. Production Effects
A study of the technological characteristics of the industry and of industry
production practices underlay the analysis of probable changes in plant
capacity utilization and in the industry's ability to absorb capacity
losses as marginally productive plants are closed.
merit Effects
Given the production effects of estimated production curtailments, of plant
closings, and of changes in industry growth, employment effects were
estimated on the basis of known production-employment relationships.
F._ Community Effects
The effects of a plant's closing on its community and area employment overall
income, and its economic life were considered. Direct losses and those
consequent to multiplier effects were examined.
VI. POLLUTION CONTROL REQUIREMENTS AND COSTS
The pollution control requirements and their costs applicable to this
an~lysis were based upon information provided by the Effluent Guidelines
Division of
engineers.
generalizcd
information
these data,
generate-.1
the Environmental Protection Agency as developed by SCS
The basic data included ovcral" control requirements and
ccst information and specific [Dilution control cost
for individual fruit and vegetable processing plants. From
specific model plant pollution control cost data were
xvn
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A. Pollution Control Requirements
Three effluent control levels were considered:
BPT - Best Practical Control Technology Currently Available
(to be achieved by July, 1977)
BAT - Best Available Pollution Control Technology Economically
Available (to be achieved by July, 1983)
NSPS - New Source Performance Standards (to apply to any plant
whose construction begins after the publication of
the Standards regulations) (identical to those for BAT)
The effluent standards specific to individual product plant categories
were given for these levels; however, because such categories did not
include the processing of combined products, specific limitation guide-
lines were not available for all of the plants considered in this analysis,
Although individual processors may utilize any one of several effluent
treatment systems, this analysis considered only those recommended by
EPA.
For BPT levels: end-of-pipe biological treatment systems (aerated
lagoon or activated sludge)
For BAT levels: either of the BPT systems augmented by a multi-
media filter or chlorination
For both BPT
and BAT: land disposal by spray irrigation with zero runoff.
B. Pollution Control Costs
Based upon the provided EPA data, effluent treatment system costs were
calculated in a manner consistent with other portions of this study's
analysis. Except for the exclusion of land costs for spray irrigation
systems, all systems' investment costs include unit capital costs, land
costs, and engineering and contingency costs. Total annual cost was
considered to be the sum of maintenance and annual operation and capital
costs and assumed a 10% cost of interest, a ten-year asset depreciation,
zero salvage value, and a 100% recovery of land costs. Cost estimates for
all systems assumed no prior in-place treatment systems.
xix
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C. Selection of Effluent Treatment. System
EPA information indicates that 92% of current direct-to-watercourse
discharge plants will meet BPT guidelines by utilizing a biological
treatment system, and that the remaining 8% will adopt a zero discharge
land disposal system. Of those plants directly discharging to watercourses
in 1977, 91% will employ biological treatment systems and 9% will meet
the BAT guidelines through zero discharge land disposal.
The impact analysis considered both a high cost, activated sludge and a
low cost, aerated lagoon system. The Tatter's cost was also used
to represent that for spray irrigation systems.
P. Status of Wastewater Treatment
The data provided for this analysis by EPA indicate that 15% of the
fruit and vegetable processing industry plants (including 334 of the
2,202 plants considered in this study) have effluent discharges requiring
treatment. Of these 15%, 80% discharge directly into watercourses and
20% use spray irrigation systems with runoff.
All but 2% of the direct discharge plants presently utilize some form
of treatment, and these plants are the only ones which must expend
the estimated total costs to meet BPT standards. The remaining plants
will incur costs to a degree that reflects the adequacy of their present
treatment systems; thus, as indicated by the study's Table VI-7, to
meet BPT control requirements:
the 40% having in-place minimum jontrols will expend 85% of total
costs and the 44% having in-p'lar j moderate controls will expend
50%. The remaining 14% currently meet the BPT guidelines. All
direct discharge plants will incur additional costs to meet the
"ventual BAT standards.
ApjJJlcatjon of Effluent Control Guidelines
The EPA control leve- guidelines are applioble to the various sizes
of industry plants as follows:
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1. Plants processing 2,000 or fewer tons of raw product per
year are excluded from both the interim final and proposed
guidelines because the proposed treatment systems are not
economically feasible for such plants. The analysis in-
dicated that under the guidelines for BPT, 50% of these
plants would close and under BAT guidelines an additional 19%
would close.
2. Plants processing from 2001 through 10,000 tons raw product
per year must meet proposed BPT and BAT guidelines, but are
not covered by interim guidelines. For this group of plants,
the technology required to meet proposed BAT guidelines is the
same as for proposed BPT. Therefore, it has been assumed that
the additional costs due to BAT are negligible and that there
would be no incremental impacts due to BAT.
3. Plants processing more than 10,000 tons of raw product
per year must meet BPT and BAT standards. The latter
require that filtration be added to the aerated lagoon
or activated sludge systems.
The study indicated (see Table VI-9) that out of the estimated 330 direct
discharging plants, 47 or '\% meet BPT standards and six plants or 2%
have no controls in place.
VII. IMPACT ANALYSIS
The impacts associated with pollution control costs were applied to
the model plants included in this study and were based upon the phys-
ical and financial characteristics of those plants as previously des-
cribed. The impacts considered were as follows:
A.' Price Effects
B. Financial Effects
C. Production Effects
D. Employment Effects
E. Community Effects
F. Foreign Trade Effects
A. Price Effects
As pointed out in Chapter IV, the fruit and vegetable processing industries
have but limited ability to pass increased costs forward to consumers. The
recent leveling off and, in some cases, decrease in consumer demand, the
xxi
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inflationary conditions of the economy, and the rise in home gardening
combine to make price increases most untenable. Toor the industries
will be unable to pass increase costs backward to growers, for industry
supply conditions are governed by forces that deny market control to
the processing industries. The analysis indicated that processors will be
forced to absorb out of profits most of the increased costs of effluent
controls.
The impact analysis examined the ability of model plants to pass through
increased costs for BPT and BAT treatment levels by applying such costs
to the financial ratios of the plants. The analysis resulted, in part,
in the following generalizations:
1. Price increases required to offset such increased costs are
two to three times greater for activated sludge systems than
for aerated lagoon systems.
2. Price increases required to offset effluent control costs
when no treatment systems were in place were 84% of costs
when "moderate" controls were in place and were 48% of costs
when "minimum" treatment systems were in place.
3. Price increases required to offset BPT costs were 67% of
those required by BAT for aerated lagoons and 87% for
activated sludge systems.
4. Price increases required to offset effluent control costs
for extra-small plants, 2000 tons and under of raw product,
were generally severe (4% or above) at BPT and BAT levels,
and for small plants, 5000 tons and under raw product, such
increases were generally severe at BAT levels.
Industry conditions—the prevalence of plants discharging to municipal
treatment systems end the competitive presence of large plants whose
per unit treatment costs are lowest--will prevent industry plants from
independently raising prices to offset costs. Industry price increases
will reflect the lowest rates of increase that can be sustained by the
larger plants. It was concluded, then, that the most highly impacted
segments of the industry (see Table VI1-2) will not be able to overcome
these added costs by increasing processed product prices.
B. Financial Effects
The financial impacts of control costs on industry plants were assessed
by analyzing the effect of such costs on industry plant rates of return
and cash flows, Rntps of return were calculated en model plant invested
capital and on sales. The analyses included (Tables VII-4 through VII-8):
xxi i
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1. after-tax income,
2. after-tax return on sales,
3. after-tax return on invested capital,
4. annual ca^.h flow, and
5. net present value.
The results of such analyses both prior to and under the assumption of
imposed control costs, though too detailed to facilitate brief summary,
indicate that, in general, the smaller plants will be severely impacted
by such control costs and that the severity of such impacts increases
for BAT controls and for activated sludge treatment as opposed to aerated
lagoons systems.
The ability of the fruit and vegetable processing industries and of indi-
vidual plants to survive increasing costs will depend, in part, upon their
access to the capital investments required by control technologies. Ob-
viously such access to either internally or externally generated funds
will reflect (both before and after controls) a firm's profitability,
its competitive position, its investment "attractiveness" vis-a-vis other
investment alternatives, and its potentiality for continued and profitable
operations.
Such requirements pose problems for the food processing industries. Profits
vary considerably from firm to firm and year to year. Firm stability is
dependent, often, on seasonal availability of-supplies; small specialized
firms are susceptible to severe local impacts; increasing costs are a re-
sult of multiplying federal regulations arid energy requirements; small
plants are decreasing in numbers — in short, the industry faces a complex
of problems that argues that investment capital will not always be available
for industry plants.
In summary, then, in view of the problems facing small fruit and vegetable
processors and the substantial investments required for effluent control
systems, those plants may encounter severe problems in securing required
capital. Although large firms have greater ability to generate capital
from internal sources, from sale of securities and from borrowings, the
amounts of investment are large and the cost of acquiring capital is high,
so that capital availability will pose problems to many of these firms
as well.
Capital availability problems, although not quantified and explicitly con-
sidered in the plant closure analysis, were implicit in the closure pro-
jections made. The principal factors considered in the closure analysis,
other than required price increases, were financial performance factors.
Those plants with severe financial impacts resulting from pollution controls
were projected to close. In most instances, these plants were either mar-
ginally profitable or unprofitable in the absence of pollution controls.
xxm
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Because of their less-than-satisfactory performance, securing capital
for investment in pollution controls for these plants would be difficult.
For those plants which continued with acceptable levels of profitability
after the imposition of pollution controls, it is assumed that capital
availability would not present serious problems since these plants would
have the repayment capacity necessary to retire loans made to finance
pollution control systems.
C. Production Effects
This section of the impact analysis (1) segmented the industry apropos
of the study's model plants, (2) projected the industries' baseline
closures, (3) projected plant closures above a baseline and resulting
from pollution controls, and (4) calculated production losses resulting
from plant closures.
1. Segmentation of Industry to_Model Plants
a. Classification of plants and commodities
The study developed model plants to represent an industry-wide comparative
characteristic—plant processing function. These processing functions wer
1. blanched vegetables
2. pitted and/or peeled fruits
3. peeled vegetables
4. dehydrated fruits and vegetables
5. brined fruits and vegetables
6. reprocessed fruits and vegetables,
7. non-basic fruits.
and
A total of 54 commodities were so classified and the 1,360 plants listed
in the Directory which were applic'ble to the scope of this study were
classified by plant type" and commodities processed.
b. Total number of industry plants
To develop the total number of plants in each industry group, the model
plants and the corresponding number of industry plants were classified
into four-digit industry groups and the ratio of the number of plants
represented by each model to total plants in an industry group was applied
to total industry group plants shown in the 1972 Census. As applied,
industry plants listed in the Directory and used in this study were equal
to 62/, of the total listed in the Census.
xxiv
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c. Sizing of industry plants
Industry plant size groups were determined by Census data and modified
where necessary by Survey and Directory data. To show the character-
istics of plants within the four-digit industry groups, the data was
categorized into five size groupings: extra-small, small, medium, large,
and extra-large. To be as inclusive of Survey and Directory data as
possible, various model plants were representative of aggregate size
data. As specifically indicated, too, extra-small plants in particular
processing groups were not modeled since in those groups small plants
were projected as closures. Similarly, because particular processing
group plants of medium, large, and extra-large sizes are not expected
to be impacted to the point of closure, they wore not modeled (p. VII-39).
2. Baseline Closures
Baselines closures are plants which discontinue operations from a base-
line of 1972 and 1977 in this study and have been estimated through
trend analysis by industry group and size for 1977 and 1983.
a. Total industry
Overall plant numbers for the fruit and vegetable processing industry
are expected to decline from 1972 through 1983 at an annual compound
rate of about 2.5% per year with some increasing an estimted maximum
of 1.5% per year and others declining as much as 2.7% per year.
b. Industry group
Expected trends in plant numbers for each of the five plant sizes from
1972 through 1983 were projected for this analysis. Categorized by in-
dustry group, the~,e trends are briefly summarized here as follows:
Canned specialties (2032): These are expected to increase at an approxi-
mate rate of 1.5% per year. Only the X-small plants will decline in number.
The percent of medium to extra large plants will increase.
Canned fruits and vegetables (2033): These will decrease in numbers at an
annual compound rate of 1.5%. Only large size plants will increase in
number.
Pickles, dressings, and sauces (2035): Plants in this industry group will
decrease at an annual compound rate of approximately 1.8%. The numbers of
only the X-large size plants will increase.
Frozen fruits and vegetables (2037): The projected number of plants in this
industry is expected 10 show a compound annual rate of decline of 3.0% be-
tween 1972 and 1977 and 1.5% between 1972 and 1983. Only the large and
X-large size plant numbers will increase.
xxv
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__h Trend analysis
indicates that plant numbers in this industry (excluding apple, citrus,
and potato dchydrators) will increase at about a 1.07; compound annual
rate. All plant size categories will reflect increases.
_______ related products (20992)
This group or total plan£s is expected to decline at an annual compound
rate of approximately 2.37. Declines are anticipated in all plant size
categories.
3.
The analysis projected plant closures as a result of effluent control cost
impacts by considering a complex of both quantifiable and subjective
factors that included economic and financial relationships and knowledge
of industry conditions. Obviously such decision factors are not finite
and the resuHant closure projects are, in part, conjectural. In attempting
to objectify the closure analysis, the study assumed three levels of impact
that implicitly measured the intensity of the closure decision factors:
serious (the economic impact of control costs are, in the face of plant
operations, too severe to warrant installation of control equipment),
mejdjrum (the impact is sufficiently serious enough that a combination of
factors may force closure), and ripjrnrial (the impacts are not great enough
in the context of the plant's overall operation to force closure).
4. ^Closure Evaluation Procedu re_
The analysis evaluated the potential for plant closure by weighing the
closure decision criteria applicable to each plant model at each control
technology level and then projected plant closure numbers by estimating
the severity of the subsequently derived impact levels.
5. Projected Plant. Closures
Generally, the e-tra snvll and small plants were most highly impacted,
primarily because of economies • of scale which exist in pollution co'.t.j"!
costs. Additionally, those industry segments (e.g. the freezing inciusti.,
and pickle processors) having lower thin-average returns suffered. The
canning industry wa~ relatively less 1 ipacted than most because of its
higher proportion of .oth larger plant; and multi-product plants. ~;ble
yTI-27 shows the e-v^ated number of c'ant closures (direct disch^-g ,. .>)
by industry group under BPT and BAT technology levels.
6_. _ N . w Sou re e_Pe_rfp_r ;ra_n e_e__ Stonida rd s
As eej-lier indicated, NSPS effluent levels ; e the same as those for "" ,
levels A^s'i'ved achievable under present '" 'viology, land disposal c' rceii.s
rein- in the :; v. t c oiraMe cype jf coiit ol , "S standards should net-
prohibit the jn:ry of > , ,,• Tirms into t e . ry since such pi cits are
expected lo be large hey can incorpo at "'ant operating precedes
to minimize effK1 '"••" !• charges, and 0 T _, dia i°t ff" ce ^h^ r ' -., e
' 0'': si mi la» ri 70
xxvi
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7. Production Losses
As shown in Tables VII-28 and 29, the analysis estimated production losses
from plant closures for both BPT and BAT levels employing either aerated
lagoons or activated sludge systems. Since most plant closures are projected
to be only for X-sniall and small size plants, industry production losses will
be relatively minimal.
The exemption of small plants (2000 tons annual raw product volume and under)
from the proposed guidelines and the modification of BAT guidelines (made
equivalent to BPT) for plants in the 2001-10,000 tons category, minimized
the number of plant closures projected. Under these conditions, only 10
plants were projected to close due to BPT guidelines and 3 additional plants
as a result of BAT guidelines.
D. Employment Effects
Employment measures in the fruit and vegetable processing industry indicate
the importance of plant size on industry employment both in terms of num-
bers and plant labor efficiency: 10% of the industry's plants fall into the
extra-large category and account for 39% of industry employment and 49% of
sales. Conversely, employment measures show the relative employment sig-
nificance of the industry's extra-small plants: 45% of the industry plants
are so classified and account for only 7% of industry employment and 4% of
sales.
The closure of industry plants, largely confined to the smaller plants,
will result in a net decrease of employment. Though the limited excess
capacity in the industry will be able to absorb some displaced employment,
the analysis indicated that less than 50% of the employment losses could
be so affected. In most cases, too, the geographic dispersion of plant
closures would largely preclude the reemployment of personnel in new
plants since the industry's characteristically unskilled labor is generally
not mobile.
E_. Community Impacts
The severity of the effect upon a community of plant closure depends upon
a number of interrelated factors: the size of the community, the size of
the plant, the role of the plant in the community's tax structure, the
percent of the community's employment base dependent upon the plant, the
extent of the area's agri-business associated with the industry, and the
prevailing economic conditions of the area. Clearly, then, relatively
small communities can be severely impacted by the closing of even a small
plant, for the multiplier effects from lost employment income and lost
associated business income can be most extensive.
The fruit and vegetable processing industry is so widely dispersed that
all U.S. regions have small plants; however, the greatest relative con-
centrations are found in New England, the Atlantic Coast, the South Central
and the Intermountain States. Such regions also contain many of the
nation's most economically depressed areas. Plant closures, thus, can
be threatening to community existence in many localities.
xxv ii
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Illustrative of the problem is the plant "profile" developed by the NCA
in 1973 from a survey of some 400+ small fruit and vegetable plants:
a. Employees -- 63 full and 73 part-time
b. Local payroll -- $700,000 annually
c. Dependent farmer-growers --33
d. Community income generated -- $1.4 to 2.1 million
e. 50% of such plants associated with towns of less than 2,500
people
f. 75/o of such plants associated with towns of less than 5,000
people
F. Balance-of-Payments Impacts
Little impact on the exports of this industry are expected from the closures
of smaller plants since they play a minor role in the industry's export trade.
The imposition of effluent controls on plants processing mushrooms, straw-
berries, blueberries, and tomato paste could, however, seriously increase
the importation of these products into the U.S. since these processing
industries are presently experiencing adverse foreign competition.
. VIII. LIMITS OF THE ANALYSIS
The data used in this study were based upon government reports, trade
association reports and extensive contacts with industry firms. In
addition, the study utilized the results of -an extensive industry survey
of financial and production conditions designed specifically for the
study and implemencec by cooper?tinb industry trade associations. Effltsnt
control technology -nd current industry control system data were provided
by EPA. The study's data and < alyses were reviewed by both EPA and
industry trade source".
Tlk complexity of th: fruit and vegetable processing industry's production
and process product mix is extensive enouih to argue the uniqueness of
each plant in terms of its size and product combination and to preclude
the publication of definitive industry data. Much of the data for the
study1: analysis, therefore, required the development of such information
and "its presentation in "model" plant configurations. The models were
designed'to be "representative" of major plant configurations in the
industry and reflect a cross-section of tfose commodities, combinations,
processes, and plant sizes which exist in the industry. Categorized
by processing typo, product mix, and plant size, a total of 15 basic
models representing 21 commodities were synthesized to form a total
of 53 detailed representative plan :,. To the extent that the ana\y. >s
could not utilize actual and precise existing p' t data it is lifted,
but the model analysis employed does allow a dc- iled analysis which
would not be possible by using inductry a\iragoo ,one.
XXV 11
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B. Possible Range of Error
Estimated ranges of error for data used in this analysis are as follows
Error Range (%)
I. Number and type of plants +_ 5
2. Distribution of plants by size " -+ 10
3. Price data for products and raw materials +_ 5
4. Sunk investment costs + 15
5. Plant operating costs + 15
6. Effluent control costs +_ 10
7. Expected price changes +_ 5
8. Estimated plant closures + 15
C. Critical Assumptions
Among the major critical assumptions used in this report, made necessary
by the study's time, budget, and data constraints, were the following:
1. Data on plant types and sizes and on product types and
combinations as derived from published and unpublished
sources are representative of actual comparable conditions
in the industry.
2. Plant profitability levels and financial analysis were
based upon 80"o of the 1973 profit data under the assump-
tion that such 1973 data reflect uniquely "higher-than-
usual" profit levels.
3. The impacts of effluent controls on those commodities
not specifically included in the detailed analysis are
analagous to those which were analyzed. Such comparative
judgements were made for those processes especially associ-
ated with unit processes and specialty food processing.
xxix
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4. Assumed "baseline" 1977 and 1983 plant numbers reflect
current industry trends as depicted in the Census of
Manufactures and, except for potato chips plants., decreases
in plant numbers were assumed to be limited to the small
and extra-small plant categories.
5. Lmployee data were assumed to be adequately reflected by
the latest available Census data.
6. Effluent control costs and current status estimates as
supplied by EPA were assumed accurate.
D. Rente.ining Questions
1. A complete study of the impact of pollution control requirements
on the processed fruits and vegetable industry would require a finite
consideration of the effect on the industry of plants which are presently
connected to municipal effluent control systems. Such plants are subject
to user fees which are constantly rising and which, obviously, will
eventuate in cost affects and their subsequent economic impacts upon
the industry.
2. The use of the model plant approach necessarily raises questions
that cannot be practically answered under the study's contract restraints
concerning the definitive "representativeness" of such models, especially
when the models are used to analyze the operations of analagous product
processes.
3. A thorough analysis of effluent control costs would eventually
have to consider the variety of pr- sent and future regulatory practices
required for all types of appli'vab.e industrial pollution by other
state and federal agencies, loo, such an analysis would have to con-
sider the impact of such regulations upon the total complex of management
practices and attitudes.
XXX
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ECONOMIC ANALYSIS OF INTERIM FINAL AND PROPOSED EFFLUENT GUIDELINES
CANNED AND PRESERVED FRUITS AND VEGETABLES INDUSTRY
Canned Fruits and Vegetables, Frozen Fruits and Vegetables, Canned
Specialties, Pickles, Sauces and Salad Dressings, Dehydrated
Fruits and Vegetables, Potato and Corn Chips
I. INTRODUCTION
This study analyzes the economic impact of interim final and proposed
effluent control guidelines on direct discharging plants in selected
segments of the canned and preserved fruits and vegetables industry.
Where appropriate, there is brief and general discussion of the economic
impact of effluent control guidelines on plants discharging to munici-
palities. The study excludes the apple, citrus and potato segments of
this industry which were considered in an earlier study. ]_/ It is helpful
to note at the onset that model plants mentioned throughout the study were
designed to reflect direct discharging plants rather than all plants in
the industry.
A. Scope
The economic impacts "of effluent control guidelines on direct discharging
plants evaluated in this report are concerned with segments of this industry
designated under the following Standard Industrial Classifications:
SIC 2032 Canned specialties
SIC 2033 Canned fruits and vegetables
SIC 2034 Dehydrated fruits and vegetables-soups
SIC 2035 Pickles, sauces and salad dressing
SIC 2037 Frozen fruits and vegetables
SIC 2099 Corn and potato chips only
Within these SIC groups, emphasis will be focused on the following industry
segments:
1. Single-commodity plants
a. Tomatoes and tomato products, canned
b. Corn, canned and frozen
c. Cherries, ?v,'eet and sour, canned
d. Sauerkraut, canned
e. Mushrooms, canned
f. Pickles, canned
2. Multi-commodity plants
a. Corn, peas, canned and frozen
b. Corn, peas, green beans, carrots, canned and frozen
c. Peaches, pears, tomatoes, canned
d. Broccoli, brussels sprouts, cauliflower, asparagus,
spinach, frozen only
— Economic Analysis of Effluent Guidelines, Apple, Citrus and Potato Segments
of the Canned and Preserved Fruits and Vegetable Industry, EPA-230/2-74-012,
February, 1975.
1-1
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3. Specialty products plants
a. Tomato and dry beans, canned
b. Potato chips
The fruit and vegetable and related food specialties industry is large and
complex. Chapter II of this report describes the organization, structure
and segmentation of this industry. There is a large number of products
processed, canned, frozen or dehydrated and .the food specialties industry
combines fruits and vegetables with other products, for example grain or
meat products, in formulating a wide variety of prepared convenience foods.
Finally, fruit and vegetable processing plants are complex in that there
are variations in size, in combinations of products processed and in product
forms. For these reasons, it has been necessary to simplify this analysis
and to key on products and plant types which are representative of major
segments of the fruit and vegetable processing industry and which primarily
discharge to surface waters. Given the results of the analysis of these
"representative" plants, the indicated impacts will be extended to other
commodities and other types of plants in the industry by associating these
remaining commodities and plants with those representative plant types
having similar characteristics.
In selecting those commodities and plant types for "representative plant"
analysis, an attempt was made to select plant types which included major
volume products, plants which represented processors of vegetables, fruits
and specialty food products.
The designation of these specific types of direct discharging plants for
analysis was based on the following factors:
1. Importance of the segment as a part of the total fruit and
vegetable processing industry - in terms of volume and value
of pack.
2. The effluent characterist.es of the plants with regard to the
effluent control problems which exist.
3. The need to include single-commodity plants, multi-commodity
plants and food specialty plants.
4. The need to include plants which process fruits and plants which
process vegetables.
5. The need to include both canning and freezing plants and canning
plus freezing operations.
6. The need to include plants which represent realistic combinations
of products for processing.
7. The need to limit the number of model plants to be analyzed to a
workable nrnber that represe ts the majority of industry plants
directly d-.schanji" ) to surf, ce wrtcT - C3 model plants were
1-2
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analysed, both with and without controls--a total of 477
situations.
8. The need to include types of plants which will be representative
of broader categories of plants and which can be used to develop
generalized conclusions regarding the impact of effluent controls
on direct discharging plants not studied in detail.
9. Availability of required data, from government and industry, from
secondary and primary sources.
It is recognized that the 53 model plants included in this analysis cannot
be considered as fully "representative" of an industry as complex as the
fruit and vegetable canning, freezing and preserving industry. In fact,
the industry is characterized by a large number of "unique" plant situations
with varying combinations of raw products and finished products and complex
seasonal and locational processing operations. An attempt will be made to
extrapolate the impacts shown for the model plants to the remainder of the
industry by grouping plants on the basis of similar unit processes (blanching,
brining, oeeling, etc.), return on investment by similar unit processes and
effluent characteristics. These groups will then be associated with those
model plant situations which they resemble.
B. Organization
The analysis was organized into eight parts or chapters, as follows:
I. Introductory Statement
II. Industry Organization and Segmentation
III. Financial Profiles - Model Plants
IV. Pricing Effects
V. Economi^ Impact Methodology
VI. Pollution Control Requirements and Costs
VII. Economic Impact Analysis
VIII. Limits of the Analysis
Chapter VI, Pollution Control Requirements and Costs, was based on effluent
control systems and costs specified by the Effluent Guidelines Division,
Environmental Protection Agency, and these costs and systems were used in
the impact analysis.
C. Data Sources
Both secondary (published) and primary (unpublished) sources of information
and data were used in the analysis.
1. Major Secondary Sources included:
a. Census of Manufactures, Bureau of the Census, U.S. Department of
Commerce, Washington, D. C.
b. The_p_irectpry of the Canning, Freezing and Preserving Industries,
Edward L. Judge and Sons, Westminister' Md.
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c . The Almanac of the Canning, Freezing and Preserving Industries,
Edv/ard E. Judge and Sons, Westminister, Md.
d. Canned Food Pack Statistics, National Canners Association,
Washington, D. C.
e. 1974 Directory, American Frozen Food Institute, Washington, D. C.
f. Frozen Food Pack Statistics, American Frozen Food Institute,
Washington, D. C.
g. Who's Who in Potato Chip Institute International , Membership
Directory and Buyers' Guide, Potato Chip Institute, International
n- Fruit Situation, Economic Research Service, USDA
1 • Vegetabl e Si tuati on , Economic Research Service, USDA
j. Marketing and Transportation Situation, Economic Research Service,
USDA
k. Demand and Price Situation, Economic Research Service, USDA
1 • foreign Agricultural Trade, Foreign Agricultural Service, USDA
m- Agricultural Stati sties , various issues, USDA
n. Various bulletins and published research reports from Agricultural
Experiment Stations, Land Grant Universities, and USDA
o . Economic Analysis of Effluent Guidelines, Appl e_,_ Cjrt rus and Potato
J jnvd Preserved Fruits and Vegetab'l es Industry,
"
-_
EPA 230/2-74-012, Environmental Protection Agency, February, "1975.
2. Major Primary Sources included:
a. Survey data furnished by industry trade associations. Cooperative
arrangements were developed with major trade associations in which
they agreed to survey their members on a voluntary basis to develop
information needed in this analysis. Participating trade associ-
ations included:
* National Canners Association
* American Frozen Food Institute
* Potato Chip Institute International
* Pickle Packers International., Inc.
* Association of Dressings and Sauces
* National Preserves I r statute
* The Vinegar Institutf
A total of 322 responses were received from the industry association survey.
Returns were received from all associations with the bulk coming from -.the
National Canners Association and the American' Frozen Food Institute. Returns
represented 17 percent of all firms included in these associations and varied
from a 29 percent response from canners to 3 percent from the specialty food
associations. ~_,
A copy of the survey form used by these associations is shown in Appendix A.
1-4
-------
Pollution control information - Special analyses and tabulations
of the status of effluent controls in the fruit and vegetable
processing industry and of proposed effluent control systems
and costs were provided by the Effluent Guidelines Division,
Environmental Protection Agency and prepared by SCS Engineers,
Long Beach, California.
Other secondary information was developed through numerous per-
sonal contacts and telephone discussions vnth representatives of
industry trade associations, firms in the industry and other
specialists in state and federal government agencies, univer-
sities and private engineering and consulting firms.
1-5
-------
II. INDUSTRY SEGMENTATION
The fruit and vegetable processing industry includes many firms, plants,
products and styles of products. Many of the firms and plants have
diversified product lines and production processes. With the large
amount of variation which occurs, it is necessary to segment the industry
before describing typical direct discharging or model plants.
The objective of this section of the report is to provide characteristics
of the firms, plants and products in the fruit and vegetable canning,
freezing and dehydrating industries.
Standard Industrial Classification groups included in the analysis are
as follows:
SIC
2032 Canned specialties (soups, dry beans, and baby foods only)
2033 Canned fruit and vegetables (excluding apples'and citrus)
2034 Dehydrated fruits, vegetables and soup mixes (excluding
potatoes and apples)
2035 Pickled fruits and vegetables, vegetable sauces, seasonings
and salad dressings
2037 Frozen fruits and vegetables (excluding apples, citrus,
potatoes and frozen specialties)
2099 Food preparations, potato and corn chips only
Wherever possible in this chapter, most apple, citrus and potato (frozen
and dehydrated) data have been excluded to provide as meaningful comparisons
as possible relative to the scope of this report. The chapter sections will
specify whether these products have been included or excluded.
A. Characteristics of Fruit and Vegetable Canning,
Freezing and Dehydrating Industries
The fruit and vegetable processing industry segments vary greatly in magni-
tude of value of production, size and number of firms, integration, diversi-
fication, concentration, employment and payrolls. The characteristics of
the above mentioned variables as they relate to industry segments are con-
sidered in this section.
1. Value of Production by Segment
The value of production for the majority of the fruit and vegetable processing
industry under analysis in this report has increased from $4.2 billion in 1958
to $8.5 billion in 1972, a gain of 101 percent, as shown in Table II-l which
excludes apples, citrus, and potatoes (frozen and dehydrated).
II-l
-------
Table II-l. Value of industry production by segment, census years 1958-1972
SIC
Code
•>/
2032-'
2033-/
2035
rl
2037-'
2034-/
2099^
Industry Segment
Canner
Canned specialties
Canned fruits and
vegetables
Pickles, sauces
salad dressings
Total
Freezer
Frozen fruits &
vegetables
Dehydrator
Dehydrated fruits
& vegetables
Chipper
Potato and corn
chips
Total
Years
Unit
$ Million
%
$ Million
%
$ Million
%
$ Million
%
$ Million
%
$ Million
%
$ Million
%
$ Million
%
1958
828
20
1,984
47
496
12
3,308
79
336
8
276^
6
294
7
4,214
100
1963
947
18
2,339
46
619
12
3,905
76
454
9
292
6
466
9
5,117
100
1967
1,191
18
2,929
45
793
12
4,913
75
572
9
371
6
648
10
6,504
100
1972
1,630
19
3,423
40
1,165
14
6,218
73
714
9
501
6
1,042
12
8,475
100
Source: Census of Manufactures. Bureau of Census, U.S. Dept. of Commerce.
— Includes ethnic and hea-lth foods and meal products which are aot part of this
study. A sufficient Census breakdown was not a\"ii Table to separate soups, dry
beans, and baby foods which are part of this re^rt.
— Excludes apple and citrus products which re no part of this report.
— Excludes Frozen Specialties (as of 1972, 1C 20 } and frozen potato products
which are not part of this report.
Excludes dehydrated potato proaucts which --re m i part of this report.
e/
— Because o." insufficient information, dehydrated iotatc ?•• iducti are not excluded
f/
from 1953 data.
'; :Tudes Potato and Corn Jn'ns, Curls anc '"plat Pro ,
»~°port but excludes other Foor Preparatic s (SI 20'."":,,
..•hich are part of this
-------
a. Canners
All canning segments (SIC 2032, 2033 and 2035) represent the largest portion
of the fruit and vegetable processing industry with value of production ranging
from 79 percent of the industry total in 1958 to 73 percent in 1972 as shown
in Table II-l. The relative importance of canned specialties (SIC 2032)
and pickles, sauces and dressings (SIC 2035) segments of canning have
remained nearly constant while the relative importance of canned fruits
and vegetables (SIC 2033) has declined.
The value of production of the three canning segments has increased from $3.3
billion in 1958 to $6.2 billion in 1972 or 6 percent annually.
b. Freezers
The frozen fruit and vegetable segment is the second largest in the process-
ing industry in terms of value of production. Its relative importance in
terms of total value of production for the industry has ranged from 8 percent
in 1958 to 9 percent in 1972.
The value of production of frozen fruits and vegetables segment has increased
from $0.3 billion in 1958 to $0.7 billion in 1972, a gain of 133 percent or
9 percent annually.
c. Dehydrators
The value of production of dehydrated fruit and vegetables has remained at a
constant 6 percent of the production value for the total processing industry
from 1958 to 1972.
In absolute terms the value of production of dehydrated fruits and vegetables
increased from a little under $0.3 billion in 1958 to $0.5 billion in 1972
or an overall gain of 67 percent or 4 percent annually.
The potato and corn chip, curl and related product subsegments of the food
preparations segment (SIC 2099) have increased from 7 percent of total
processing industry production in 1958 to 12 percent in 1972.
The value of production of these subsegments has increased from $0.3 billion
in 1958 to about $1.0 billion in 1972, a gain of 254 percent or 17 percent
annually.
2. Size and Number of Firms
Data sources were not available to provide a true measure of size of firms
(production per day) in the fruits and vegetable processing industry. Sizing
by production per day puts firms or plants with varying volumes and season
lengths into perspective on a common denominator basis. Data on annual
volume packed by canning and freezing firms v/ere available and gives an idea
of how the industry is grouped by size of firm.
II-3
-------
This section excludes most apple, citrus and potato (frozen and dehydrated)
data except section A., 2., c and Table II-4.
a. Canners
A detailed analysis was made of the volume packed (in terms of cases of
canned product) for 657 canning firms. It should be emphasized that this
analysis is in terms of physical volume rather than gross sales. Table II-2
indicates the number and percent of firms in each annual volume category.
Over half of the firms analyzed (54%) were considered small canners with
an annual pack of less than 500,000 cases. At the other end of the range,
24 percent packed over 2,000,000 cases and were classed as large and 8
percent of the canners packed over 5 million cases annually and were considered
in the very large group.
The Directory is felt to be a good source for determining the characteristics
of the fruit and vegetable processing industry. However, due to unmeasurable
variance between years in changes of addresses, response to questionnaires
by old and new firms and change in ownership, trend analysis would be
inconclusive. Thus, analyses similar to Table II-2 above of past Directories
were not included.
The number of plants per firm is considered in another subsection of this
Chapter.
The 1974-75 Directory lists 930 firms which have products consistent with
the scope of this report. Of these, 751, or 81 percent, did all or some
canning of fruits and vegetables. Oi i, of these 751 firms, 640, or 85 percent,
were strictly canners. The other 15 oercent, or 111 firms, had plants,
in addition to carmine,, that froze an '/or dehydrated products within the same
plant(s) or between
in the same plant.
b. Freezers
Annual ••<">) jnie data were available "re
The distribution of sizes of these fi
hc process frozen specialties e
them; over h?"1 ;> of the 111 canned and froze products
> 216
•
-------
Table II-2. Size distribution of fruit and vegetable canning firms, 1974-
Annual
i Size volume in
Category 1,000 cases
imall
ledium
arge
otal
ource:
Under 100
100-249
250-499
500-999
1,000-1,999
2,000-4,999
5,000 and over
Judge, Edward R. and
Number of
firms
140
101
113
94
52
101
56
657
Sons, The
Total percent
Percent of total in size category
21
16 54
17
14
8 22
16
8 24
100 100
Directory of Canning, Freezing and Preserving
Industries, 1974-75.
Excluded from this table are firms which process only canned apple or citrus
products.
II-5
-------
Table II-3. Size distribution of fruit and vegetable freezing firms, 1974.-
Size
Category
Small
Medium
Large
Total
Source:
Annual
volume in
million Ibs.
Less than 2
2-4.9
5-9.9
10-19.9
20-49.9
50-99.9
100 and over
Judge, Edward E. and
serving Industries,
Number of
firms
72
21
26
38
20
17
22
216
Sons, The
1974-75.
Percent of total
33
10
12
18
9
8
10
100
Directory of Canning and
Total percent
in size category
55
27
18
100
Freezing and Pre-
- , >
- Excluded from thistable are firms which process only frozen apple, citrus,
or potato products.
II-6
-------
c. Dehydrators
The 1974-75 Directory has too few fruit and vegetable dehydrating firms (13)
showing size information to provide a representative and comparable series,
i.e., number of firms by annual volume packed. The best alternative is to
present the number of dehydrators by employment class. These data are avail -
Table for census years 1954-1972 from the Census of Manufactures and is
tentatively summarized below in Table 11-4 which includes apples, citrus
and potatoes. The employment size groups are subject to change so as
to correspond to subsequent chapters of this report regarding impact
analysis. Census data concerning the number of canned and frozen fruit
and vegetable processors by employment size is also presented in this
table to provide insight and perspective into the relative importance
of the six industry segments.
3. Degree of Integration
There is only a relatively small amount of vertical integration in the fruit
and vegetable canning, freezing and dehydrating industries. Based on a
special canner survey by the Economic Research Service^ U.S. Department of
Agriculture in 1964, it was estimated that only 8 percent of the fruits and
vegetables canned were obtained from land owned or rented by canners. A
comparable situation existed in the freezing industry where only 9 percent
of the raw product was obtained from freezer-owned or rented land.
Over two-thirds of the supply of fruits and vegetables processed by canners
and freezers is obtained through contractual arrangements with growers.
Contracting with growers has provided a means whereby canners and freezers
can reduce the risk of raw product supply variations from year to year with-
out investing capital resources directly into farm production. Thus, they
avoid the necessity of integrating backward into production..
Canners and freezers also have never integrated very far forward into whole-
sale and retail trade. Some large processors do maintain sales offices in
principal wholesale markets; however, brokers handle over two-thirds of the
sales of processed fruits and vegetables. A comparable situation is be-
lieved to exist for the dried and dehydrated food processing industry
especially in the dehydrated potato industry which also makes extensive use
of contractural grower processor arrangements.
4. Industry Diversification and Specialization
Most fruit and vegetable processing firms are not highly diversified outside
of kindred food products considered in this report. However, most canning,
freezing and dehydrating plants are highly diversified into multiple products
and lines of fruits, vegetables and juices.
It follows that these processors are highly specialized. Part of this spec-
ialization is location-oriented since they are located near fruit and vege-
table production and the other part is equipment-oriented, i.e., specialized
equipment is required.
II-7
-------
Table II-4. Fruit and vegetable processing establishments by number of
employees and industry segment, census years 1954- 1972.
SIC
Code
2032-/
2033
2035
2037-/
2034
209 9^
Sources :
Industry
segment
Canner
Canned
specialties
Canned
fruits &
vegetables
Pickles,
sauces &
salad
dressings
Total
Freezer
Frozen
fruits &
vegetables
Dehydrator
Dehydrated
fruits &
vegetables
Chipper
Potato- and
corn chips
Percent of establishments with employees totaling:
Year
1954
1958
1963
1967
1972
1954
1958
1963
1967
1972
1954
1958
1963
1967
1972
1954
1958
1963
1967
1972
1954
1958
1963
1967
1972
1954
1958
1963
1967
1972
1954
1958
1963
1967
1972
1-4
NA
14
31
30
32
21
18
19
23
21
39
36
36
39
35
NA
22
25
28
26
16
12
21
22
;2
31
30
24
29
29
40
37
38
42
40
5-19
NA
22
24
22
25
22
25
22
17
19
30
31
33
27
27
NA
27
25
20
22
21
26
25
18
6
26
28
31
26
-22
33
37
37
28
29
Census of Manufacture1;. Bureau of
Statistical
Bulletin
490, Potatoes
20-99
NA
33
22
22
20
41
39
38
36
33
23
25
22
25
27
NA
35
33
31
30
39
33
30
31
39
28
26
32
26
29
21
20
20
24
23
100-249
,„.
NA
10
8
12
9
11
13
15
17
18
6
5
7
6
7
NA
11
12
13
14
18
21
15
18
27
11
13
p
12
11
5
4
4
5
6
the Census. U.S.
and Sweet
Potatoe
Nuinhpr nf
250 or more establishments
NA
21
15
14
14
5
5
6
7
9
2
3
2
3
3
NA
5
5
7
8
6
8
9
11
26
3
3
5
7
9
1
1
2
1
2
Dcpt. of Commerce.
s, CRB, SRS, USDA.
NA
107
173
175
203
1,758
1,607
1,430
1,223
1,038
717
619
588
527
495
NA
2,333
2,191
1,925
1,736
230
260
258
209
209
148
161
175
178
178
NA
412
358
314
256
Includes ethnic and health foods and meat products which are not part of this
study. Census data were not subsenmentcd to those canned specialities (SIC 2032)
considered in this report (soups, dry beans and baby foods).
Includes frozen specialties (SIC 2038) prior to 1972 and apples, citrus
and potatoes which are not part of this report. Census data were not
previously subseymonted to Frozen Fruits and Vegetables. Number of
establishments exclude frozen specialties only.
Includes all Food Preparations (SIC 20°Q). Census data wore not subseqmcnted to
corn atv! potato cliij uris ar,.! re-Tat J products. Therefore, this distribution of
' Mil ir.hr,untc intv not ••'^'"•psont the- d';t ribut ion of "Mato chip nstibl ishments.
Number of ^Uu-l islim -its WLIL tal.en f n » Statistical L^Uetiii 490.
II 8
-------
The Bureau of Census calculates specialization ratios for different types of
industries. These represent the ratio of sales value of all the primary
products of the plant to its total of primary plus secondary products.
Apple, citrus and potato data are included in this section of the report.
a. Canners
Canned Specialties - In 1972, the specialization ratio was 81 percent. Thus,
the value of sales of canned dry beans, baby food, soups, ethnic and health
foods represented 81 percent of total sales of these plants. Secondary
products shipped by this industry segment were mainly fruits and vegetables
(SIC 2033) and prepared meats.
Canned Fruits and Vegetables (SIC 2033) - This industry segment's value
of primary products shipped was 89 percent of its total product shipments.
Secondary products were primarily canned specialties and frozen fruits
and vegetables, bottled and canned soft drinks, pickles, sauces and salad
dressings and food preparations.
Pickles, Sauces and Salad Dressing (SIC 2035) - The specialization ratio
was 80 percent in 1972. Secondary products were mainly canned and dehydrated
fruits and vegetables, food preparations, shortening and cooking oils.
b. Freezers
This industry's production of frozen fruits and vegetables (primary products)
in 1972 represented 86 percent (specialization ratio) of its total product
shipments. Secondary products consisted mainly of canned fruits and vegetables,
frozen specialties and bottled and canned soft drinks.
c. Dehydrators
Dried and Dehydrated Fruits and Vegetables (SIC 2034) - The specialization
ratio for dehydrators was 95 percent in 1972. Secondary products were mainly
food preparations.
Food Preparations (SIC 2099) - The specialization ratio for potato and corn
chips, curls and related products was 97 percent in 1972.
• 5. Concentration of Production in the Fruit and Vegetable Processing Industry
Local area processing concentration has little meaning to fruit and vegetable
canning, freezing and dehydrating industries. Plants and firms located in
any region are potential competitors to-those producing the same product
lines in all other regions; therefore, concentration by value of production
rather than region is an important consideration.
II-9
-------
The fruit and vegetable processing industry is characterized by a few firms
in each SIC industry group, of which the largest 50 account for 70-99 percent
of total value of shipments.
Table II-5 presents concentration ratios which show the percent of value
of shipments accounted for by the 4, 8, 20 and 50 largest companies for
the six industry segments. The 50 largest firms in each segment are of
increasing importance since they accounted for a weighted average of 79
percent of total shipments in 1963 and 83 percent in 1967. This section
and Table II-5 include apple, citrus and potato data.
a. Canners
The four largest firms from the combined three canning segments (SIC 2032,
2033, and 2034) accounted for over one-third of the value of oroduction .
and the 50 largest were responsible for 78 percent in 1967. However, in the
major segment (SIC 2033) canned fruits and vegetables concentration is lower,
the 4 largest accounting for 21 percent and the 50 largest for 65-70 percent.
The canned specialty segment has the highest degree of concentration; i.e.,
large firm domination (concentration ratio, 99 percent for 50 largest com-
panies), of the three canning segments. The remaining one percent of value
of production was accounted for by 100 small firms in 1967. The 50 largest
firms in the canned fruit and vegetable segment accounted for a lower per-
centage (70%) of the total value of production than was true for the other
canning, freezing and dehydrating segments.
b. Freezers
The four largest companies in the frozen fruit and vegetable segment, ex-
cluding frozen specialties accounted for about one-third of the value of
shipments in 1967. This group of freezers has a high degree of concentration
with a ratio of 93 percent for the 50 largest companies.
c. Dehydrators
The two dehydrating segments have a high degree of concentration. The ratios
are 96 and 87 percent accounted for by the 50 largest firms for dehydrated
fruits and vegetables, and potato and corn chip processors, respectively.
The remaining production is accounted for by numerous small firms.
6. Total Employment in the Industry
The fruit and vegetable canning, freezing and dehydrating industries are
major employers of labor in the areas in which they operate. Further, they
employ a high proportion of low-skilled seasonal workers in relation to total
employment in the industry. As a result, curtailment of these processing
industries would have an important impact on employment in the lower income
levels in the areas concerned as well as the local agricultural and business
community.
11-10
-------
Table II-5. Percent of value of shipments accounted for by largest
companies in industry segments a/
Value of Shipments
Total"
SIC
Code
Industry
segment
Year
Million
dollars
Percent accounted
Companies
4 Largest
8
Largest
for by companies:
20
Largest
bO
Largest
Canners
2032k/ Canned 1970
specialties 1967
1963
2033
2035
Canned fruits 1970
& vegetables 1967
1963
NA
1,191
947
NA
3,222
2,584
Pickles,
sauces and
salad
dressing
Total
Freezers
1970
1967
1963
1970
1967
1963
NA
2037 £/ Frozen fruits 1970
& vegetables 1967
1963
Dehydrators
793
619
NA
5,206
4,150
NA
1,073
832'
NA
150
154
NA
930
1,135
NA
479
541
NA
1,559
1,830
NA
243
323
66
69
67
21
22
24
38
33
36
NA
34
36
NA
32
33
81
83
83
33
34
34
51
44
46
NA
47
47
NA
49
49
NA
94
94
NA
52
50
NA
62
64
NA
63
62
NA
73
70
NA
99
99
NA
70
66
NA
80
79
NA
78
75
NA
93
89
2034
2 099 i]
Total
Dehydrated
fruits &
vegetables
Potato and
corn chips
Canners ,
Freezers &
Dehydrators
1970
1967
1963
1970
1967
1963
1970
1967
1963
NA
451
335
786
589
418
NA
7,319
5,735
NA
134
126
278
314
358
NA
2,250
2,637
33
32
37
NA
41
41
m
34
36
52
50
56
NA
55
51
NA
48
48
N
75
80
NA
72
69
NA
66
65
NA
96
96
NA
87
84
NA
83
79
Source: Census of Manufactures, 1963, 1967 and Annual Survey of Manufactures 1970.
Statistical Bulletin 490, Potatoes and Sweet Potatoes, CRB, SRS, USDA.
NA - not available.
— Table II-5 includes apple, citrus and potato data.
b/ Includes ethnic and health foods and meat products which are not part of this contracted
study. There was not sufficient breakdown of Census data to provide estiamtes of
establishments for those canned specialties considered in this report (soups, dry beans
and baby foods).
d/
The value of shipments are actual for the subsegments considered in this report. 'With
frozen specialties (as of 1972, SIC 2038) excluded, the value of frozen fruits and
vegetables were 57K and 492 of total shipments (SIC 2037), 1963 and 1967 respectively.
The estimates of the number of companies were percentaged accordingly. Percent of
value of shipments accounted for by companies also excludes frozen specialties.
The value of shipments are actual for the subsegments (years 1963 and 1967) considered
in this report. With the value of potato and corn chips, curls and related products
at 21% and 24Ao of total shipments, 1963 and 1967 respectively, 1970 was estimated at
25%. The estimates of the number of companies were taken from Statistical Bulletins
490. Percent of value of shipments accounted for by companies also excludes other
food preparations.
11-11
-------
In this section, A., 5., a and b includes o;>pie, citrus and potato industry
employment and payroll data to show comparisons between years. However,
section A., 5., c. shows employment and payroll by SIC code industry
group for 1972 with nearly all apple, citrus and potato (dehydrated and
frozen) firms excluded and will relate to later chapters on economic
impact.
a. Number of Employees
Canning Industry - The total employment in the three segments of fruit and
vegetable canning plants in 1972 was 139,700 down from 147,100 in 1967 and
152,100 in 1957. The canned specialty and pickle, sauce and dressing
segments have increased employment from 1958 to 1972 by 14% while canned
fruits and vegetables have declined 17 percent. A large percentage (86 per-
cent) of all employees in the three segments consisted of production workers
(1972). Plants employing more than 20 people have been 51-52 percent of total
plants in 1958, 1967 and 1972. These segments are, in terms of employment,
by far the most important with approximately 63 percent of the total
employment in all six industry segments combined.
Freezjna Triai-st^v - employment data from the Census was not broken down
r.Mweer fr":..•'• f ;••>.• it-
-------
Dehydrating Industry - The dried and dehydrated fruit and vegetable plants
employed 11,100 in 1967 and 12,400 in 1972. Eighty-five percent of 1972
employees were production workers. This dehydrating segment represents 6
percent of the total employees in the six segments of this report.
Potato and corn chips, curls and related product plants employed 25,200
in 1967 and 27,200 in 1972, an 8 percent increase. The employment in 1972
represents 15 percent of the total employment in the combined six segments.
b. Industry Payrolls
Canning Industry - In 1972, annual payroll in the three canning industry
segments totaled $923,900,000, an average of $532,200 per plant. Production
payrolls equalled 78 percent of total payroll in 1972. The average annual
earnings per employee was $6,526 in 1972, up from $4,973 in 1967.
Freezing Industry - Total annual payroll in the frozen fruit and vegetable
industry in 1972 was $261,800,000. Production payrolls equalled 80 percent
of total payroll in 1972. Average annual earnings per employee was $6,102
in 1972. Judging from both freezing segments, earnings increased about
one-third from 1967.
Dehydrating Industry - Total payroll for the fruit and vegetable dehydrating
industry was $84,300,000 in 1972. Production workers claimed 74 percent of
the 1972 payroll. Average earnings were $6,768 per employee in 1972.
In 1972, there were 27,200 employees in plants processing potato and corn
chips, curl and related products. Total payroll was $205,700,000 and averaged
$7,562 per employee.
Although annual average earnings represent the contribution of these industries,
it must be recognized that these payrolls are seasonal and that employees'
monthly earnings from these industries are greater than.annual data would in-
dicate.
c. Industry Employment a-nd Payrolls, 1972 (excluding nearly all apple,
citrus and potato (frozen and dehydratedT"firm data)'
The number of employees and corresponding payrolls shown below will be
referred to in later chapters of this report.-
SIC Industry Group Employees Payroll
(000)($ mil)
Canned Specialties 29.1 217.8
Canned fruits and vegetables 83.0 517.3
Pickles, sauces and dressings 20.8 146.2
Total Canners 132.9 881.3
Frozen fruits and vegetables 17.0 103.7
11-13
-------
SIC Industry Group Employees Payro11
(000) T$mTlT
Dehydrated fruits and vegetables 11.2 75.8
Potato and corn chips 27.2 205.7
Total dehydrators 38.4 281.5
Total 1&8.3 1,2667s"
B. Number of Plants and Employees in Each Segment
An important aspect of the analysis is the number of plants and employees
in each industry segment. This information for the most recent census
year, 1972, is summarized in Table II-6 and excludes nearly all apple,
citrus and potato (frozen and dehydrated) data. The number of plants
and employees shown in Table 11-6 will be used as the parameters in the
impact analysis in subsequent chapters of this report.
As shown in Table 11-6, canners comprise 75 percent of the plants in the
combined six segments of this report and 70 percent of the employees.
Freezers of fruits and vegetables, excluding frozen specialties, comprise
6 percent of the plants and 9 percent of the employees. There were 209
freezing plants listed in the 1972 Census of Manufactures Industry Series
of which 80 (38 percent) were estimated to be apple, citrus, and potato
freezing plants. The estimates were made by obtaining ratios from the
Directory ]_/ and applying them to Census data.
Dehydrators are estimates to have 19 percent of the plants and 21 percent
of the employees of the combined six segments of this report.
C. Characteristics of^Fruit and Vegetable Canning
Freezing and Dehydrating Plants
A more convenient, readily available, and in some cases a more meaningful
summary is derived by segmenting the industry by plant characteristics
rather than by firm characteristics. This summary is more meaningful in that
operating decisions are based on individual plant data as opposed to firm
data. Operating or closure decisions will be made on plant by plant
basis within the muHi pi ant firms in that some plants may share a dis-
proportionately large share of the total burden of mandatory pollution
abatement standards and will be closed while perhaps newer, more efficient
and profitable plants will he virtually unaffected.
— Judge, Edward F- and Sons, The D're:tory nf Canning, hree2:ing and Pre-
serving Indust ies, --4-75,
r-i
-------
Table II-6. Number of plants and employees by industry segment, 1972.
Industry
SIC
203 2-f
2033--7
2035
Total
2037-/
2034-7
2099
Total
Segment
Name
Canners
No. of plants
(No.) (%)
Canned specialties 203 9
Canned fruits and
vegetabl es
Pickles, sauces,
salad dressings
Canners
Freezers
Frozen fruits and
vegetabl es
Dehydrators
Dehydrated fruits
and vegetables
Potato and corn
chips
Canners, freezers
dehydrators
Source: Census of Manufactures
959 44
and
495 22
1,657 75
129 6
160 7
256 12
2,202 100
, 1972.
No.
empl
(000)
. 29.1
83.0
20.8
132.9
17.0
11.2
27.2
188.3
of
oyees
(«)
15
44
11
70
9
6
15
100
— Includes meat products, ethnic and health foods, not part of this report.
— Excludes plants processing only canned apple or citrus products which
are not part of this report.
— Excludes frozen specialties which are SIC 2038 as of 1972 and plants
processing only frozen aople, citrus, or potato products which are
not part of this report.
— Excludes plants processing only dehydrated apple or potato products which
are not part of this report.
11-15
-------
A variety of plant characteristics including size, location, number, utilizatic
and efficiency are presented in the following discussion. Sections C, 1-b and
exclude nearly all apple, citrus and potato (frozen and dehydrated) data
while section C, 6 and Table 11-13 includes them.
I/ Number and Location of Plants
A summary of the 1974-75 Industry Directory— indicates that there are
1,390 fruit and vegetable canning, freezing and other fruit and vegetable
processing plants listed in this report. This includes 994 fruit and
vegetable canners, 229 fruit and vegetable freezers, 111 plants that can
and freeze fruit and/or vegetables in the same plant and 56 that had other than
canning and freezing processes, e.g., can-freeze-dehydrate. Table II-7
presents the total number of fruit and vegetable canners, freezers and
combination plants listed in the Directory by region.
Table II-7 shows that all regions contain fruit and vegetable canning
plants, 333 or 33 percent of them in the North Central region. All regions
also contain freezing plants with the majority of them in the Northwest
(27%) followed by the North Central States (25%). Combination canning-
freezing plants are located in all regions with the least number being
in the South Atlantic and South Central regions. Those plants which have
processes other than or in addition to canning and/or freezing are most
prevalent in the Southwest (28%).
Since the Directory is not representative of dried and dehydrated fruits
and vegetables under analysis in this report, data from the Census, Potato
Chip Institute International and USDA are shown in Table 11-8 below.
Similar information for canning and freezing plants are also shown to
provide additional perspective into the six industry segments.
Table II-8 indicates that most of the dried and dehydrated fruit and vege-
table plants are in the West (73%). Most of the potato and corn chip
industry is located in the North Central states (41%) followed by the
North Eastern region (25%).
2. Size of Plants
The fruit and vegetable processing plants were segmented into five size
groups to illustrate the size configuration of the industry. Although each
industry group was sized individually to reflect its particular character-
istics, the size groups followed a general pattern. The concentration of a
major portion of total production in a small number of plants results in a
relatively large number of plants in the extra small and small size groups
and relatively few plants in the extra large group.
- Directory of the Canning, Freezing and Preserving Industry, Edward E.
Judge and Sons, Westminister, Maryland.
11-16
-------
Table II-7. Number of fruit and vegetable canning and freezing plants
by type and economic region, 19741/
Type of
plant
1
2
Region —
3 4
5
6
Total
Percent of
total plants
Canning
Freezing
Both canning
and freezing
Other-7
Total
Percent of
total plants
183 150 333
37 21 52
26
9
7
4
31
7
104 68 156
16 62 41
7 23 17
10 10 16
255 182 423 137 163 230
994
229
111
56
1,390
72
16
8
4
18
13
30
10 12
17
100
Source: Judge, Edward E. and Sons, The_ Pi rectory of the Canning, Freezing,"
and Preserving Industries, 1974-75.
— Excluded from this table are plants which process only apple, citrus,
frozen potato, and dehydrated potato products.
— Regions:
1.
2.
3.
4.
5.
6.
North Atlantic
South Atlantic
North Central -
South Central -
Northwest -
Southwest - '
ME, NH, VT, MA, RI, CT, NY, PA, NJ
WV, VA, MD, DE, NC, SC, GA, FL.
ND, SD, NB, !'S, MM, IA, MO, WI, IL, IN, OH, MI
NM, OK, TX, AR, LA, KY, TN, MS, AL.
WA, OR, ID, NV, MT, WY, UT, CO, AK.
AZ, CA, HI.
3/
— Other plants are those who could not be classified as canners, freezers or
both such as dehydrators, canner-freezer-d.ehydrator or process into
packages or cartons in addition to canning and/or freezing.
Table II-9, based on Census data, shows the number of plants and ranges of
production (tonnage and value) and employees per plant by size and industry
group. Industry group, four digit, concentration ratio functions were de-
veloped using 1967 percentages (1972 yet unpublished) of total plants, pro-
duction, employees and payroll and applying them to 1972 Census data of
11-17
-------
Table II-8. Number of fruit and vegetable processing plants by Census region,
1972I/
SIC •
Code
2032
2033
2035
2037
2034
2099
Regions^/
Type of Plant
Canner
Canned specialties
Fruits and
vegetables
Pickles, sauces &
salad dressings
Total canners
Freezer
Fruits and
vegetables
Dehydrator
Fruits and
vegetables
3/ '
Corn and potato-'
Total
I
47
203
115
365
12
19
64
456
II
41
264
150
455
36
15
105
599
III
52
236
108
396
2.0
10
38
457
IV
63
256
122
441
61
116
49
647
Total
plants
203
959
495
1,657
129
160
256
2,202
Percent of
all plants
9
44
22
75
6
7
12
100
Sources: 1972, Census of Manufactures.
— Excludes plants which process only apples, citrus, frozen potatoes, and
dehydrated potato product.
2/
— Regions:
I Northeast - CT, MA, ME, NH, NJ, NY, RI, VT, PA.
II North Central - IA, IL, IN, KS, MI, MM, HO, NE, NO, OH, SO, WI,
III South - DE, MD, DC, NC, SC, VA, WV, FL, FA, AL, AK, KY, LA, MS, OK,
IV West - NM, CO, WY, MT, AZ, UT, ID, NV, CA, OR, WA, HI, AK.
3/
— Percentage estimates of plants by region were computed from the Membership
Directory and Buyer's Guide 1974-75, Potato Chip Institute International.
These percentages were applied to total plants from the Cens, us of Manufac tures.
II 18
-------
total plants, production, employment and payroll. Product class, five digit,
concentration ratios of percent of plants by largest companies provided in-
sight into the percent of total plants by size group in the four digit, in-
dustry group, data to develop various realistic average size plants and their
ranges of published basic inputs (employees and payroll) and output (pro-
duction). The results of this analysis of size groups as shown on Table II-9
and later in Chapter VII, Impact Analysis, are believed to be realistic in
the sense that (1) many of the plant sizes concur with survey results and
(2) it shows the large number of small plants that rarely, if ever, get docu-
mented in surveys and reports of this nature. Average size characteristics
of fruit and vegetable processing plants from the above described analysis
can be found in Chapter VII, Impact Analysis, Section C, Production Effects.
3. Single Plants vs. Multiplant Firms
All of the 930 canning, freezing and combination firms in the Directory were
classified according to whether they had one or more plants as shown in
Table 11-10.
The importance of single plant firms is obvious in that 78 percent of all
firms -- canners, freezers, or combination plants -- are single plant
fi rms.
The absence of a comprehensive listing of all fruit and vegetable dehydrating
plants necessitates confining the above discussion to fruit and vegetable
canners and freezers only.
4. Number of Plants by Type of Product
An additional segmentation, i.e., type of plant by product is shown in
Table 11-11. Approximately 45 percent of all canners process vegetables only,
5 percent process fruit only, 6 percent process fruit and vegetables only,
and 26 percent process fruit and/or vegetables plus some combination of
drinks, juices, jams, jellies, dressings, Canned specialties, baby food, and
soups. A relatively large percentage of freezers ( 33 percent) process
vegetables only, 23 percent process fruits only, and 30 percent process
specialized products in conjunction with fruits and vegetables.
5. Number of Products by Type of Plant
Most canning, freezing and combination plants are multiproduct plants with
approximately 61 percent of all plants engaging in the processing of two
or more products. The distribution of type of plant by number of products
packed is presented in Table 11-12. This table is primarily concerned with
canning, freezing or combination plants in that comprehensive data have not
been located for fruit and vegetable dehydrating plants.
The advantages to be gained by processing several products include increasing
the length of the processing season due to different harvest dates by type
of crop, avoiding crop failure effects and adverse price fluctuations associ-
ated with a single product and greater utilization of plant capacity.
11-19
-------
Summary of number of plants and ranges of values per plant by size group for annual tons of production, annual value of
production, and employment, 1972 I/
Sma 11
Medium
ro
o
Extra
large
Total
Plants
Tc-is of production
\'-.lue of production
" .lyirant
PI ants
Tons of production
V" ue of production
Employment
Plants
T'-T.S of production
'•;-'" ue of production
E, i'Jioyment
Plants
u~.i of production
ue of production
;,rnloynient
Plants
Tons of production
;alue of production
Employment
Plants
Units
Number
Thousands raw tons
Mil 1 ion dol lars
Employees
Number
Thousands raw tons
Mil 1 ion dollars
Employees
Number
Thousands raw tons
Million dollars
Employees
Number
Thousands raw tons
Million dollars
Employees
Number
Thousands raw tons
Million dollars
Employees
Number
Canned
specialties
.1
.1
1
1.8
1.2
39
11.
7.4
157
25.
17.
ir^z
•jvj
61.
.41.
590
128
- 1.7
- 1.1
- 38
30
- 10.9
- 7.3
- 156
14
0 - 25.9
- 17.3
- 304
14
0 - 61.5
4 - 40.9
- 589
17
6 and over
0 and over
and over
203
Nu
inber of plants and range of production and employment per pi ant
Canned fruits
& vegetables
.1
.1
1
3.2
.8
29
13.
3.1
85
30.
7.1
167
54.
12.
259
384
- 3.1
- .7
- 28
240
- 13.0
- 3.0
- 85
143
1 - 30.6
- 7.0
- 166
96
7 - 54.1
- 12.4
- 258
96
2 and over
5 and over
and over
959
Dehydrated fruits
and veaetables
64
.1 - 1.8
.1 - .3
1 - 13
40
1.9 - 11.4
.4 - 1.8
14 - 58
24
11.5 - 34.7
1.9 - 5.5
59 - 142
16
34.8 - 72.9
5.6 - 11.6
143 - 253
15
73.0 and over
11.7 and over
259 and over
160
Pickles, sauces
and dressings
.1
1
.4
.2
6
2.9
1.0
29
10.
3.5
79
25.
8.4
155
198
- .3
.1
- 5
124
- 2.8
- .9
- 28
74
- 10.6
- 3.4
- 78
50
7 - 25.8
- 8.3
- 154
49
9 and over
and over
and over
495
Frozen fruits
and vegetables
.1
.1
1
3.1
.8
36
16.
3.9
117
44.
10.
238
86.
20.
383
52
- 3.0
- .7
- 35
32
- 16.1
- 3.8
- 116
19
2 - 44.0
- 10.3
- 237
13
1 - 86.1
3 - 20.1
- 382
13
2 and over
2 and over
and over
129
Potato and
corn chics
164
.1 - 5.0
.1 - 3.7
1 - 98
31
5.1 - 9.7
3.8 - 7.2
99 - 170
23
9.8 - 15.0
7.3 - 11.0
171 - 240
15
15.1 - 22.5
11.1 - 16.7
241 - 341
23
22.6 & over
16.8 5 over
342 & over
256
Basic source data was obtained from Census of Manufactures, 1967 (1972 not yet available), for development of concentration ratio functions applied to
1972 Census data for total numbers of plants and their value of production and employment. Adjustments have been made to exclude apple, citrus,
po:..,,c,c ana frozen specialty processors not within the scope of this study.
-------
Table 11-10. Number of fruit and vegetable single and multi-plant firms,
by type of plant!/
Type of
plant
Canning
Freezing
Both
canning
freezing
Other-7
One
Number
555
107
&
58
34
Total 754
Source:
Plant
Percent
by type
83
67
68
71
78
Judge, Edward E. & Sons
Preserving Industries,
Fi rms wi
Few Plants
th:
(2-5)^
Percent
Number by type
96
41
18
10
165
, The Direc
1974-75.
14
26
21
21
17
tory of
Many PI ants (6+)-/
Number
19
11
9
4
43
the Canni
Percent
by type
3
7
11
8
5
ng, Freezi
Total
number
670
159
85
48
930*/
ng and
I/
2/
4/
Excluded from this table are firms which process only apple, citrus, frozen
potato, and dehydrated potato products.
— Firms may have more than one type of plant.
3/
— Firms had plants with processes other than canning and freezing.
This column is the actual number of firms analyzed, however, the column is
not additive due to 32 firms having plants with more than one plant type,
i.e., some combination of canning, freezing, dehydrating, or packaging
plants.
11-21
-------
Table 11-11. Types of fruit and vegetable processing plants by type of product,
1974 !/
Type of
product
Fruit only
Vegetable only
Fruit and
vegetable
Other?-7
Fruit and
other •£/
Vegetable and
other!/
Fruit, vege-
table and
other!/
Total plants
Source: Judge,
Unit
Number
0!
h
Number
01
h
Number
°i
h
Number
01
h
Number
Number
°/
h
Number
°/
la
Number
%
Edward E .
Canner
46
5
443
45
65
6
184
18
44
4
146
15
66
7
994
100
Type of Plant
Freezer
53
23
75
33
32
14
45
19
5
2
13
6
6
3
229
100
and Sons, The Di
Preserving Industries,
1974-75.
Both
6
5
27
24
14
13
26
23
11
10
13
12
14
13
111
100
rectory
o /
Other^/
18
32
14
25
0
-
9
16
4
7
6
11
5
9
56
100
of the Canni
Total plants
123
9
559
40
111
8
264
19
64
5
178
13
91
6
1,390
100
ng, Freezing,
— Excluded from this exhibit are plants which process only apple, citrus,
frozen potato, and dehydrated potato products.
2/
— Includes canned specialties, drinks and juices, jams and jellies, dressings,
sauces, baby foods, and soups.
3/
— Plants having different processes in conjunction with or other than basic
canning and freezing such as dehydrating or packaging.
Il-fZ
-------
Table 11-12. Number of products by type of plant-.
Single Product Plants 2-5 products/plant Over 5 products/plant
Canning
Freezing
Both
Other-7
Total
Source:
Number
407
81
24
36
548
Percent
by type
41
35
22
64
39
Judge, Edward E. & Sons
Number
503
102
62
14
681
, The Di
serving Industries, 1974-75.
Percent
by type
51
45
56
25
49
rectory of
Number
84
46
25
6
161
the Canni
Percent
by type
8
20
22
11
12 1
ng, Freezi
Total
994
229
111
56
,390
ng, and
Percent
by type
100
100
100
100
100
Pre-
- Excluded from this table are plants which process only apple, citrus, frozen
potatoes, and dehydrated potato products.
Plants having different processes in conji
canning and freezing such as dehydrating, brining, or packaging.
- Plants having different processes in conjunction with or other than basic
11-23
-------
6. Age of Plants and Level of Technology
Level of technology is difficult to assess in the fruit and vegetable
industry. Many of the plants are relatively old, but throughout their
useful life new equipment has been added or used to replace that which is old
or technologically obsolete. As a result, most plants in the industry
represent a combination of old and new equipment. Generally, the newer
equipment installed represents a higher level of technology than the old.
However, in the short run, considerably fewer plants than in the past are
expected to update their facilities in the face of obsolescence, inflation,
recession, and added investments required by government regulatory bodies.
In a recent survey by the National Canners Association, the age of plants
was investigated. Approximately 200 plants were surveyed and the approxi-
mate years at the site is given in Table 11-13 along with the years since.
the last expansion (Table 11-13 also contains apples, citrus, potatoes,
seafood and specialty plants). Only 13 percent of the plants were less than 10
years of age and 8 percent from 10-19 years. Seventy-nine percent of the
plants were located at the same site for more than 20 years. Sixty-two
percent of the plants have undergone a major expansion program in the last
five years. However, another 19 percent had undergone expansion since
1960. Nineteen percent had not expanded since 1959.
A large majority of the plants surveyed in the New England, North Central
and Mountain Regions were over 40 years old. By commodity, the oldest plants
were spread throughout fruit and vegetable canning plants. By comparison,
the seafood and specialty plants were relatively newer.
7. Plant Efficiency
Plant efficiency is a broad concept which includes factors such as age,
level of technology, utilization, capacity and other factors. It is
obviously not possible to discuss or even ascertain many of these factors
on a firm or plant-by-plant basis. For this v'eason, one-major criterion of
plant efficiency—utilization of capacity—is extended at this time.
•Capacity is defined as the output which a canning or freezing plant is
capable of producing at a given time with a specified machinery and equip-
ment combination. Normal capacity is the output per unit of time which
is realized at other than the peak of the harvest season. Maximum capacity
is the greatest output obtainable per unit of time with existing plants
and equipment. Almost all processors utilize maximum capacity at the harvest
season peak. Industry data indicates that plants will run near maximum
capacity from 15 percent to 38 percent of the days of plant operation each
season. Excess capacity in the fruit and vegetable industry equals maximum
capacity minus volume processed through a plant during the harvest season
peak.
Utilization of capacity is the degree to which normal capacity is attained
in the output of a plant during a given period.
Utilization of capacity is an important factor in the financial success
of a given plant and utilization is affected by a number of supply, operating,
and sales factors. These factors are stnmarized in Table 11-14.
-------
Table 11-13. Percent of Canning Plants' in Various Age Groupings by Location and Commodity
and Years Since Last Major Expansion
i
ro
en
Years at site
0 - 9
10 - 19
20 - 39
40 - 59
60 +
Total
Year of
expansion
1965 - 69
1960 - 64
50 - 59
Before 1959
Total
Years at site
0-9
10 - 19
20 - 39
40 - 59
60 +
Total
Year of
expansion
!S'o5 - 69
I960 - 64
1950 - 59
Before 1950
Total
New-
England
S
8
8
53
23
100
46
8
8
sa
100
Iviicdle
Atlantic
9
9
34
34
14
100
•
55
25
8
12,
100
Fruit
Q
8
40
34
9
100
53
23
14
10
ICO
South
North
Atlantic Central
o
12
49
21
9
100
64
12
18
6
100
9
5
16
50
20
100
62
22
11
5
100
Tomato
9
0
30
45
•16
100
61
17
15
7
no
Location
South
Central Mountain
16 0
5 0
53 27
21 46
5 27
100 100
68 50
5 20
16 10
11 20
100 100
Type
Vegetable
10
7
32
40
1 1
100
64
22
7
7
:oo
North-
west
17
11
49
18
5
100
63
21
9
7
100
Seafood
17
15
26
23
19
100
63
7
15
15
100
Sourh-
Alaska west
30
10
25
10
25
100
85
5
10
0
100
14
o
34
37
6
100
60
20
12
8
100
Specialty
14
13
. 30
30
13
100
67
16
10
7
IOC
Total
13
8
33
33
13
100
62
19
11
8
100
Source: National Canners Association
-------
Table 11-14. Summary of factors affecting utilization of capacity
within fruit and vegetable processing plants
Factor
Comments
1. Length of Harvest Season by
Product
2. Crop production
3. Availability of packing
materials
4. Product carryover
5. Raw Product Quality/Recovery
Percentage
6. Level of Maturity of Raw
Product
7. Number of Products & Schedule
8. Variations in container sizes
9. Warehouse and Inventory
Conditions
Year to year variation exists
Varies from year to year, but gen-
erally peaks within season and
is dependent on weather and crop
maturity.
Although most processors plan ahead
to have materials on hand, shortages
of containers, etc., can impede
utilization of capacity.
Affects utilization from year to
year.
Quality affects throughput.
Can vary within a season and affects
quality
Multiproduct plants may have over-
lapping a; d competing seasons. Capa-
city i^ affected by definition.
Affects raw product volume capacity
and is generally dictated by demand.
Plant schedules may vary with
associated warehouse space and atten-
dant inventory conditions and rail
car availability.
11-26
-------
An indication of plant capacity utilization can be ascertained from utili-
zation of product-line capacity and was available in three sources. Firsts
a recent report by National Canners Association !/ shows that processors of
28 major fruit and vegetable products use on the average between 70 and 90
percent of product-line capacity. Secondly, a recent survey from six
processor associations which was summarized by DPRA 2/shows that canners,
freezers, and potato chip processors utilized on the average 72 percent
of product-line capacity on 56 basic products. Plants processing under
2,000 tons of raw product used an average of 65 percent of processing
capacity and larger plants used 72 percent.
A study by Pearson — in the Southern Region found that canners utilized
57 percent of vegetable processing capacity as compared to 74 percent by
freezers. As a general rule, larger plants utilized a greater portion of
capacity.
There is substantial year-to-year and seasonal variation in the production
of fruits and vegetables. Thus, 10-30 percent capacity, above normal,
is vital to enable the industry to process peak season and larger-than-
normal year production.
In summary, it is believed that very little excess capacity exists in both
the canning and freezing industries. In general, utilization of capacity
is higher in larger plants and in intensive commercial production areas.
II
2/
Impact of Environmental Controls on the Fruit and Vegetable Processing
Industry, National Canners Association, 1974.
Development Planning and Research Associates, Manhattan, Kansas, received
and summarized survey responses from members of the National Canners
Association, American Frozen Food Institute, Potato Chip Institute •
International, Pickle Packers International, Incorporated, National
Preservers Association, Association of Dressings and Sauces and the
Vinegar Institute. The surveys were in response to the expansion and
updating of the industry data base for this report. The responses were
based on the 1973 crop year.
-' Pearson, James L., Utilization of the South's Vegetable Processing
Capacity, Department of Agr. Econ., Fla. Agr. Exp. Sta. and Econ.
Res. Sv., USDA, Agr. Econ. Res. Rpt. EC 68-5, January, 1968.
11-27
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D_. Importance of Spedfic Products Relative to the Industry
The preceding section has discussed plant characteristics. The objective
of this section is to relate the importance of the products to be analyzed
in.detail in this report to the fruit and vegetable canning, freezing and
dehydrating industries.
I- Specific Vegetable Products Relative to the Canned Vegetable Industry
The relative importance of any specific product can hest.be portrayed by
comparing its volume of annual pack by specific product relative to the
appropriate industry totals. This information is presented below for
selected products considered in this report.
Product
1. Tomatoes
2. Corn
3. Green £ wax beans
4. Green peas
5. Carrots
6. Peas & carrots
7. Sauerkraut J_/
8. Mushrooms!/
9. Picklesi/
10. Dry beans!/
Total
Vol ume
___ __
TOOO cases "
24/303 cans)
101,553
55,228
55,002
29,558
5.
2.
529
186
10,008
3,637
67,066
% of total
canned
vecietables, 1973
22
12
12
6
1
1
2
1
15
15
_
397,767
87
Source: Division of Statistics National Canners Association
Judge, Edward E. and Sons, Th_e__Alj]ian^c_pJ_the__C^^
and Preserving Industries, 1974. Census of Manufactures, 1972.
- 1972 pack since 1973 is unavailable
- Converted from 598,800 tons for processing in 1973 times 112 24/303
cases per ton.
V
—' Census of Manufactures data for 1972 for various size cases.
11-28
-------
Annual volume pack for the ten canned vegetable products considered in
detail in this report represents approximately 87 percent of the industry
total. The specified products and combinations of vegetable products con-
sidered in detail in this report are relatively major components of the
vegetable canning industry.
2. Specific Vegetable J3 rod u_cts_Relative to the Vegetable Freezing Industry
The volume of pack for the eight frozen vegetables considered in detail in
this report is shown below. Since frozen potatoes amount to 49 percent
of total and are not part of this report, the products considered in
detail herein account for 65 percent of the total frozen vegetable pack
excluding potatoes. Thus, the eight specified products shown below are
a major portion of the frozen vegetable segment.
Product
Volume
ack _
bs.
% of total
frozen
vegetable pack
1. Corn
2. Green peas
3. Green & wax beans
4. Carrots
5. Broccoli
6. Cauliflower
7. Lima beans
8. Spinach
TOTAL
294,223
387,749
290,861
231,688
213,165
96,098
149,689
1,822,524
10
14
10
8
8
3
5
_6
65
Source: American Frozen Food Institute, 1973.
3. Specific Canned Fruit Products Relative to the Canned Fruit Industry
The three canned fruit products to be analyzed in detail and shown below
represent 10 percent of total canned fruit and fruit juices considered
in this report. Forty-three percent of the canned fruit and fruit juice
pack are products not considered in this report (citrus, apples). Canned
peaches and apricots (29 percent of products to be analyzed in this report)
were initially specified for analysis in detail. However, preliminary analysis
11-29
-------
showed they were processed with tomatoes, in large plants, in the Southwest
and discharging primarily to municipal sewers. As a result, peaches and
apricots were omitted as a separate category for detailed analysis.
Product
Fruits:
1. Cherries, RSP and sweet
2. Plums, purple
3. Pears
TOTAL ALL FRUITS
Volume
pack_
[000 cases"!
1,082
1,261
9,813
78,617
% of total
canned fruits
and juices, 1973
1
1
10
79
__
total fruit jiuce
TOTAL ALL FRUIT AND
FRUIT JUICES
20,590
99,207
21
100
4. Specific Fruit Products Relative to Frozen FruiL Industry
Cherries to be analyzed in detail, constitute 21 percent of frozen fruits
packed and considered in this report. Apples, including sauce., which are
not part of this report, constituted 21 percent of total frozen fruit pack.
Since citrus juice products comprise 99 percent of the total frozen fruit
juice pack, no frozen juice products were analyzed in detail.
5_. Specific Products Relatiye_to the Dehydrating_Ijidu_sjtry
The 1972 Census data reveals that the dehydrated food industry shipped a
total of 1.7 billion pounds of fruit and vegetables of which 1.1 billion
are relevant to this report, i.e., excluding apples and potatoes. This
segment of the industry will be considered in the general analysis.
Potato chippers processed 3.2 billion pounds of potatoes in 1967 and
shipped 814 million pounds of finished potato chips. Corn chips, curls
and related products shipped were 287 million pounds. In ]973: potato chippers
utilized 3.4 billion pounds uf Irish potatoes and shipped about, 850 million
pounds. Since potato chip processors comprise about 75 percent of the total
volume packed of chips, aiolQ and related products, they will be analyzed in
detail. Corn chips, curls and related products will be in gt :-:,'al analysis.
11-30
-------
£. Significant Impacts on the Industry
Because of the unique structure and competitiveness of the fruit and
vegetable processing industry, pollution abatement standards when imposed
on plants discharging to surface waters and municipal sewers can have
serious consequences on the industry itself. The magnitude of this
impact will, of course, depend on the level of of investment required to
meet the specific standards. The smaller third—and to some extent the
middle third—of the plants discharging direct and to municipalities are
expected to be seriously impacted. They may not be able to recover the
cost of installing and operating abatement facilities or paying user
charges unless they have access to lower cost facilities, expand or merge.
The specific plant impacts will, of course, depend on many factors such"
as capital availability, size of plant, profitability of the plant, location
and availability of low cost treatment strategies.
It is recognized that the impact of substantially increased user charges,
now and in the future, to plants hooked to or planning to hook-up to
municipal sewers is extremely critical to the industry, local business
communities and to consumers. However, the scope arid the economic impacts
in this report pertain to those plants directly discharging to navigable
surface waters which are estimated to be 324 plants (15%1/ of 2,159 plants).
1. Capacity of Low Cost Producers Relative to High Cost. Producers^
The capacity of low cost producers hooked to municipal sewers and/or
directly discharging relative to high cost producers in the same position
is one of the more important factors in considering the impact of pollution
abatement costs imposed upon the industry. In the canning industry, the
largest third of the plants pack approximately 80 percent of the total
volume. The riddle-third of the plants pack abo»t 15 percent, and the
smallest-thi :an only 5 percent of the toi ' pack. Due to economies of
scale, the 1 • plants are already expected to have a definite cost
advantage. -position of high pollution abatement costs on the smallest-
third of th: ts discharging direct or to municipalities, and to a large
extent the n, e-third, are exoected to result in further diseconomies.
of these lov, lume plants. If these small plants are forced to shut down
(unless lov/ cost abatement procedures can be utilized), the low cost-high
volume plants in the industry will most likely" offset, possible losses
in capacity through expansion (acquisition, plant expansion) and new con-
struction, assuming firms can acquire the necessary capital.
Location of plants with excess capacity is another aspect which must be
considered, and this factor will require further analysis. For many
products, regional distributions of alternative-sized plants are not uniform.
Honce, significant regional dislocations in processing (and at the grower
level) could be expected in that there are counties throughout the U.S.
that have a significant percentage of their labor force employed in small
direct or municipal discharging plants -- which are expected to be severely
impacted.
— Environmental Protection Agency, Guidelines Division, and developed by
SCS Engineers.
11-31
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2 . Fa c 1 err Dislocation Within the Industry
Differential impacts from pollution abatement controls are expected within
the fruit and vegetable processing industry, both in terms of type of firm
and in regional location of affected plants. The impacts expected and
reasons for associated dislocations are as follows:
a . Types of Firms and Location,
As explained earlier, the fruit and vegetable processing industry is
comprised of many firms (inulti /single plant) differing in plant types
(canning, freezing), products processed (multi/single commodity), size
(rate per hour), length of season (long/short), capacity and utilization
of capacity, level of technology (new/old) and other factors. Many of
these factors were considered in the preliminary analyses and one of the
most critical measures in terms of assessing a plant's ability to with-
stand the impact of internalized pollution abatement costs is its overall
through-put size.
- _EJ ™$. ~ Within the fruit and vegetable industry, margingal firms
are typically the "small" and single plant firms. This is particularly
true in terms of small firm's (direct or municipal dischargers) ability
to financially withstand projected high capital investment requirements
of pollution abatement measures. Such plants often simply lack capacity
to pay-out such investments (at the levels given). Many single plant
firms also lack the capital-acquiring ability of larger multiplant firms.
Within this framework, marginal firms faced with the decision to either
curtail employment or shutdown would most likely shut down. However,
pollution abatement investment costs can be an incentive to expand produc-
tion, not lower it, in order to lower per unit costs for those plants
having or able to ii.jtall self contained disposal fac i i ivies.
Other plant closures of almost any size are expected to result where
obsolescence together with rising operational and required regulatory
capital needs cause total costs of operation to be so high, continued
operation is economically unfeasible. For single plant firm closures,
uneinployiTiGnt and loss of market to farmers and local businessmen associated
with the closing plant are expecled to result. For some closed plants
that, belong to inulti pi ant firms, various proportions of production and
employees will shift to other nearby plants belonging to the firm; some
unemployment, due to immobility, with a corresponding loss of payroll and
local business will re-suit. Other closed plants that belong to multiplant
firms may not be ab!e to shift pro tuction and are expected to have the
same effects as the i ;ngle ["ant firm closures.
As previously mentioi • H, downward trends in the number of earning, freezing
and chipping plants •• . occurring. Pollution abatement controls are
expected to acrelrtf >" this iownward trend in the number of firms in the
industrv.
-------
Locational Impacts - Only general patterns of location of plants by size
category ""have been" assessed in this phase of the study, but from this
alone it is believed that regional differences in impact will occur
following standard adoption of pollution abatement controls. It is recog-
nized that differences from state to state in State Water Quality Standards
and the possibility of non-uniformity of enforcement within and between
states is another important factor in the impact on fruit and vegetable
processing plants. Even though this problem is recognized, the impact
of regulatory variability is not included in this report.
Another study completed by DPRA- has shown that on the basis of average
employment estimates and probable closures, the county unemployment gener-
ated could be as great as 4 percent of total county employment in selected
counties.
3. Reasons for Dislocations
Reasons for the above type of firm and location-dependent expected dislo-
cations within the industry have been generally described. A summary in
terms of profitability and capital attainment is appropriate.
Profitability - Profitability of firms, but particularly the smaller, in-
efficient and undercapitalized firms, will be affected by pollution abate-
ment measures. While average incremental costs for pollution abatement
may eventually be passed through to consumers, the smaller firms are
expected to have much higher than average per unit costs of abatement
and to drop out during the period necessary to achieve any consumer price
adjustments.
Economies of scale in pollution control are apparent, and this is to the
relative disadvantage of smaller firms. As previously suggested, many
of the plants discharging direct or to municipalities might be forced
out of the industry. This would have a limited desirable impact on the
remaining firms in that pollution control costs could be spread over a
larger volume. Thus, the level of profitability of the surviving plants
might be affected less on the average.
In-plant modifications and operational changes which will reduce effluent
loads may or may not improve the profitability of those plants which can
take advantage of them. In-plant modification costs and savings must be
assessed and justified by individual plants.
~ Economic Impacts and Adjustments to Pollution Abatement Impacts,
Economic Development Administration.
11-33
-------
Cap i ta 1 A va i 1 a h_ i 1i ty - Capital within the fruit and vegetable industry
Is obtained primarily from comnerci:;1 sources outside the industry and
from the investment of profits. Additional capital requirements for
financing pollution abatement measures will also principally be sought from
In this case, ability to obtain additional capital is expected to be
determined by an individual firm's projections of net returns with an
ex'pn'ided investment program. Consequently, capital availability is expected
to Le directly related to profitability—and the smaller, inefficient plants
will have difficulty raising the needed long and short term capital to
stay in business. The large sums of short term working capital needed by
most fruit and vegetable processors tends to limit their ability to obtain
long-term capital for changes in facilities required by FEA, FDA, OSHA and
F.PA and plant/firm expansion. In this sense, inability to obtain capital
will contribute to the shutting down of marginal processing plants.
Firms which are able to pass through incremental cost of pollution abate-
ment costs and maintain positive profitability will be able to acquire
capital for increasing capacity—plant expansion, acquisition, etc. Cur-
rently, pass th'-oi.'grs of rapidly increasing and larger-than-normal propor-
tions of costs an- difficult to expedite. Costs of food are rising rapidly
and are disproportionately largo due to a nearly simultaneous inflation
of operational costs (labor, materials, raw product) with new investment
rT
-------
III. FINANCIAL PROFILE
To ascertain the economic impact of pollution abatement costs on direct
discharging plants in alternative product segments of the fruit and vegetable
processing industries, it is critical to assess probable differential im-
pacts among representative plants within the industry. All firms are not
expected to be affected equally in terms of per unit cost of abatement.
Economies of scale will exist in controlling pollutants associated with
processing.
A microeconomic evaluation of costs and returns for representative plants
within the fruit and vegetable processing industry for specified product
segments is needed to assess probable economic impacts of effluent guide-
lines on direct discharging plants within the industry. From this base of
information, meaningful overall impacts on the industry can be projected.
The model plant data and financial profile have been developed largely
from a survey of the canning and freezing plants. The survey was con-
ducted for this study by trade associations in this industry. Approxi-
mately one-third of the firms responded to the questions asked. These
data have been compared and confirmed by other industry studies and
other secondary data which are available. The model plants are based on
these data and it is believed that the model plants chosen do represent
conditions closely related to plants operating within the industry during
the time frame chosen.
A. Model Plants by Segment
Table III-l shows the 52 model plants selected to represent the fruit
and vegetable canning and freezing industry as included in this study.
These plants were chosen as a result of the analysis of the segments as
described in Chapter II, Industry Segments, and have been verified by data
returned directly from industry in response to the industry-wide.survey.
From the survey data three types of Plants have been snecified for
analysis: 1) single commodity piants--those plants orocessina a sinqle
commodity exclusively either on a year-round or seasonal basis; 2) the
, multi commodity plants — those plants processing two or more commodities
on a year-round or seasonal basis; and 3) specialty processing plants --
in this case, potato chip processors who do not oualify either as a canner
or freezer but are shown in the data as "dehydrator" type processor.
A second key variable considered was the size of operation and the spread
of these model plants from extra small to extra large shown in Table III-l.
In each case where the size has been specified, it has been chosen as being
representative of direct discharging plants actually in operation in the
industry and is further divided between canning and freezing plants.
III-l
-------
Table III-1. Summary cf model plant characteristics: commodities and sizes
Extra
STQl 1
Sir,:!? Cc-Todity Plants
Ccrr
•^C'TOCT.S 200
1,500
2,500
Fi.-ides
Sa'.c Taut
Tomatoes 1,500
. '. -.j—odity Plants
Corn, Peas 3,000
-.„'.,,, r-eas, Green Beans, Carrots
Srccccli, Cauliflower, Lima Beans, Spinach
T.-p.to, Dry Beans 2,000
Cherry, Green Beans, Pears, Plums
Cherry, Strav.'berry, Caneberry
?!
-------
The approach used in this analysis is not based on the synthesis of hypo-
thetical costs and returns data, but on performance of representative plants
operating in the field which have reported actual data on sales, costs,
profitability and investments. It should be emphasized, however, that
these model plants as used in this analysis do not represent any specific
plant, but rather are representative of the group of plants taken as a
whole.
1. Seasonality
As previously mentioned, some plants operate on a year-round basis and
operations of some plants are highly seasonal in nature. This variation
comes about by virtue of the commodities that ore processed and further
by the complexity of the plants; that is, whether or not there is more •
than one commodity processed. In Tables III-2 and III-3, the nature of this
seasonality is shown. For a particular plant with a particular commodity
or mixture of commodities, the percent of the total annual pack processed
in each month in the year is shown. As can be seen, this varies from single
commodity corn plants where the season is essentially a two-month operation
to those plants processing mushrooms, potato chips and dry beans which are
basically year-round operations. The preponderance of the data presented
in this chapter will represent conditions as they existed in 1973. However,
where there were highly unusual conditions in 1973, adjustments have been
made to reflect a more normal condition and variations from 1973 will be
noted.
2. Style of Pack
In analyzing these model plants, it must be recognized that there is a wide
variation in style of product among specific commodities in the fruit and
vegetable processing industry. In some cases, style of product was clearly
identified in data submitted and in other cases, the commodity itself VMS
shown without regard to style. Therefore, t>;ese model plants represent
averages or ranges and include information from plants with a broad spectrum
of styles. Tomato plants-, for example, are most representative of this
type of variation. For tomato plants style varies from peeled whole tomatoes
to various types of pastes, sauces, catsup and juices. Likewise, the pickle
styles are also broadly-based including both the fresh pack and the brined
pickles. It is known, for example, that in both pickle and tomato plants
there are specialty companies that carve out particular segments in the
market and process unique or premium quality products. Usually these pro-
ducts command premium prices to cover these unique styles and qualities
or have specialized markets or other unusual market features which allow
them to operate at least as well as the plants processing the bulk tonnages
of particular commodities.
B. Model Plant Configuration
In the following paragraphs, the financial profiles of the model plants are
shown. It is important to note that all of the cost and sales data presented
III-3
-------
Table III- 2. Monthly volume of production—single commodity plants and specialty plants
Monthly Volume— Percent of Annual Production
Tyoe of plant Commodity
Single Commodity Plants
Corn
Mushrooms
Pickles
Sauerkraut
Tomatoes
Jan. Feb. March April May June July Aug.
45
n n 5 n n e 5 5
44 3 3 3 8 20 30
666555 10
30
Sept.
50
6
10
20
55
Oct. Nov. Dec.
5
6 11 11
744
25 6 6
15
Specialty Plants
Potato Chips 8
8 10
-------
Table III- 3. Monthly volume of production--™! ti-correrodity plants
Monthly Volume—Percent of
Plant combination
Broccoli-Cauliflo'ver-
Spinuch-Lirra Beans
Cherry- Canberry-Strawbcrrv
Cherries-Green Beans-Pears-
Pi u-s
Corn-Peas
Corn-Peas-Green Beans-
C-irrols (Canned)
Ccrn-Peas-Green Eeans-
Carrots (Frozen)
Dry Beans-Dressings and
Sauces
Tomatoes- Dry Beans
Cornodity Jan Feb March Aon'1
Broccoli 5 5 15 5
CauliHower 2 2
Snn-.ach 35 55
Lima Eoans
Plant Total 2 1 13 15
Cheery
Careberry
Strawberry
Plant' Total
Cherries
Crc,rn Beans
Pears
PllP.S
Plant Total
Corn
Peas
Plant Total
Corn
Peas
Gresn Beans
Carrots
Plant Total
Corn
Peas
Green Beans
Carrots
Dry Ceans 10 10 10 10
Dressincs and 8
Sa. ess 99 3
Pickles 44 33
Tomatoes
Plan Total 55 44
To~£toes
Cry Beans 10 10 10 10
Plant Total 1111
May June
15 15
1 10
10
6.5 6
15
10
70
35
15
i
30
6
30
3
30
10 10
8 8
3 8
4 5
10 10
1 ' 1
July
5
10
4
75
30
30
46
75
25
12.5
60
12
60
25
3
10
60
25
5
5
8
20
9
5
.5
Annual Production
Auq
5
15
25
11
10
55
17
10
50
35
35.5
40
1U
34
40
10
50
5
35
40
10
50
5
5
8
30
30
21
30
.5
27.5
Sent
5
5
60
17.5
5
1
25
40
90
37.5
50
40
50
2b
15
33
50
25
15
5
8
10
55
2-2
55
5
50
Oct Nov
5 10
20 25
15
10 9
25
10
13.5
10
8
10
50 15
n 2
10
50 15
5 10
8 9
7 4
15
1C 5
15
5 10
14 1
Dec
10
10
5
10
1
10
10
9
4
5
10
1
-------
take into account the utilization factor common in the industry in 1973.
The sales figures for example are representative of these specific plants
as they operated in 1973 at the prices which were prevalent in 1973.
Therefore, a utilization rate comparable to this period is assumed and no
specific utilization rate is calculated. In all cases, the plant sizing
has been done on the basis of total annual tons of raw material processed.
From the industry survey it was evident that 1973 was an unusual year for
processors of fruits and vegetables. There were a few respondents (less
than 5/') that suffered losses or reported conditions that adversely
affected their results. However, the preponderance of respondents (about
50%) reported highest profits in recent years and generally good results.
The year 1973 was one of price freezes, but for many processors this freeze
occurred after the pack was established and after many price contracts had
u^en negotiated. The fact that there was good production in I0"'?, and that
the pack sold out with little carryover was responsible for an improvement
in profits in 1973.
A study--- of 31 fruit and vegetable canning firms shows an average of 5.5t
pre-tax return on sales for 1973 compared to a 4.4% average pre-tax return
on sales over the 13-year period, 1961-1973 for essentially the sai::e linns.
In the impact analysis, which follows in this report, analyses will be made
of impacts ot effluent controls based on industry returns in 1973 and over
the 1961-73 period.
Tables III-4, III-5 and III-6 show the 1973 cost and profitability status
of these 52 model plants. All of these costs are stated on an annual basis
which eliminates the seasonal factors, month to month variations and plant
utilization variance:. Plant tvpes are shown by symbols, C, F and 0 re-
ferring to canning, freezinq and dehydrating and nlanl sizes am o,n^n !,y
self explanatory symbols ranging from extra small (XS) to extra largo
(XL).
]_1__SalJe_s_
Sal PS values shown in these fables are primarily influenced by the size of
the plant. However, there are variations in sales which are not accounted
for strictly by size variations. It appeals in some cases that the style
of pack of particular plan's increased the ratio of dollars worln of sale
to tons of product processed. This is particularly true in trie
tomato plants. The very l;r,p tomato plants, which are presumed
a large percentage of pastes, show a very low ratio of dollars o
per ton of product. Neverin .less, these 'ales figures are repro-
of plants of this size and correspond with the entire financial
for these plants. Sales da... are based on F.O.B. prices at the plant.
--'' "Financial Ratios Cannes :Vuits and Vegetables," released 3-20-75 to
National Canners Assor : ' ui !>- Touch, , Ross and Company, One Maritime
P!-.., ,, San From i ,^o, f on < 941 1 .
•1-6
-------
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-------
III-5. Estimated sales, va.-ic.ble and f':>ed costs and relationships for industry segments based on rrodel plants -
~ultiple coraodity plants --I973
Cc-roditv
0 o '" r - 9 '"* a s
'~ v ~ '^ - r " P S
• ,- - r _ r -j p c;
-r-cc.5
Co ---Pe,,s-3. Beans-Carrots
C'j- --•'eas-G. Bears-Carrots
3" *"-?•' ~:' ~G . B "-ins-Carrots
•---"- ' . " -'S-OC-TOtS
- -'. -;. 3-._ is-Carrots
5 . •-'-- i-::-j. C ear. s- Carrots
CC.T,-^ eas-G. Baans-Carrocs
3c-p-"3a'-3. Beans -Carrots
^ i . ' ". .- - i
E -occ3 1 i-3ijl if .-L. Beans, -Spin.
" i ". j" if .-L. Beans, -Spin.
T -. ,es-D-y Beans
7c-..tu:s-0ry Beans
- ----- s-3r j 3°:ns
' -~ -y r -ens
Tc- :;:c-S-3'-y leans
C'-e-ry-G. Bean-Pear-Plum
f_r-,-ry-G. Cean-Fear-PluTi
3'-erry-3. Bean-Pear-Plum
C«.'-y-stra.,tc'-y
3- :, •-, -'_-?:;C'-^y
C-"--y-:a-:ce>-y
"-.c-'"e-Tc-3tces-D. Bean,
3-eos- r\5 S Sajces
P" :• "-;-7c~ictjes-0. Bean,
: ^?.-!:r" Dpan
'- .". ".O. :,san.
-'- -: ': - Si-ces
~,"~!~. = i Products
c T.ed PrcJuCtS
' ' "•"• J 'CtS
Tvoe
r
c
C
o
C
c
F
F
p
F
F
F
F
F
C
C
c
r
c
c
c -
c
Si 2=
tons
S
M
L
V 1
At
S
M
L
XS
S
S
M
L
S
XS
S
M
;_
A 1_
; ar.njc.1
oroccssed
3, COO
12.030
37,000
i 0 o i"i ' , n
i £. J , UU"J
13,000
25,030
50,030
^ 0 'kj U
ic. 'coo
12,030
25,000
50 ,000
8,030
25,000
10,000
2,000
7,030
20,000
70,330
175, COO
5,000
10,003
200,000
C~r\ n
2,000
5,300
2,000
6 ,000
18,000
O •-" ) -,
fl ^ ^ '
4,004
155
1,134
2,253
253
531
"17
9 3 5
1,931
1,131
3,525
^ y -_ J ^
211
791
2,735
6,170
10,058
"28
1.C55
2,110
'36
1,333
2 .6-"0
591
2,060
5,131
20,460
?6
305
7 c i
Va r i a
rOC'JCt
P p Y- f :^""i •*"
I L : U — ' 1 L.
18
18
18
1 Q
*O
19
19
19
25.2
26.2
2o
25
25
23
28
23
35
35.7
35 .5
o o . 0
37.6
25
26
26
ZL'"1 ^
40 '. 3
r n -5
35
35
35
35
1 7
17
^ Pi
Die Costs
Ctner
SO 30
197
874
2r ~\ i
, J JH
3 7 "0
o * / -^ J
93C
2,459
4.9-0
'313
/ _ L
i j v 0 w
1,4/2
2,941
1,042
3,113
4 , 2-2
243
805
2,285
6.059
1 0,00 3
878
1,755
3,510
Or p
952
2, -"-12
496
1,560
5,154
17,515
187
720
7 "0
Direc
P=~r,=
r \_ i t_ —
31
32
32
7?
Oi-
41
41
41
36
37
37
37
37
25
25
21
36
35
36
35
3'-
13
43
43
33
35
35
24
26
29
30
37
40
3?
r-,;
t I r d •:
ri •*• C ^ ^t O
• 1 0 v*-- *•> "J
210
993
237
in 3-0
j. u , ^ i • J
579
1,640
3,476
1 i 0
367
536
833
1,697
1,354
^ " c/i
7^929
131
3/1 O *J
*T^l J
4 1,231
0 3,252
6 5,337
379
803
1,610
3 201
7 513
1 1,299
5 406
4 1,278
5 4,217
214,413
156
486
511
xed Cc
rsct
£ pv, ^
'
33
35
J i1
"3Q
0 .7
23
27
29'
19
19
19
21
22
33.5
11
40
19.7
19.7
19.6
20.0
15.6
19
20
20
19
19
19.5
20.5
22.0
24.2
24.7
31
27
25
sts
Intsr
y,",', "1 C
V w ^ O I
29
85
150
f r. r\
S" ijsj
60
180
270
45
72
130
140
270
91
100
300
13
14
118
363
574
45
70
135
13
25
r'l
108
252
288
510
17
62
74
est
C i W •
5
3
1.4
Id
. -r
2.5
3
2.1
5.0
5.0
5.0
3.5
3.4
2.2
i
1.4
2.0
2.0
1.9
2.0
o r-
£. , \J
2,2
1.7
1.6
1.2
1.0
0. 7
6.0
4.3
1.6
1.0
3.0
3.5
i.O
Deoreci
Sn\l
y >^ w U
29
95
180
1^1
4 JU
70
200
300
46
72
150
160
300
91
155
215
13
44
113
353
574
50
75
150
13
25
i?
108
252
288
540
17
62
74
atic
P?v-
r c. w
5
3
1.6
i f,
I.O
3
3.4
2.4
5.0
5.0
5
4
4
2.2
1
1.6
2.0
2.0
1.9
2.0
2.0
2.4
1.9
2
1.2
1.0
n ->
6.0
4.3
1.6
1.0
3.0
3.5
4.0
Total
n costs
Sf p 'i p - r* f
•^ \j •J r d -- •
578 9 .6
2,520 9 .7
7,231 9 .7
?s on* qi c
t-J^C./T' _7j,.V
2,252 93.5
5,523 93.1
11,
-------
Table III-6. Estimated sales, variable and fixed costs and relationships for industry segments based on model plants
specialties commodity plants - 1973
Ccrrccity
Tyoe
Siz>,
tons
5 annual
orocessed
Sal:
Variable Costs
2S Raw Prccuct
$OCO Percent
Potato Chips
Potato Chips
"otatc Chips
Potato Chips
Potato Chips
D
D
D
D
D
XS
S
M
M
L
1
2
8
13
• 30
,000
,500
,000
,000
,000
620
1,450
3,760
5,330
11,250
100
100
100
100
100
Ctrer
$000 Percent SCOO
350
800
1,840
2,535
4,350
56
55
49
48
39
96
230
704
1,062
2,950
Direct
Percent
15
16
18.4
20.0
26.0
Fixed Costs
Inch !
^ect
$000 Perc.
104
250
763
1,150
3,196
IS
18
20
22
23
Interest
$000
20
50
141
186
235
Perc.
3
3
4
3
2
.0
.0
.0
.0
.0
Total
Deoreciation costs
SCOO
25
62
177
232
294
Perc.
4.0
4.0
5.0
4.1
3.0
. SCCO Pcirc
595 95.
1,392 96.
3,625 95.
5,165 95.
11,025 98.
-------
2. Variable Costs
The variable costs, which vary with the amount of product going through
the plant, were divided into two groups: raw product, which is designated
as the cost of the raw product delivered to the plant for processing, and
other direct costs. In other direct costs, the balance of the direct costs
have been lumped together. These would include labor, cans and packaging
materials, other materials and supplies, arid all of the direct charges not
associated with overhead costs.
The raw product cost as a percentage of sales costs showed wide variation
by commodity. The cabbage and sauerkraut had the lowest ratio of 17-19
percent; whereas, cherries processed in a freezing plant had a very high
percentage as related to the raw material cost versus total sales. Raw
cherries averaged 59 to 60 percent of total sales price. In general, most
of the processing plants seemed to indicate that raw product costs were in
the 20-30 percent range as a factor of total sales of the plant. Similar
variations were shown in the other direct costs.
Part of the variation in raw product and other direct costs shown in Table
III-4 undoubtedly result from the variation in accounting procedures among
firms responding to the industry survey. For example, in some instances,
raw product costs shown may include harvesting and processing costs when
these functions are performed by the canner, whereas other raw product costs
may represent f.o.b. plant prices. Although such situations do exist, the
net effect on total costs should be comparable and the variations within the
cost structure as shown are believed to reflect standard cost practices in
the industries analyzed.
From data submitted by processors, fixed costs were most difficult to derive
in terms of normal distributions and average percentages. There are wide
variations in the way that overhead expenses and administrative expenses
and other similar items are allocated from plant to plant and from product
to product. Nevertheless, on the basis of this study where we felt we had
reliable data on the profitability of various size plants and on the total
sales of the plants involved, the wide variation in indirect costs was not
believed to be detrimental to the validity of this study. In all data sub-
mitted, interest costs seem to bear a close relationship to depreciation
and thus in these model plants interest and depreciation are very similar
figures. Depreciation, however, varied widely from plant to plant and from
commodity to commodity without o'nowing any consistent patterns for size or
for commodity . Dcprecia4 ion as shown in the table as a percent of sales
which is not the way that depreciation is measured normally. Depreciation
is normally a factor of pi ant investment and in the data submitted varied
from 6 to 14 percent of total investment. Therefore, for purposes of this
study, depreciations in this ranne based on total investment were used and
wide variation when shown to relation to sales was the result,
111-10
-------
4_. Total Costs
Total costs showed variation by commodity and by size of plant. In all
cases, total costs were less than 100 percent of sales. Although some
data were submitted to indicate that a small percentage of plants operated
at varying degrees of losses, i.e., cost exceeded 100 percent for the year
1973 when averaged over plants of similar size, these losses were more
than offset by plants showing considerably lower cost-sales ratios. No general
statements can be made as to the cost relationship of single commodity
plants versus multi-commodity plants as each group has both low and high
cost plants represented in the data.
5. Investment
Tables III-7, III-8 and III-9 show for the model plants an analysis of the
components of total investment of the model plants. Land is characteristically
a small part of the total fixed investment, although there is one notable ex-
ception—the small pickle plant. It is believed the reason for this higher-
than-usual land figure is that these small pickle plants are located in urban
areas where land represents a substantial part of the total investment.
Buildings, equipment, and other investments ere averages of plants operating
with the same configuration as the model plants shown. Depreciation, when
related to total depreciable assets, shows ranges, as previously mentioned,
from 6 to 16 percent. The single-commodity plants were more consistent in
their reported depreciation and group around C percent or roughly 12-year
life which includes buildings, which normally have a longer life and
equipment which normally has a shorter life. In multi-commodity plants, the
higher averages probably reflect newer plants with current higher costs and
possibly rapid depreciation schedules.
Working capital estimates did not come from the survey. These data are
based on a ratio of working capital to sales taken from annual reports of
food processing companies in 1973. Data from these annual reports showed a
fairly consistent relationship of 23.2:=, working capital to sales. This re-
lationship was used throughout this study although it is recognized that the
amount of working capital does vary from commodity to commodity.' Hulti-
plant companies did not make allocations of working capital on a commodity
by commodity basis and therefore the overall average of 23.2% was used for
both single- and multi -conrnodi :y plants.
6. Values and Costs Per Ton
Table 111-10 summarizes the relationships between' volume processed, sales
and costs per ton processed for the 52 model plants analyzed in this report.
For most commodities, total costs decreased as size increased. However,
there were exceptions where the small or extra small plants showed the
lowest cost per ton processed, primarily as a result of lower overhead costs.
III-ll
-------
Table III- 7. Estimated investment for industry segrents based on model plants —
single c"mnodity - 1-973
"-rodit/
'"" ~ - 1-1
Oor-
L „ S i" ?*C C~3
"_"- roc-s
'.,:•• re srrs
. .
•Me- "es
" • :"" 53
" :,1c3
"-j--r^-2ut
0;, •• "'•"•£ lit
T ..,,.,..,<.
~~ - - ., ,v -
-,,_, ^, ,,
c C ^ _OC 3
Type
C
C
r
c
c
c
c
c
c
c
c
c
c
•~
c
tons
s
M
XS
S
s
i'i
s
K
L
S
iv'
XS
c
M
XL
s ? n n L* 3 i
processed
5,500
13,000
200
1,500
2 , 500
5,000
1,5CO
6,000
10,000
6.000
9,500
1,500
£.500
25.000
150.000
l.ar.d
20
44
50
95
115
,/0
33
Q
15
1C
13
8
0
85
j. C r
sunrises
100
2/-0
205
l,27c
2,026
3,595
50
170
290
358
400
4 ?
03
8; 9
1,4 JO
Oeprccicble a
Eo.io^nt
150
£25
203
1,277
2,109
3,7-0
100
500
710
3£3
r\ ^ c;
150
195
1,049
2,7:"c,
ssets
Other
10
30
10
c n
125
273
10
20
30
59
70
—
—
157
155
Total
260
695
£58
2,700
4,375
7,750
160
690
1,030
730
925
192
309
2,025
4,324
Depn
$000
23
55
42
2^3
394
543
13
55
83
62
74
20
36
155
385
;ciation
Percent
9
8
9
o
9
9
8
8
8
8
S
14.0
11.7
8.1
8.7
Total
f -i v c. ^
• 1 /. C-vJ
assets
280
739
" 1 "
" lo
2,795
4,4?0
7,893
193
693
1,0-5
790
933
150
318
O i i r>
L. . I I \J
4,553
capila"
157
455
64
4S3
805
1.612
209
974
1,624
418
441
^0
1^9
831
3,7!2
asset;
£57
i j - / ~>
532
3.0"?
5.295
9 , 50 ?
402
1,5-3
2,659
1,203
1.379
200
-57
2,5-1
8,230
-------
Table III-3 . Estinatod investment for in it"; try segments b<)3ed on ncccl plants --
multiple commodity plants - 1973
Co~~odity
C*.rr.-;33S
Corn-peas
Corn-peas
Corn-peas
Ccrr.-psas-G. Beans-Carrots
Ccrn-poas-G. Beans-Carrots
Corn-pj,;s-G. Beans-Carrots
Cc'r.-pidS-G. Eiins-Cirrcts
Cirr.-p-.i3-G. EC' -s-Cdrrots
Corn-peas-G. Beans-Carrots
Ccrn-peas-G. Beans-Carrots
Cori-peas-G. Beans-Carrots
Broccoli
Lrcccol i-Caol if .-I. Deans-Spin.
Brcccol :-Caul •' . -I. Ceans-Spin.
Tcratoss-0. Beans
Tc~a*ce;-D. Eeans
Tc-TatTes-3. E^ans
To-itoes-3. Eeans
Tc/rit&es-D. Eeans
Cnerry-G. Sear.-Pear-Plun
Cnerry-G. Esir-^ear-Plum
Cu.erry-St'-ai:b-2rry-Car,eberry"
Cnerry-STrav.'terry-Canebc-rry
Cnerry-Strawberry-Car.eberry
P.CKli.To-ato.D. Bean, Dress.
3 Sa.ccs
Pickle, To~ato,D.Beon, Dress.
i Sauces
^ici'.'.e, To:rato,D.Eean, Dress.
i Sauces
Fickle, 7cr,ato,D. Bean, Dress.
& Sauces
Brinea Products
Er-,nji ProcuCts
Erir.od Products
Type
C
C
C
C
C
C
C
F
f
F
F
F
F
F
F
C
C
C
C
C
C
c
u
C
F
F
F
F
F
F
F
C
C
C
Size annual
tons processed
S
M
L
XL
S
M
L
XS
S
S
M
L
S
XS
S
M
L
XL
S
M
L
XS
S
M
XS
S
M
L
XS
S
M
3,000
12,000
37,000
120,000
10,000
25,000
50,000
b,30C
10,000
' 18,000
25,000
50,000
8,000
25,000
40,000
2,000
7,000
20,000
70,000
125,000
5,000
10,300
20^000
800
2,000
5,000
2,000
6,000
18,000
£0,000
1,500
6,000
10,000
Depreciable ac
Land
10
25
75
100
25
30
50
20
35
30
50
90
20
122
276
10
20
75
116
259
10' '
20
30
10
12
20
75
125
200
300
10
10
15
Buildings
20
250
705
1,904
175
496
814
224
349
433
594
954
314
548
691
59
207
592
2,072
3,700
150
200
450
62
120
225
720
1,440
1,440
2,400
100
358
400
Equipment
f rinn
220
500
1,057
2,900
385
744
1,221
336
523
650
891
1,431
446
823
1,035
79
291
838
• 3,033
5,450
200
300
750
93
180
339
1,075
2,150
2,130
3,500
no
363
455
:S6tS
Other
15
40
50
100
5
5
15
20
28
3
15
25
-
7
77
10
20
50
75
100
10
15
20
5
10
20
5
10
30
100
59
70
Depreciation
Total
255
790
1,812
4,940 '
565
1,245
2,050
SCO
900
1,036
1,500
2,410
760
1,378
1,804
148
518
1,480
5,180
9,250
360
515
1,220
160
310
585
1,800
3,600
3,600
6,000
210
730
925
SCOO
29
95
180
450
70
200
300
46
72
150
180
300
91
165
216
13
44
118
363
574
50
75
150
13
25
47
108
252
2SS
540
17
62
74
Percent
11.4
12.0
10.0
9.1
12.4
16.0
14.6
8.0
8.0
13.8
12.0
12.4
12.0
12.0
12.0
9.0
8.5
8.0
7.0
6.2
13.9
K.6
12.3
8.0
8.0
8.0
6.0
7.0
8.0
9.0
8.0
8.0
8.0
Total
fixed
assets
205
815
1,837
5,040
500
1,275
2,100
600
935
1,116
1,550
2,500
. 780
1,500
2,080
158
538
1,555
5,296
9,509
370
525
1,250
170
322
605
1,375
3,775
3,800
6,300
220
790
940
Working
capital
•--SOCO
640
1,974
5,403
559
1 ,395
2,733
219
-30
653
914
1,827
937
2 929
4^636
155
513
1,457
3,959
6,705
475
951
1,932
250
624
1,550
456
1,353
4,059
13,520
113
418
464
Total
assets
•^11
1 ,455
3,851
Il.-?'t3
1,1 --9
2,671
4,393
J19
1,373
1,77-1
2,45i
4,327
1,717
4,429
6.766
314
1,051
3,012
9,255
16,214
845
1,475
3,152
420
946
2,155
2,331
5,038
7,859
19,820
333
1,203
1,404
-------
oct'i o'c:
'-12 S£t
33
0 C ^ T
UO
-------
Table III-10. Relation-ship ix-t',,"_^;i si 20 c,f pl/n*. and cev.s per ton, fruit and vegetable Canning and
freezing plants, 1973
Value
COT ,:odity
and
prone rs
Corn--C
Com--C
Mushroo,;s--C
1'ijshr o.,v,:>--C
Mushrooi;.,--C
Mushrooi iS--C
Pickles--C
Pickks--C
PicUes--C
Sauerl reut--C
Sauerrt at, L--C
Tomatoes-- C
Tor,atocG--C
Tcnatoes--C
To')iatees--C
Corn-peas--C
Corn-pc;.r,--C
Corn-peas --C
Corn- pear --C
Corn-peas--F
Corn, peas ,C.r>er.ns ,
carrots-- C
Corn, peas ,G.Br£ns,
carrots--C
Corn, peas ,G. Beans ,
carrots--C
carrots--!
Corn, peas ,G. Beans,
carrots--F
Core ,1-eas ,G. Beans ,
can ols--F
Corn, pea:, .G.r.^ans,
carrots--F
Corn , pens ,C>. Deans ,
carrots--;
l-reccol i , caul i flower,
llu'd DLJI.S, SPI l:2Cii--F
Breccul i , raal i f lower ,
lir ; b'.ji'.s, :,;M:,,UI--F
tiroc c.jl l , cJLil i ; io'.'.vr,
linw booni, spii;ach--F
Size
ecus re
pro:'. pro
per ye-d
5,500
18,000
200
1,500
2,500
5,000
1,500
6,000
10,000
6,000
9,500
1 , 500
4,500
25,000
150,000
3 ,000
.2,000
37,000
120,000
10,000
10,000
25,000
50,000
5,000
10,000
18,000
25,000
50,000
8,000
25,000
40,000
w
(!')
(XS)
(S)
(S)
( '*)
U)
(S)
(f.)
(XS)
(S)
'' ' ' )
(I-)
(S)
('•)
(L)
(XL)
(S)
(S)
(M)
(L)
(S)
(f-0
U)
(M)
(I-)
Sales
135.
132.
1,390.
1 , 3C'J.
1,390.
1,390.
COO.
700.
700.
300.
200.
184.
180.
142.
106.
210.
230.
230.
230.
155.
240.
240.
240.
189.
189.
157.
157.
157.
505.
505.
505.
00
CO
00
'J J
00
00
CO
CO
00
00
GO
00
00
00
66
CO
00
CO
00
50
GO
76
76
00
00
50
52
50
00
00
00
Variabl
Raw
p. r od .
22.00
24.00
650.00
650.00
650.00
650.00
240.00
2,30.00
280 . 00
61.00
38 . 00
55.33
48.65
39.40
35.33
37 . 67
40.25
40.27
40.23
56.30
45.50
45.36
45.36
50.20
50.10
39 . 83
39 . 84
39.82
141.38
141 40
141.40
e c e
£'
63
6'J
245
264
264
50 '.
260
IOC;
107
120
75
47
54
40
32
65
72
72
72
19
98
98
98
68
71
58
58
58
130
124
106
or cost per to
,:ts
"ct
. 45
. 00
.00
.00
.00
.80
.67
.33
.00
.00
.89
.33
.00
.92
.00
. 66
.83
.81
.83
.60
.76
.80
.60
.30
.89
oo
.83
.25
.52
.05
Fixed
Over-
head
ri - 1 1 • r -
38.91
34 . 72
60 . 00
133.33
140.00
19.-.&0
66.67
272.33
272.90
81.00
48.21
42.66
52.22
39.40
22.20
70.00
82.75
88 . 84
90.58
41.00
67.90
65.60
69.52
35.20
36.70
29.78
33.32
33 . 94
195.50
207.76
198.00
r. process.
C'JSiS
Interest
~
4.18
3.11
210.00
162.00
157.60
10f,.60
8.67
9.17
8.30
10.33
7.79
33.33
8.00
C.60
2.57
9.67
7.08
4.05
3.33
6.90
• 6 . 00
7.20
5.40
9.20
7.20
7.22
5.60
5.40
11.38
4.00
7.50
?d
De-
preci-
ation
4.18
' 3.11
210.00
162.00
157.60
108.60
8.67
9.37
8.30
10.33
7.79
13.33
8.00
6.60
2.57
9.67
7.92
4 . 86
3.75
7.50
7.00
8.00
6.00
9.20
7.20
8.33
6.40
6.00
3 1 . 33
6.60
5.40
Tor.;-.]
cost:
132.73
128.94
1,375.00
1,371 20
1,369.20
1,367 80
581.67
6/9.00
6/5.50
2/2. 6/
17/.68
170.66
170.83
132.92
94.67
192.67
"10.83
210.84
210. 7C
131 .30
225.20
224.92
225.03
172.40
172.30
344.05
144.04
144.04
489.88
484.28
463.61
111-15
-------
Table 111-10. Relationship bcU'oon size of plint i.nJ costs per ton, fruit and vegetable car.nnyj and
freezing plants, 1973 (continued)
Size
Cc.iriodity tens rai;
and prod. proc.
process per year
'
Toii''ito°s , Dry beans--C
Tonu'foes, Dr.) beans--- C
TonuiLoes, Dry beans-- f
Tomatoes, Dry beans--C
Tomatoes, Dry beans---C ]
Cheriy, G. Beans, pear,
pi in;:- -C
Cherry, G. Beans, pear,
pi urn --C
Cherry,!1,. Beans, pear,
plum--C
Potato (.'nps-'-D
Potato Cnips~-D
Potato Chips--D
Potato Chips-- D
Potato Chips--D
Cherry ,Strawbet ry ,
cancbc-rrv--!
Cheriy, Strawberry,
canohpiT.)'-- F
Cherry, Strawberry,
canuberiy--F
Pickles, Toivatocs, D.
beans, Dressing &
Sauc e-j
Pickles, Tomatoes, D.
beans, Dressing &
sauces
Pickles, To.natocs, D.
Beans, Dixssint] &
Saures
Pickles, Tor.mtoes, D.
Beans , Di ess i ng S
Sam ; s
Brined Products
Brined Pro'iucls
Brined i'ro 'ucl s
2,000
7,000
20,000
70,000
125,000
5,000 (XS)
10,000 (S)
20,000 (H)
1,000
2,500
8,000
13,000
30,000
800
2,000
5,000
2,000
6,000
18,000
60,000
1 , 500
6,000
9,000
Value
or cost per 10'
Variable costs I
Sales
336.
315.
314.
243.
231.
410.
410.
410.
620.
530.
470.
410.
375.
1,345.
1,344.
1,335.
983.
978.
T71.
-.'71.
r 9.
K) .
a;o.
50
86
00
80
20
00
00
00
00
00
00
00
00
00
50
GO
50
83
94
33
GO
00
00
Raw
prod.
122.00
113.00
111.75
83.14
86.86
105.60
105.50
105.50
350.00
320.00
230.00
195.00
143.00
515.00
542.50
538.00
345.50
343.33
340.77
341.00
57.33
51.00
36.00
Other-
direct
121.
115.
114.
86.
80,
175.
175.
175.
96.
92.
88.
81.
98.
475,
481
482,
248,
260,
286
293
124
120
76
50
.00
30
56
,00
.60
.60
.50
00
,00
.00
.69
.33
.00
.00
,40
,00
.00
.33
.58
.67
.00
.00
OVv
I:;
i -
65
61
61
46
43
75
80
80
104
100
95
88
106
255
259
259
203
213
234
240
101
81
51
•', processed
~ixed costs
.r-
:ad Intcres'
1 1 .-
.50
.Kb
.55
. 60
.10
.80
.30
.50 -
.00
.00
.38
.46
.53
.00
.00
.80
.00
.00
.28
.22
.00
.00
.10
6.50
6.29
5.90
5.19
4.59
9.00
7.00
6.75
20.00
20.00
17.63
14.30
7.83
16.25
12.50
9.40
54 . 00
12.00
16.00
9.00
11.33
10.33
7.40
De-
preci-
t ati on
6.50
6.29
5.90
5.19
4.59
10.00
7.50
7.50
25.00
24 . 80
22.12
17.85
9.80
16.25
12.50
9.40
54.00
42.00
16.00
9.00
11.33
10.33
7.40
Total
costs
" . - -
322.00
30^.43
299.40
231 .14
219.14
376.00
375.80
376.75
595.00
556.80
453.13
397.30
367.50
1,307.50
1 ,307.50
1,299.00
904.50
900.33
893.39
892.80
308.67
272.67
1/8.00
111-16
-------
In general, raw product costs were reasonably consistent within a
specified product category. However, in some instances small producers
showed, either higher or lower costs than did larger, commercial packers.
Where raw product costs were low, it is assumed that producers either had
access to low-cost local supplies or produced a substantial part of their
production requirements. Where raw product costs were higher for small
producers, it is assumed that they were buying on the open market rather
than through grower contracts.
Other direct costs generally decreased with size or showed little variation
among size groups.
In many instances, overhead costs, per ton of product processed, increased
with size. In particular, the extra-small plants had lo'wer overhead than
did other sizes.
Interest and depreciation costs per ton of product tended to decrease with
size of firm.
C. Model Plant Incone
Tables III-ll through 111-24 show a complete income statement for all
node! plants. These annual income statements were derived from industry
surveys and feature sales, cost breakdown between direct and indirect
costs, income, profitability, and cash flow.
Model plants achieve a positiv- cash flew for all sizes of plants and for
all combinations of commodities.
1. Corn Cannii-g Plants - Table 111-11
Corn plants are characterized by very short seasons, normally two months,
and by a low ratio of finished product to raw product processed. Because
the comrcdity is common and widely-grown, competitive pricing dictates
that profitability will be low and the model plants reflect this.
2. "ushroorr Cannipn
Very low profitability was seen in mushroom plant models, resulting net so
much from nigh processing costs us from lower than expected unit sales due
to credits for returns because of possible contamination. These results were
reflected in the model plant budgets as a result of industry survey data.
111-17
-------
3. Pi eld e Canning Plants - Table 111-13
Industry survey data analyzed may not reflect, all the factors of pickle pro-
duction variations in the field. The three model plant, sizes show economies
of scale although this may not be consistent were wider data responses
available. Smaller urban pickle operations sometimes are merely oversized
household or industrial kitchens where local markets with distinctive taste
requirements are important. At the other end of the scale, mass markets
with standardized products may be less profitable than models show.
4-r Sauerkraut Canni ng ji_Ts.b1_e_I I T-_l^
Sauerkraut, canners exhibited better than average profitability for all
canners. Part of this result may be due to a low raw product cost relative
to sales price and a year-round canning operation to go with high volume
cabbage slicing operations in season.
5 . Toma t o_ C a , n nj n g - Tab 1 e III -• j 5_
Tomato canning operations, reflected in model plant profitability, are both
simple and complex. Response from tomato processors in the survey was high
and reflected tomato products, peeled, unpeeled, juice, puree, paste, ketchup
and a host of other tomato items. The variety of items mode for a wide
spreod in product values and processing costs. These great differences show
up in the fact, that the srrol 1 and medium plants rre slightly less profitable
than the extra small plant. However, the extra large tomato processing model
was in the very top group of all model plants in terms of profitability.
6. Corn- Pea CsrmuK '} '")c
Corn-pea plants are the most frequently-occ' 'ring of the mul ti --commodity
plants. These four model corn-pea plants also illustrate improved profit-
ability as compared to single commodity corn plants.
7. __ Corn -Pea- GeTeCr tCnn ing Plant - Table M 7
In spite of previous generalizations concerning canning and freezing plants,
we find here industry data that show higher cales and higher profitability
for canning plants as compared to very similar freezing plants. This may
be primarily due to the high profitability of canned green beans which, showed
up consistently in the survey, However, indications are that expanding green
bean processing may reduce the profitability of this commodity.
8. Corn- Peaj-J^)'_e^n_ J^MrTj^^r rqt_Jr_roe_7_i !iq_PJ_a_nt _-_ Tab 1 e 1 1 T -• 1 8
The profitability of -'ies> fr.-ezinq plants is unexpectedly lower than
similar canning plants becdi.ic the value of sales per ton are lower
aecor":in<.j to survey data. ',,,.~e lower sales anc! fronts taken together
with 'inner i''v-~' * v/a account fc." lower »eturn on investment.
iil-l
-------
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cu ro
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rr rt rt
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ro
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i
i—
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rs
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rr
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ro
ro
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rs
r-t"
1
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trr
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-------
Table III-ll. Estimated annual cash flow and rate of return on average invested capital for model
corr Canning clants, 1973.
o
5,500 tons/vear
$1,000 " oercent
Sal
n _ ,
u - .'"'
j. j ; ^J
lit
Dep
pro
Ir,c
Aft
Arv,
~ct
Ov-->
• -r
r -i .-
es
"rcduct Cost
°r Cirsct Cost
i rect Cost
erest
reciation
-tax Ir,co™,e
o."-~ tax
er-tax income
ual cash flow
al Investment
rax ~0T
er tax ROI
h flow ROI
743
121
3^9
214
23
23
13
3
10
33
437
100
15.
£7.
29.
3 .
o .
1.
5.
2.
7.
3
0
0 .
0
0
7
3
3
6
13,000 tons/year
Si, 000 percent
2,375
432
1,152
625
56
56
55
20
35
91
1,174
100
IS.
48.
25.
2.
2.
2.
4.
3.
7.
n
5
4
3
3
3
7
0
8
-------
Table 111-12. Estimated annual cash flow and rate of return on average invested capital for model
mushroom canning plants - 1973
200 Ton/Year
Sales
Raw Product Cost
Other Direct Cost
Indirect Cost
Interest
Depreciation
Pre-tax Income
Income tax
After-tax income
Annual Cash Flow
lotal Investment
Pre tax ROI
After tax ROI
Cash Flow ROI
51,000
278
130
49
12
42
&',!
3
1
2
44
582
Percent
100.0
47.0
18.0
4.0
14.4
14.4
1.2
0.5
0.3
7.6
1,500 Tons/Year
$1,000
2,085
975
396
200
243
2 43
23
7
21
254
3,278
Percent
100.0
47.0
19.0
10.0
11.3
11.2
1.4
0.9
0.6
8.1
2,500 T
11,000
3,475
1,625
660
350
394
'}0/1
*J ~j i
52
18
34
428
5,296
ons/Year
Percent
100.0
47.0
19.0
10.5
11.0
11.0
1.5
1.0
0.6
8.1
5,000 Tons/Year
SI, 000
6,950
3,250
1,529
974
543
543
111
47
64
607
9,502
, srcent
100.0
47.0
22.0
13.4
8.0
8.0
1.6
1.2
0.7
6.4
-------
Table 111-13. Estimated annual cash flow and rate of return on average invested capital for model
pickle canning plants - 1973
1,500 tens/year
$1,000 Percent
Sales
Raw ?
I n d i r
roouct
Direct
act Cos
Interest
Cost
Cost
t
Depreciation
Pre-t
Incor:
After
A.nnua
Total
ax Ir.co
3 tax
Tie
-tax income
1 cash
Invest
f 1 ow
ment
900
350
391
100
13
13
23
5
18
31
402
?r2 tax ROI
After
r^<;h
tax RO
f i nw «n
T
I
100
40
43.
11
1.
1.
2.
5.
4.
7.
5
5
5
5
7
5
7
6,000 tons/year
$1,000 Percent
4,200
1,580
550
1,634-
55
55
125
54
72
127
1,573
100
40
15
39
•t
1
3
7
4
7
.4
.3
.3
.5
.3
.6
10,000 tons/year
$1,000 Percent
7,000
2,300
1,070
2,719
83
83
245
111
134
217
2,659
100
40
15
39
1
1
A
9
5
8
.2
.0
. 1
-------
Table 111-14. Estimated annual cash flow and rate of return on average invested capital for model
sauerkraut canning plants - 1973
ro
(-0
Sales
Raw Product Cost
Other Direct Cost
Indirect Cost
Interest
Depreciation
Pre-tax Income
Income tax
After-tax income
Annual Cash Flow
Total Investment
Pre tax ROI
After tax ROI
Cash flow ROI
6,000 tons/year
$1,000
1,800
306
720
486
62
62
164
72
92
154
1,208
Percent
100
17
40
27
3.5
3.5
9
13.6
7.6
12.8
$1,000
1,900
361
721
458
74
74
212
95
117
191
1,379
9,500 tons/year
Percent
100
19
38
24
4
4
11
15.4
8.5
13.8
-------
Table 111-15. Estimated annual cash flow and rate of return on average Invested capital for model
tomato canning plants - 1973
t— H
1 <
t— 4
»
-£a
C:.]e3
Dru Ov^. ^ Cost
i ~ Cost
'_ _ 0 t.
Interest
r* ,>---iat.-io-
Pre-tax Incor.e
Incorr.s tax
o ~ t i* d A t . i \~ U 1 1 i ci
Anniia1 cash flow
Total Investment
re v.ax ROI
• •fier tax ROI
Cash flow 301
1,500
$1,000
276
S3
71
64
20
20
18
4
34
tons/year
Percent
100
30
26.5
23
7
7
6.5
9.0
7.0
17.0
4,500 tons/year
$1,000 Percent
810
219
243
235
36
36
41
13
28
64
100
27
30
29
d. 2
4.' 2
5.6
• 8.8
6.0
13.7
25,000 tens/year
$1,000 Percent
3,550
985
1 ,023
985
165
165
227
102
125
290
100
24
31
33
D
5
6.4
7.7
4.3
9.9
1 50,000 tons/year
$1,000 Percent
16,000
5,300
4,830
3,330
335
335
1,800
858
942
1,327
8,280
100
33
30
21
2.4
2.4
n .2
21.7
11.4
16.0
-------
Table 111-16.
Estimated annual cash flow and rate of return on average invested capital for model
corn - pea canning plants - 1973
3,000 tons/year
$1,000 Percent
Sales
Raw Product Cost
Other Direct Cost
Indirect Cost
Interest
Depreciation
Pre-tax Income
Income tax
After- tax income
Annual cash flow
Tctcl Investment
630
113
1D7
210
29
29
52
1C
34
63
411
100
18
31
33
5
5
3
12,000 tons/year
$1,000 Percent
2,760
483
874
993
85
95
230
104
126
221
1,455
100
13
32
35
3
3
8
37,000 tons/year
$1,000 Percent
8,510
1,490
2,694
3,237
150
180
709
334
375
555
3,861
100
18
32
39
1.4
1.6
8
120,000 tons/year
$1,000 Percent
27,600
4,834
3,740
10,870
400
450
2,305
1,100
1,205
1 ,656
11,443
100
13
32
39
1.4
1.6
8
Pre tax ROI
After tax ROI
Cash flow ROI
12.6
8.3
15.3
15.8
3.7
15.2
18.3
9.7
14.4
20.2
10.5
14.5
-------
Table 111-17. Estimated annual cash flow and rate of return on aveage Invested capital for model
corn - pea - green bean - carrot canning plants, 1973
10,000 tens/year
$1,000 Percent
i , 3
;'j.', Product Cost
r
T
i
-
r
ther D
ncirec
rt^r9<;
eprec".
re- tax
r c o r" ^
* •- '^ - 1
Annual
T
r
otal I
^e tax
fter t
irect Cost
x f"<;t
U \J^J *} (,
t
ation
Income
tax
ax inccme
cash flow
nvestmant
ROI
ax ROI
/"• i . r "") C\ T
2,408
• 455
988
579
60
70
156
63
£3
158
1.149
100
19
41
28
2.5
3
6.5
13.6
7.7
• n . 8
25.000 tons/year
$1.000 Percent
6,019
1,134
2,469
1,640
180
200
395
184
212
412
2,671
100
19
41
27
3
3.4
6.6
14.8
50,000 tons/year
$1,900 Percent
12,038
2,263
4,940
3,476
270
300
784
370
414
714
4,892
100
19
41
29
2.
2.
6.
16.
1
4
5
0
1
-------
Table 111-18. Estimated annual cash flow and rate of return on average invested capital for model
corn - pea - carrot - green bean freezing plants, 1973
5,000 tons/year
Sales
Raw Product Cost
Other Direct Cost
Indirect Cost
Interest
Depreciation
Pre-tax Income
Income Tax
After-tax Income
Annual Cash Flow
Total Investment
Pre-tax POI
After-tax ROI
Cash Flow ROI
$1,000
845
251
343
176
45
46
83
33
50
96
819
Percent
26.2 -
36.0
19.0
5.0
5.0
8.8
10.1
6.1
11.7
10,000 tens/year
$1,000
1,890
501
711
367
72
72
167
74
93
165
1,373
• Percent
26.2
37
19
5
ID
8.8
12.2
6.8
12.0
18,000 tons/year
$1,000
2,835
717
1,060
536
130
150
242
110
'132
282
1,774
Percent
100
25
37
19
5
5
8.5
13.6
7.4
15.9
25,000 tons/year
$1,000
3,938
996
1,472
833
140
160
07-7
JO/
155
182
342
2,464
Percent
100
25
37
21
3.5
4
8.5
13.7
7.4
13.9
50,000 tons/year
$1.000
7,875
1,991
2,944
1,697
270
300
673
316
357
657
4,327
Percent
100
25
37
22
3.4
4
8.6
15.6
8.3
15.2
-------
'•"ab^e 111-19. Estimated annual casn flew and reie of return on average invested capital for model
trocceli - cauliflo.ver - li^a ba?"s - soinach freezing plants, 1973
a,::n tons/y-r
7
c
I
1
"^
p
T
A
A
T
p
r
-~
. 1 ^s
aw Product Cost
ther Direct Cost
"direct Ccst
n tsrss t
.. _veci ation
;-<;-tax Inccoie
ncc~re Tax
~ter-tax income
n-K'sl Cash How
c:?i Inv23t~£ni:
re-tax ROI
fter-tax ROI
as? Flc,-,1 ?OI
$1,000
ii n i o
1,231 '
1,0^-2
i 5 o 4
: 1
C, ;
121
52
t r
-i ^ ,-,
.1? J
1,717
P^rcer;
:co.o
2S.O
25.0
3 ".6
2 . 2
2.2
3.0
7.0
^. n
J. 3
•7 - ,- p n i. r
51, oc:
12 ,62b
O " 7 C
^,^0^
3,1:3
5,19"
100
155
518
2-, 2
£/0
dC ^
^,^29
\°s/year 40,000 tons/year
Percent
100
28
25
41
1
1
4
11.7
6.2
10.0
$1
20
5
4
7
1
1
6
,000
,200
, 606
,242
,920
3"0
2:6
,656
788
,084
,765
Percent
100
28
21
40
-T
1.
8
24.
11.
16.
4
6
5
6
0
-------
rv
Table 111-20. Estimated annual cash flow and rate of return on average invested capital for model
tomato - dry bean conning plants, 1973
Sales
Raw Product Cost
Other Direct Cost
Indirect Cost
Interest
Depreciation
Pre-tax Income
Income Tax
After- tax Income
Annual Cash Flow
Total Investment
Pre-tax ROT
After- tax ROI
Cash Flow ROI
2,000 t
$1,000
673
244
243
131
13
13
29
7
22
3 j
314
ons/year
Percent
100.
36.
36.
19.
2.
2.
4.
9.
7.
11.
0
0
0
7
0
0
3
2
0
1
7,000 tons /year
$1,000
2,211
791
805
433
44
44
94
39
58
102
1,051
Percent
100.0
35.7
36.3
19.7
2.0
2.0
4.3
8.9
5.5
9.7
20,000 tons/year
$1,000
6,280
2,235
2,285
1,231
113
118
292
134
158
276
3,012
Percent
100.0
35.6
36.4
19.6
1.9
1.9
4.6
9.7
5.2
9.2
70,000 tons/year
$1,000
17,066
6,170
6,059
3,252
363
353
849
401
448
811
9,255
Percent
100.0
36.0
35.0
20.0
2.0
2.0
5.0
9.2
4.8
8.8
125,000 tons/year
$1,000
28,900
10,858
10,000
5,387
574
574
1,507
717
790
1,364
16,214
Percent
1CO.O
37.6
34.6
18.6
2.0
2.0
5.2
9.3
4.9
8.4
-------
Table 111-21.
Estimated annual cash flow and rate of ^eturn on average invested capital for model
cherry - green bean - pear - plum canned plants, 1973
I
o
5,000 tons /year
$1,000 ^ercent
cales
Paw Product Cost
Other Direct Cost
indirect Cost
\ merest
r-nv-eciation
Pre-tax Incoir.a
Tr.ccrrp tax
hfter-tax income
Annual cash flow
Total Investment
Pre tax ROI
After tax ROI
Cash flow ROI
2,050
523
878
379
45
50
170
75
95
145
845
ICO
26
43
- p
"2.2
2.4
8.4
20.1
11.2
17 !l
10,000 tons/year
$1,000 Percent
4,100
1,055
1,755
803
70
75
342
158
184
259
1/76
100
26
43
20
1.7
1.9
8.4
23.2
12.5
17.6
20,000 tons /year
$1,000 Percent
8,200
2,110
3.510
1,610
135
150
535
322
353
513
3,152
100
26
43
20
1.6
2
8.4
21.7
11.5
16.3
-------
Table 111-22.
Estimated annual cash flow and rate of return on average invested capital for model
cherry, strawberry, caneberry freezing plants, 1973
800 Tons/Year
Sales
Raw Product Cost
Other Direct Cost
Indirect Cost
Interest
Depreciation
Pre-tax income
Income tax
After-tax income
Annual cash flow
Total investment
$1,000
1,076
436
3£0
204
13
13
3C
8
22
35
420
Percent
100.0
40.5
35.3
19.0
1.2
1.2
2.8
2,000 Tons/Year
$1,01)0
2,689
1,085
962
518
25
25
74
29
45
70
946
Percent
100.0
40.3
35.7
19.0
1.0
1.0
2.8
5,000 Tons/Year
$1,000
6,678
2,690
2,412
1,299
47
47
183
81
102
149
2,155
Percent
100.0
40.3
36.1
19.5
0.7
0.7
2.7
Pre-tax ROI
After tax ROI
Cash flow ROI
7.1
5.2
8.3
7.8
4.8
7.4
8.5
4.7
6.9
-------
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-P> -~J
-Pi cn
j — » i — *
co en
ro co
-Pi CD
73
OJ iV
^
fD
~U C/)
-5
O
Q-
O
rr
CD
O
rt-
t— i
«
cn CD
UD cn
>— * "^-1
1 — t
CA> CD
i.n O
0 0
ro cn
t» t»
CD CO
cn ^j
O CO
, .
CO CD
en CD
CD O
f — 1
cn -~j
i — * _pi
CO CD
Pi cn
i — i
OJ O
cn o
O O
IX) en
O CO
-pi ro
cn co
0 0
i — >
CO O
cn o
1
1
t/> ro
i — . ^»
- I'D
O CD
*.._> CD
O
-H
O
T3 17)
ro -^
~s "*^
O fD
r.: OJ
r-t
-oo- cn
1 — ' ^
" "P
0 CD
0
o
:;s
,1) ^^
-1 -<
o ro
3 T
n
;y-j. j — i
'— CO
CD O
CD CD
O O
0
-a rs
(D CO
-5 ~-~.
O -<
ro ro
c-t T
-o> cn
f-> O
00
CD 0
0 0
—I
o
-a rs
CD CO
-s ^
O -<
fD ft)
ZJ OJ
r~4- -«
I — 1
°J-
fD
i — i
t — (
i — i
1
ro
CO
-._-]
!„
r> m
,?r oo
— ; rT
ro -i.
•/) 3
V. ft)
rr
-H fD
O CL
=3
OJ OJ
rr 13
o rs
c:
OJ
O — '
^< 0
CD
CO cn
fD ~^~
0'
-3 — h
O
O 5!
"^
ro oj
CO 3
•J\ CX
^5 ""i
CQ ;-'
in r-h
•T>
O)
rs O
a. ->.
u~> -*,
oj ro
c: rr
(D i!L
ro -5
t/1 rs
o o
rs CJ
rs CD
OJ
'O 1Q
— ' a>
OJ
C~i~ 13
oo <
» fD
CO
] I f~^
UD ro
^^j ^
CO
o
OJ
-a
OJ
-h
o
3
o
0-
fD
i
co
^-' CD CD --1 ro CD
-------
Table 111-24.
Estimated annual cash flow and rate of return on average invested capital for model
brined products canning plants - 1973
1,500 Tons/Year
$17000
Percent
6,000 Tons/Year
$1,000 Percent
10,000 Tons/Year
$1.000 Percent
OJ
U)
Sales
Raw Product Cost
Other Direct Cost
Indirect Cost
Interest
Depreciation
Pre-tax income
Income tax
After-tax income
Annual Cash Flow
Total Investment
Pre tax ROI
After tax ROI
Cash flow ROI
509
86
187
156
17
17
46
16
30
47
338
100
17
37
31
3
3
13.6
8.9
13.9
1,800
306
720
486
62
62
164
72
92
154
1,208
100
17
40
27
3.5
3.5
13.6
7.6
12.8
2,000
361
760
511
74
74
220
99
121
195
1,404
100
18
38
25
4
4
11
15.7
8.6
13.9
-------
Table 111-25.
Estimated annual cash flew and rate of return on average invested capital for model
Potato Chips plants - 1973
1,000 Tons/Year
,__,
* — !
1
t.J
_V_J
Sales
, ..', , rocuct
Other Direct Cost
Indirect Cost,
"ntersst
Depreciation
-re-tax Income
Ircc:"e ta/>
After-tax income
Annual cash flow
Total Investment
Pre tax ROI
After tax ROI
Cash flow ROI
$l,OuO
620
350
95
1C4
20
25
25
6
19
44
3 $4
Percent
100.0
56.0
15.0
18.0
3.0
4.0
4.0
7.3
5.5
12.8
2,500 Tons/Year
$i,coo
M50
800
230
250
50
62
58
21
37
99
811
Percent
100.0
55.0
16.0
18.0
3.0
4.0
4.0
7.2
4.6
12,2
8,000 Tons /Year
Si, 000
3,760
1,840
704
763
141
177
135
58
77
254
2,272
Percent
100
49
18
20
4
5
3
5
3
11
.0
.0
.4
.0
.0
.0
.6
.9
.4
2
13,000 Tons/Year 30,000 Tons/Year
$1,000
5,330
2,535
1,062
1,150
186
232
155
73
92
324
3,187
Percent
100.0
48.0
20.0
22.0
3.0
4.1
3.1
' 5.2
2.9
10.2
$1,000
11,250
4,350
2,950
3.196
235
294
225
102
123
417
5,310
Percent
100.0
39.0
26.0
28.0
2.0
3.0
2.0
4.2
2.3
7.9
-------
D. Return on Investment
In Table 111-26, the results of the returns on invested capital by model
plant -ere displayed. From this table, several general conclusions can
be made:
1. Multi connodity plants have a more satisfactory return than do
the single commodity plants and the specialty plants.
2. Freezing plants average somewhat higher returns on invested
capital than do canning or dehydrating plants. For pre-tax
ROI, tha average figure is 13.5 percc it for freezers, 11.7
percent: for canners and 5.9 percent for dehydrators.
3. Although most groups of model plants exhibit rising rates of
return by size of plants, there are exceptions in four groups
out of the 15 groups.
Pos_sible_ Inpac_ts
From the foregoing statement and the tabulation of Table 111-26, there
are indicated several areas of potential impacts which may develop from
added costs of pollution control. Those plants with marginal returns on
investment, i.e., less than 6 percent, will certainly have difficulty
financing pollution controls arid paying for any incremental operating costs
Most seriously impacted are mushroom, corn and potato chip plants.
Less potentially impacted5 but still vulnerable, are pickle plants of all
sizes and the three smaller tcmato plants.
E_. Va 1 ug
For each model plant, there are three ways in which assets can be valued.
In each case the values used in this analysis were based on the industry
survey of plants.
Table 111-27 shows a tabulation of all model plants and the results of
valuing the assets at:
a. Salvage value
b. Book value
c. Reolacement value.
111-35
-------
Table 111-26. Model giants return on investment - 1973
Hodi'l plants
Coraiodities 1)
Single Cornnodity l'i ants
Corn
Cot n
Hushr'joms
I1ushroo-:'s
Mushrooms
Hjshreo. is
Pickles
PicKles
Pickles
Sauerkraut
Sauerkraut
Tomatoes
Tonatces
Tomatoes
Tomatoes
Multi-Co^ iodi ty plants
Corn, peas
Corn, peas
Corn, peas
Corn, peas
Corn, p"as, G. Beans,
carrots
Corn, peas, G Reanr. ,
carrots
Corn, pets, G. Beans,
carrots
Corn , ' " ^s , G. Per, n j ,
cor
Corn, , .: , G. B> »,,,
c a r r o i '.
Corn, PC'S, G. ['.i-din,
cai i ''ts
Corn, pecs, G. [Vi.;is,
Cc"rrete
Corn, pec. s, G. R;d:r>,
carrots
Broci,; ' . , rr-ii 1 1 ;' ' I •
Put .• ; " f n i;,s
!' < >1 C i| s
I'o! >' • lii,.
IV t ;'" i< "-,
1 ' 1 1 i : . i n i . .
^JiO
C
C
C
C
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
F
r
r
F
F
F
r
c
c
c
c
c
c
t
c
f
(
r
c
c
c
c
c
c.
(
V'
1)
;l
I'
1)
Si/e
fanual
t on b
5,500
18,000
200
1,500
? , 500
5,000
1,500
6,0'JO
10,000
6,000
9,500
1,500
4,500
25,000
160,000
3,000
32,000
3/.000
120,000
10,000
25,00'J
50,000
5,000
10,000
18,000
25,000
60,000
8,000
25,Cr)0
40,000
2,010
7,01'0
?0,0'!0
70,000
ir»,coo
5,000
5 0,00:.
?0,000
TOO
2,f)')0
!..IXiO
2,nno
d",WJ
18,0'Ki
60,000
1,500
6, ('O;)
JO.UJO
l,n;'i
f' ' ! )
?',() 'tl
1 '• , w '' )
-> ' , ' '' '' '
t* i e • tax
no i
6.3
4.7
0.5
0.9
1.0
1.2
6.7
7.5
9.2
13.6
15.4
9.0
8.8
7.7
21.7
12'. 6
15.8
18.3
20.2
13.6
14.8
16.0
10.1
12.2
13.6
T/.7
15.6
7.0
I!./
24.5
9.2
8.9
9 7
9.2
6.3
20 1
23.7
11.0
7.1
7.8
8.5
C.'i
9.3
i ;-, . o
23.1!
11. r,
n.'.
16. /
/.-;
7 '-'
', fi
' 2
•1 ./
After-lax
KOI
_ _ _ _ _ i p j cent — ______
2.3
3.0
0.3
0.6
0.6
0.7
4.5
A. 3
5.0
7.6
8.5
7.0
6.0
4.3
11.4
8.3
8.7
9.7
10.5
7.7
7.9
8.5
6.1
6.8
7.4
7.4
8 3
4'.0
6.2
11.6
7.0
5.5
5.2
4.8
4.9
11 .2
12.5
6.2
5.2
4.8
4.7
3.8
4.9
9. A
}2.f
8.0
7.6
8.6
r i
', . '•
3, 1
2. :;
2 i
Cash flow
R01
7.6
7.8
7.6
8.1
8.1
6.4
7.7
7.6
8.1
12.8
13.8
17.0
13.7
9.9
16.0
15.3
16.2
14. A
14.5
13.8
15.4
14.6
11.7
12.0
15.9
13.9
16.2
9.3
10.0
16.0
11.1
9.7
9.2
8.8
8.4
17.1
6.2
8.7
8.3
'/ ,A
6 9
O . 'J
<;.g
13.1
15.1
13.fi
12, a
13.9
12.8
i ;> . >
11 .2
1 V- . ?
!.-,
Ill-.'tti
-------
Table II1-2/. Oc ",\M r.oii (it t/.'.it diid s.ilvj-iL- v.ili.os of fi>,,^l ^s'-ots of ivo-Iel plants, 1973
Coriro;1! t tos
Sjmjlj^CCV. -)dl|y_[,Jr-rts
Corn
Pickles
Si lies kiv ut
Toralor-s
Corn, p.--5
fot it'.. C
Type
. s
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
c
1
F
F
F
F
F
r
F
c
c
c
c
c -
c
c
c
F
F
F
.[, ,
0
c
r,
c
c
r
t
r
t;
i,
i
Sl?0
Aniiuj 1
tons
5,500
18,000
200
1 , 500
2,500
5,00,1
1,500
6,000
10,000
6,000
9,500
1,500
4,500
25,000
150,600
3,000
12,000
37,000
120,000
10,000
25,0^0
50,0 JO
5, ('00
10,0'0
18,000
25,000
50,000
8,000
25,000
40,000
2,000
7,000
20, (.00
70,000
125,000
5,000
10, (00
20,000
800
2,000
5,000
2,f""i
C / ''0
10 / ^
60,0-0
1,660
6,o":i
lO.f'JO
1,000
2,'/.'J
I:.' '• .
li, .',
'";,[.' it
lard
20
44
50
95
llD
140
33
9
15
10
13
8
9
65
181
10
25
75
100
25
30
50
20
3'j
30
50
70
20
1 2?
270
10
20
75
116
259
40
78
I'.O
10
12
2U
75
12',
'i\ 0
liuO
10
10
15
20
"-"'
40
! -1
1-iU
HUM. V,i
and
fquip
260
695
468
2,700
4,37'.
7.750
160
60j
1,030
78
925
1:'.
1 fiO
445
1,^00
1 ,',,',.
2, , ,')
l.i,-
. Total
280
739
518
2 , / 10 .,
4 .rt'fO
7, COO
193
699
1 ,045
790
938
200
318
2,110
4 ,5:>8
205
815
1,887
5,o;o
500
1,2/5
2,100
600
£3")
1 , ] ! 6
] r'.)0
2,500
780
1 ,600
2,00/J
158
533
1 , 5 '. -•
5,2-05
9,50-;
927
2,185
3,550
170
3 ''2
f'j5
1 ,(:/>.
'( , / /
'' , ,' f i
C.30J
2''0
7 0
9',0
?--,,-l
4 / 3
1,40)
) ,'''.. '
2,;o,
Land
" *» nfK
20
44
50
95
115
140
33
9
15
10
13
8
9
85
1H4
10
25
75
100
25
30
50
20
35 ,
30
50
70
20
122
276
10
20
75
116
259
40
78
150
10
12
20
75
1'5
200
300
10
10
15
20
30
40
50
140
"Buil
and
1 qui
)
26
70
47
270
438
775
16
69
103
78
92
19
31
202
438
26
79
180
494
56
125
200
58
50
109
150
241
75
1 33
180
• 15
52
143
518
925
89
2)1
380
16
31
69
180
3(0
3f.O
600
2)
7li
93
18
45
H,,
1 ' /
(' 'U
K'cKI'J V.llu
d
p. Total
46
114
97
365
653
915
49
78
118
88
105
27
40
287
622
36
104
255
694
81
155
250
78
125
133
200
3)1
96
260
456
25
72
223
634
1,184
129
289
530
26
43
79
255
485
560
900
31
88
108
30
75
176
2/6
396
Vi-K nVt
of Hook
- — -
If,
15
18.7
13.1
12.3
11.6
26
11
11
11
11
14
13
14
14
14
13
14
12
14
12
12
13
13.4
12
13
12
12.3
17
22
15.8
13.4
14.3
12.0
12.5
14
13
13
15.3
13.4
13.1
13.6
13.0
14.7
14.3
14.1
11.1
11.5
10.0
16.8
12.6
13.7
14.6
111-37
-------
1. Book Value
For the model plants, the book value is shown in total in Table 111-26
and in detail in Tables III-7, III-8 and III-9. Book values are usually
well below original costs as these values are normally the depreciated
values carried on company records in 1973. Book value lists land at its
original cost and the depreciable assets, buildings, equipment, and other
are listed at a net depreciated value which is the original cost less the
amount accumulated and taken as depreciation for each asset.
The values for these model plants were generated from data from the in-
dustry survey and therefore are characteristic of plants processing those-
commodities considered in this study.
2. Salvage Value
Salvage value assumes the closure of the plant and the sale of the assets
either individually or collectively for a non-consistent use. This method
rules out the sale of the plant to another company which would continue to
operate the facilities for the same purpose, thus making no change in total
productive capacity of the industry.
The salvage valuations shown in Table 111-27 assume that land has a salwv:
value equal to its original cost and can be resold at that cost. There may
be given circumstances where land values have increased substantially above
original costs and salvage sale of lane! could return more than 100 percent
of its original cost. However, for purposes of this an&iysis., the assumption
is made that land will be salvaged at a value equal to its original cost.
Buildings, equipment and other assets have less salvage value as related
to cost than does land. For purposes of this analysis, an assumption hos
been made that this salvagt value will average 10 percent of the current
depreciated values shown in Tables III-7, III-8 and III-9.
Working capital is not shown in the
theless is part of the total assets
fixed assets of Table 1 1 1-27, never-
of Tables III-7, iII-8 and III-9. In
determining values of salvage in the impact and closure analysis to follow
working capital is considered current and liquid and therefore subject t-
salvage at 100 percent: of its book value.
In summary, the salvage value of assets shown in
of the following percentages of book value shown -'
Table 111-27 is made up
the model plants:
Land
Buildings
Equipment
Other Assets
100%
10%
1025
111-38
-------
In this table, the recoverable value of the total fixed assets range from
a low of 11 percent to a high of 25 percent. Normal recovery or salvage
rates would be from 12-15 percent. The very high 25 percent salvage rate
appears to be a unique condition in the small pickle plant where land
value is an abnormally high portion of the fixed asset value.
3. Replacement Value
Replacement implies that land, buildings and equipment are replaced as new
in the current market. In comparison with book value., which is a depreciated
value, replacement cost will be higher, primarily because of two factors:
1. Replacement value (new cost) is an undepreciated value; whereas,
book value is a depreciated fioure--the amount of the depreciation
being a function of the age of the plant and equipment.
2. Prices of land, buildings and equipment have risen substantially
as a result of inflationary pressures and resultant higher costs
of labor, materials and land.
From the industry survey, respondents have indicated that replacement
costs vary from two to 12 times book value. Considering this survey and
the factors enumerated above, it appears that replacement cost or value
will average five times book value. These will be values that can be used
when considering investment costs for new sources.
111-39
-------
IV. PRICING EFFECTS
The industry impact of increased processing costs associated with the
imposition of requirements for effluent pollution controls on the fruit
and vegetable processing industry will be directly influenced by the
ability of processors to pass pollution control costs forward to the
consumer in the form of higher prices for finished products or backward to
suppliers in terns of lower prices for raw materials and purchased
services. To the extent that such cost-trdnsference opportunities are
limited, then the costs of effluent controls will have to be absorbed by
processors, profits will be reduced and the impact on the industry will
be more severe.
The specific price impacts of effluent controls, for the fruit and vege-
table processors included in this analysis, will be considered in Chapter VII
Impact Analysis. This chapter will examine those industry and product char-
acteristics which bear on the ability of the fruit and vegetable processing
industry to make the required pricing adjustments.
This chapter will consider the following price-related factors;
1. Demand
2. Supply
3. Industry pricing processes
4. Processing and marketing margins
5. Anticipated price effects resulting from imposition of
effluent guidelines
A. Demand
The market for canned, frozen and otherwise preserved fruits and vegetables
includes five major segments of demand (1) consumers-served mainly through
retail food stores, (2) institutional food purveyors, (3) government pur-
chases, (4) secondary processors and (5) export markets. The importance of
each of these demand segments varies from product to product and from time
to time.
1. Trends in Demand
Demand for processed fruits and vegetables varies in both the long-run and
the short-run.
IV-1
-------
Long-run changes in demand result from gradual changes in dietary patterns,
consumer tastes and preferences, population growth, income changes and
changes in technological processes which affect the availability and/or
convenience of these foods.
Short-range changes in demand are more closely related to supply-price
related factors. In the case of fresh fruits and vegetables, seasonal
supply factors are major determinants of price and will vary substantially
within a production season. However, there is less short-run (intra-
seasonal) variation in the demand and price for processed fruits and vege-
tables since once the carryin and pack are established, the supply for
that period essentially is fixed.
Some indications of trends in consumption can be analyzed by evaluating
trends in (1) population, (2) per capita consumption, (3) government
purchases, (4) foreign trade and (5) total pack and carryover by major
product lines.
2. Per Capita Consumption
Patterns of consumption for fruits arid vegetal)! es have changed appreciably
during the past 20 years, in terms of product form and in terms of consume
of various products.
.ble^ "_P9ir_c_fti:!Jta_ S°nluJT!j)tl'on ~ Tah1e !V-1 shows civilian per capita
consumption of fresh '"canned ami frozen vegetables, on a processed weight
basis, for the period 1950-1974. Total per capita consumption of fresh
vegetables decreased from 115 pounds to 98 pounds during the period while
total processed consumption rose from 45 pounds to 79 pounds, a gain of
76 percent. Consumption of canned vegetables increased from 42.1 to 55.9
pounds, a gain of 33 percent and consumption of frozen vegetable" increased
from 3.4 pcunds to 23.2 pounds, a gain of 582 percent.
Consumption of commercially produced processed vegetables decreased during
1974. These changes are attributable to the recent consumer preference
for fresh vegetables which then are often preserved by the indivduals
at home. The recent popularity of home gardens also has had its influence-
on consumption of processed foods as more and more people are seeking the
sociological and economic benefits of growing their own vegetables.
These shifts in cnn.^mption reflect the changing patterns of family living
in the United State?,. Until 1974, the emphasis on convenience foocK was
reflected in the in.. 'eased consumption of both canned and frozen vegetables
and the increasing , -.pcrtance of "rozen vs. canned and fresh forms reflec1'
the greater ac.rpial. :1 i ty of f roz an vs. canned foods plus substantial impv
ments in home free.:.. 'S aiv refric 'rator-freezer combii., lions as well as
self-service free;; • counters in etail food stores. Preferences during
1974, howc-Y'. r, charged as fresh vegetables and home canning experienced
an increase in popularity.
I/-2
-------
Table IV-1. Commercially produced vegetables: Civilian
per capita consumption, United States, 1950-73
Processed wciqht basis
Year
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
Fresh--7
~ObsT
115.2
111.9
111.6
109.1
107.2
105.2
107
106.
103,
102.
105.8
103.7
101.3
101.2
98.6
Total
TTbTT
45.5
46.4
47.3
48.7
47.8
50.0
51.0
51.4
52.8
53.7
54.3
54.7
58.2
59.1
60.7
Canned
TTbTT
42.1
42.1
42.0
43.3
41.9
43.4
43.9
43.9
44.7
44.8
44.
44.
46.
47.
47.2
Frozen
TTbTT
3.4
4.3
5.3
5.4
5.9
6.6
7.3
7.5
8.1
8.9
9.8
10.0
11.3
11.6
13.5
1965
1966
1967
1968
1969
98.3
95.9
98.2
101
97
62.5
64.8
67.0
70.5
72.6
48.7
49.0
50.6
52.3
53.7
13.8
15.8
16.4
18.2
18.9
1970
1971
1972
1973
19742/
98.5
96.6
95.9
97.2
97.8
73.7
76.1
.77.4
81.2
79.1
52.9
54.3
55.2
57.2
55.9
20.8
21.8
22.2
24.0
23.2
I/
2/
Excludes melons. Data include pickles and sauerkraut in bulk; excludes
canned and frozen potatoes, canned sweet potatoes, canned baby foods,
and canned soups.
Preliminary.
— Source:
The Almanac of the Canning, Freezing and Preserving Industries,
1974 and the Vegetable Situation, ERS, USDA.
IV-3
-------
Table IV-2. Civilian per capita consumption - selected vegetables, by product form, 1950, 1960, 1965, 1970 and 1973-/
(Pounds)
\X:^-i
" " "•"> !"c
L i ~ i •:
X ~ T • . K
Cjrrct
Fr =, s
?.•• ?ki
s --;•-, 3 c
TV j '_c
B : e *_ s
Corn
r-;-jr,ie
3 : 'j s r k
S,.c-et
~ r-ii'-'o
C'jlif
Potato
Brccco
bl e
"US
:;n3
,1 J3 p C
s
n & squash
'^ fit
es—
s
raut
potatoes
Is sprouts )
lower )
)
" i )
Fr.
0.9
0.5
3. 9
8.8
0.7
1.7
12.9
1.1
7.7
_
_
12.9
0.1
3.0
105.0
1.0
1950
Can.
0.7
0.6
3.4
0.4
5.4
0.6
0.9
1.2
5.2
3.3
1.9
0.7
_
_
-
Froz.
0.12
0.51
0.35
0.03
0.86
0.06
0.38
_
_
0.21
_
-
0.09
0.09
0-.12
0.22
Fr.
0.7
0.4
2.6
7.3
,0.3
0.9
12.6
0.7
8.5
_
7.1
0.1
1.3
108.0
0.4
1 960
Can.
0.7
0.4
A. 2
0.6
4.4
0.7
0.9
17.6
1.3
5.3
4.5
1.5
0.9
_
_.
-
"
Fr
0.
0.
0.
0.
1.
0.
0.
_
_
0.
_
-
-
0.
0.
2.
0.
02.
21
73
76
35
75
11
55
64
19
19
68
63
Fr.
0.6
0.3
.0
7.0
0.2
_
0.6
12.0
0.5
8.1
-
-
6.2
0.1
1.0
-
0.3
1965
Can.
0.8
0.3
4.8
0.6
4.1
0.5
0.8
18.9
1.4
5.5
6.2
1.4
1.2
_
-
-
~
Froz.
0.15
0.69
0.91
0.51 '
1.98
0.07
0.62
-
-
1.13
-
-
-
0.22
0.20
5.72
0.68
Fr.
0.5
3/
1.7
6.6
3/
-
0.3
12.2
3/
7.2
-
-
5.6
2/
0.8
118.0
0.4
1970
Can.
0.7
0.4
5.8
0.6
3.9
0.5
0.8
15.2
1.5
5.9
7.4
1.5
1.2
-
-
-
Froz.
0.14
0.71
1.05
0.77
1.86
0.13
0.68
-
-
1.61
-
-
-
0.22
0.30
11.11
0.82
Fr.
0.4
3/
1.5
6.6
3/
-
0.5
12.5
3/
8.1
-
-
5.2
21
0.7
119.0
0.5
1973
Can.
0.6
0.3
5.9
0.6
4.3
0.7
0.9
15.8
1.3
6.4
8.0
1.4
1.3
-
-
-
Fro;
o.i:
0.6C
1 1 f
1 . i °
0.9?
1.7?
O.U
0.5;
-
-
1.57
-
-
-
0.23
0.3?
13.26
1.06
1 /
Source: Agn'cultural Statisties, USDA. fresh en a fresh equivalent basis, canned.
— Less than 0.05 pound.
— S~all arrount-rincluded in minor vegetables.
— Including canned whole tomatoes and tomato products other than soup.
-------
These changes have been largely the result of changes in life styles toward
more convenience foods and toward less formal, less heavy meals. The de--
crease in consumption of lima beans reflects in part a shift away from
starchy foods, but also reflects the relatively high cost of limas to the
consumer. The increase in tomatoes and tomato products in recent years
has been primarily in the tomato product category especially catsup and
tomato paste and sauce. The increasing popularity of pizza and other tomato,
starch, cheese products (Italian foods) was a major factor affecting this
change. The substantial increase in pickle consumption is associated
with a change toward sandwich meals and also with the affluence of the
American consumer. In general, rates of change have slowed during the
period since 1967.
Changes in fro/en vegetable use, 1950-1973, have been substantial and have
been associated with improvements in freezing techniques and rrw frozen
pioduct forms, with improvements in home freezers and refrigerators and
with the increasing demand for convenience foods. Changes in consumption
leveled off during the period 1967 to 1973 as frozen veyetables found
their place in the consumers diet and as major technological changes in
processing and display of frozen foods had been completed.
1967-1973
1950-1973 Annual Average
Total Change ate> f Chane
Asparagus - 8 -8.7
Lima Beans +35 -1 .1
Snap beans +226 +3.3
Carrots +1,138 +5.5
Peas +105 -1.7
Pumpkin ft squash +167 +4.3
Spinach ' +76 +0.1
Corn +648 -0,6
Brussels Sprouts +156 +2.0
Cauliflower +311 +6.. 8
Potato products +10,950 +9.9
Broccoli +382 +5.4
In terms of pounds consumed, potatoes (13.3 Ibs.), corn (1.5 1bs.) and
peas (1.8 Ibs.) are the major commodities. The substantial increase shown
for frozen carrots results from the high use of frozen carrots and peas
and mixed vegetables. The gain in potatoes is almost entirely in frozen
french fries and again a substantial increase was seen in consumption of
pumpkin and squash.
IV-6
-------
. IeJl_cJLl:li4uL ^ojnsj^nrrtKm - Civilian per capita consumption of fresh
canned, frozen and. di iecl fruits and juices, 1950-1973, is shown in Table
IV-3. Significant trends in consumption are seen:
. A continuing decrease in per capita consumption of fresh
fruits
. A constant per capita consumption of canned fruits
A gradual increase in per caoita consumption of canned arid
chilled juices with most of the increase being in chilled
juices
A substantial and continuing increase in per capita consumption
of frozen fruits and juices with 88 percent of this increase
being in consumption of frozen citrus juices.
Fresh fruit - per capita consumption changes (Table IV-4) were:
1950-1973 1967-1973
Total Annual Average
Fresh Product _Ch_aj!9j? _ Rates of Change
Percent Percent
Citrus fruit -37 -1.2
Apples -36 -0.2
Apricots -78 -2.9
Cherries 0 +1.9
Cranberries -37 +3.8
Grapes -56 -8.6
Peaches -55 +5.0
Pears -40 +4.2
Pineapples +80 +10.1
Plies & prunes -37 -1.4
Strawberries +7 +0.6
All fresh fruit -32 ' -0.8
Although overall consumotion of fresh fruit from 1950 to 1973 was down
appreciably, the consumotion of many of the fruits has increased from 1967
to 1973 as a result of greater availability in retail food stores pri-
marily associated with improvements in production and harvesting techniques
as well as improvements in transportation from producing areas.
Canned fruit and juices - per capita consumption changes were:
1950-1973 1967-1973
Total Average Annual
Canned Product Change Rates of Change
Percent Percent
Apples & applesauce +42 -0.9
Apricots -37 -2.4
Cherries -56 +0.4
Fruit cocktail +15 0
IV-7
-------
Table IV-3. Processed fruits: per capita civilian consumption,
United Stoles, 1950-74
Processed Weight Basis
Year
1950
195]
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1957
1963
1969
1970
1971
1972
1973
1974
Source:
I/ Ann"
Fresh , , Canned and ~, 37
fruits Canned fruits-7 chilled -juices- Dried fruits—
Obs.l
108.8
118.0
114.4
109.4
105.1
99.4
98.9
96.7
94.0
95.7
93.4
88.6
83.4
74.5
78.3
81.1
81.5
81.0
78.2
78.7
81.2
79.8
77.1
75.6
80.0
: The Aln:~.n-tc
IPS. 3 P n 1 p r, A i ; r
(Ibs.)
21.6
19.0
20.8
21.0
21.2
22.5
21.9
22.6
22.9
22.3
22.6
23.6
23.2
23.3
23.0
23.8
22.9
22.6
2J.9
24.2
23.3
21,°
2i.4
21.3
19.4
of the Canning,
p> ,inr i rnt '; hrri
ObsT)
13.5
15.0
14.1
13.4
13.2
12.0
14.8
15.6
1.6.1
14.0
15.1
13.4
14.0
14.2
12.9
12.9
14.9
16.1
16.4
19.3
19.4
20.7
20.8
21.6
19.8
Freezing and
Hoc rhorrip'
(Ibs.)
4.1
3.8
3.8
3.8
3.9
3.6
3.7
3.6
3.0
3.2
3.1
3.1'
3.0
2.9
2.9
3.0
3.0
2.8
2.8
2.7
2.7
2.6
2.1
2.8
3.0
Preserving Industries
; HnrliiHinn h r i n p H ^
4/
Frozen fruits—
and juices
(Ibs.)
4.3
4.8
6.6
7.1
7.4
8.7
8.8
9.0
7.9
8.8
9.1
8.8
9.7
8.0
7.4
8.5
8.1
10.1
9.4
9.3
9.8
10.2
10.2
11.2
11.9
, 1974.
r r ri n h o r r i p s .
Total
pro-
cessed
(ibsTT
43.5
42.6
45.3
45.3
45.7
59.8
49.2
50.8
49.9
48.3
49.9
48.9
49.9
48.4
46.6
48.2
43.9
51.6
50.5
55.5
55.2
r r" ft
54.4
56.9
54.1
fiqs, fruit cod.util and salad, citrus sections, olives (including brinua), pine--
apple, plums, prunes, peaciies (including spiced), and pears.
— Grapefruit, oranqe, blended citrus, lemon and lirne, tangerine and blends, pine-
apple, apple, gnine, and p>~-j"r -juices, and fruit nectars. Including conned con-
centrated citrus juices convened to s ing Ir-strength basis but excUHes ?il i rozen
juices.
3/
— Pricv apples, apricots, dates, ^iqs, peaches, pears, prunes, and raisin'^. Excludes
unirL; chontt bl'j ii>,'., _
-------
Table IV-4. Civilian per capita consumption, selected fruits ar\d fruit juices, by product form, 1950, 1962,
1966, 1970 and 1973 (pounds-processed cwt.)
Fruit
Fr.
/-pples a applesauce 22.2
Apricots
Oi" rries
Fruit cocktail
P. :••'.: he s
Fears
P", nerjDle
PI IT'S
-------
1950-1973 1967-1973
Total Average Annual
Canned Product (con'd) Change _ fortes_pf_Cha_nue
Percent ' Percent
Peaches -17 -3.1
Pears +38 +4.5
Pineapple +17 +0.5
Plum & prunes -50 -10.0
Olives -13 -3.6
Grape juice +22 -0.2
Citrus juices +49 +13.4
Apple juice +395 +10.4
Pineapple juice +75 -0.6
Prune juice +8 -1.6
The increases shown in consumption of canned fruits are largely related to
the demand for convenience foods. The decreases in canned apricots,
cherries, plums and prunes are related to changing tastes while the de-
crease in olive consumption is primarily price related. A general in-
crease in canned juice consumption is seen with the substantial increase
in apple juice related to increased use of apple juice for infants and
young children. In recent years (1967-1973), the trend toward increased
consumption of canned juices has continued strong with less change noted
in consumption of canned fruit items.
Frozen fruits and juices - overall per capita consumption increased by 160
percent, 1950 to 1973, with the principal changes as follows:
1950-1973 1967-1973
Total Averaqe Annual
Frozen Product Change Rate s _of_Chance
Percent Percent
Apples & applesauce +114 +3.7
Apricots +33 -5.5
Cherries +37 +6.4
Peacht,, +44 -2.4
Strawberries +34 -2.0
Other berries -33 -9.9
Grape juice -80 -23.5
Citrus juice +403 +4.6
The principal change in por capita consumption of frozen fruits and juices
between 1950 and 1973 was the substantial (403"') increase in consumption
of frozen citrus juices, of which frozen concentrated nranne juice accounts
for 9? percent of total consumption- With the exception of cherries, per
capita consumption tended to level off curing the period 1967 to 1973.
IV-10
-------
This may be partially due to the establishment of frozen fruits and
juices in a place in consumer's tastes and preferences as well as a
leveling off of the increasing consumption trend as advances in freezing
and frozen retail display technology have been achieved.
Dried fruits - per capita consumption of dried fruits has generally
decreased since 1950. However since 1967, the declines in consumption
have slowed down; and, for dried dates and pears, consumption has
actually increased. Specific changes were as follows:
1950-1973 1967-1973
Total Average Annual
Dried Prodjci_ _01l§JL(!§ Rates J}f_JLh
Percent Percent
Apples +17 -1.9
Apricots -58 0
Dates -38 +4.3
Figs -38 -5.1
Peaches -82 -2.3
Pears -22 +23.9
Prunes -40 -1.5
Raisins & currants -39 -7.1
3. Go ye rnnie n f Pure h a s e s
Government purchases of canned and frozen fruits and vegetables include
purchases for four major uses:
. Military
Veterans Administration
Child Nutrition Program
Needy Family Program
Purchases for these purposes, 1966-1973, are shown in Table IV-5 (canned
products) and IV-6 (frozen products). Military purchases in relation
to total government purchases were as follows:
Percent to Military
Product 1966 ' 1_973^
T
>
Canned vegetables 77 44
Canned fruits 67 32
Canned juices 91 53
Frozen vegetables 100 71
Frozen fruits 100 97
Frozen juices 77 37
IV-11
-------
Table IV-5. Government purchases of canned fruits, vegetables
and juices, 1966-1973
Year
1966
1967
1968
1969
1970
1971
1972
1973
Source:
All Vegetables
000/Cases
24/303
16,437
16,355
12,475
18,302
13,167
11,101
11 ,562
6,346
The Almanac of the Canning
1974.
All Fruits
000/Cases
23/2 1/2
6,337
9,621
5,300
5,574
7,142
6,128
6,533
3,983
, Freezing and
All Juices
000/Cases
24/2
4,409
9,101
3,272
8,218
8,050
7,759
6,673
4,735
Preserving Industries,
Table 1V-6.
Government purchases of frozen fruits, vegetables and
juices, 1966-1973
Year
1966
1967
1968
1969
1970
1971
1972
1973
Frozen Vegetables
(000 Ibs.)
67,981
79,241
72,592
80,270
83,865
73,260
91,591
100,798
Frozen Fruits
(000 Ibs.y
24,895
25,930
23,883
20,588
19,227
14,709
9,693
9,164
Frozen Juices
(000 Ibs.)
31 ,592
142,966
18,750
22,3^9
31 ,161
35,862
13,550
40,817
Source: The Almanac of the Canning, Freezing and Preserving Industries,
1974.
IV-K
-------
The substantial increases in frozen vegetable purchases in 1972 and 1973
were the result of ourchase of 23 and 25 million pounds of frozen French
fried potatoes for the child nutrition program. The very large frozen
juices purchased in 1967 resulted from the purchase of 4,943,000 cases
(basis 12/32 oz) of frozen orange concentrate for the child nutrition pro-
gram. Other irajor purchases of frozen orange concentrate for child
nutrition and/or Veterans Administration were made in 1966, 1970, 1971
and 1973.
In relation to total pack, government purchases in 1973 were approximately
as follows:
Percent Gov't. Purchases
Product Here of Totaack __
Canned vegetables 2.1
Canned fruits 4.5
Canned juices 6.8
Frozen vegetables 2.0
Frozen fruits 1.4
Frozen juices 2.7
Thus, it is seen that in most years government purchases are not a major
factor affecting demand for processed fruits and vegetables. Further-
more, the- rectnt trend of smaller military forces will reduce, even
further, the influence of government purchases on the total demand for
processed fruits and vegetables.
4_. _ Exports
Exports of canned fruits have remained relatively constant since 1967
in the range of 350 to 400 million pounds (Table IV-7). Exports of canned
vegetables had also been relatively steady in the 85 to 105 million pound
range until 1973 whan 181.5 million pounds were exported. Major increases
in exports of canned corn and tomatoes and tomato products accounted for
most of the increase in vegetable exports in 1972-73. Canned juice ex-
ports have reiiiained steady~since 1967 within a range of 28-33 million
gallons. Exports of frozen juices, led by frozen orang concentrate,
gained steadily in the 1967-73 period from 5.4 million gallons in 1967
to 13.8 million gallons in 1973. Exports of frozen fruits and vegetables
were~steady in the range of 30-36 million pounds until 1972-73 when exports
doubled to 65.1 million pounds with most of the increase being in exports
of frozen vegetables.
IV-13
-------
le YI-7, Export volume, processed fruits and vegetables, general categories, 1967-1973
Export Volume
iuu*. ~
Canned fruits
Canned vegetables
Banned juice
" r-.z. :• juices
Frc:-jn fruits
r. "d vegetables
I'ni
(000
(000
(000
(000
(000
£
Ibs)
Ibs)
gal)
gal)
Ibs)
1-967
354,809
100,251
33,115
5,419
32,377
1 968
302
89
29
5
32
,234
,764
,992
,162
,276
1969
439,990
107,384
28,199
5,437
.34,351
1970
396,261
102,587
32,135
7,815
30,342
197
321,
84,
28,
9,
24,
-\
850
717
515
641
036
1972
376,238
103,842
28,568
10,462
36,493
1973
374,505
181 ,515
32,706
13,825
65,129
;o.,rce: Division of Statistics, National Canners Association.
-------
In relation to total pack, exports were as follows:
Kern ' % of 1973 P.-ck
Canned vegetables 2.2
Canned fruits 9.7
Canned juices 12.1
Frozen fruits and vegetables 1.1
Frozen juices 6.9
These data indicate that exports are relatively important for canned juices,
canned fruits and frozen juices, but are of little significance for canned
vegetables and frozen fruits and vegetables.
Table IV-8 shows exports of major canned and frozen fruits and juices, 1970-
1973 and major importing countries. The major canned fruits exported are,
in order of importance, canned peaches, fruit cocktail and pineapple. No
major trend in exports of canned fruits is evidenced in the past four years.
Major markets are Canada and Western Europe.
Exports of canned fruit juices go mainly to Canada and Western Europe and
are dominated by canned (hot pack) citrus juices which account for 50 per-
cent of total canned juice exports. Canada, Sweden and Western Europe are
the principal export markets. Canned tomato juice exports go primarily to
Canada, Japan and Saudi Arabia and it is expected that exports to Arab
countries may continue to increase.
Frozen citrus concentrated juices dominate frozen juice exports, accounting
for 91 percent of the total in 1973 with frozen orange concentrate repre-
senting 80 percent. Canada, Sweden, Western Europe and Australia are the
major markets.
Exports of canned vegetables and frozen fruits and vegetables are shown
in Table IV-9. An increasing trend is shown in exports of canned vege-
tables, with the greatest increases in tomatoes and tomato products, corn
and baked beans. Canada, l.'estern Europe and Japan are the principal
markets. Amounts shown, while substantial in total, represent only a small
part (2.2 percent) of the U.S. pack and the export market does not exceed
4 percent of the total pack for any major canned vegetable item. Exports
of frozen fruits and vegetables were up sharply in 1973 but still repre-
sent only 1.1 percent of total pack. Principal markets are Western Europe,
United Kingdom, Scandanavian countries and Australia.
5. fJemand Characteristics
The ability of processors to pass forward increased costs, associated with
pollution controls, to the consumer will be dependent in part on four demand
characteristics.
IV-15
-------
Table IV-8. . Exports of major, canned and frozen fruits and juices, 1970-1973
% of
Pro duct 1970 1971 1972 1973 pa ex Major countries
(000 Ibs) (197,
Peaches 165,573 137,811 134,159 118,087 11.4 W. Germany
Canada
Switzerland
Bel gi urn-Luxembourg
Sweden
Netherlands
Austria
" , i: r .'.-•: 108, 773 76,832 92,738 109,140 19.2 Canada
k. Germany
Bel gi urn-Luxembourg
Pineapple 68,648 63,321 71,310 78,764 10.2 W. Germany
Bel gi um-Luxenbourg
France
Canada
Netherlands
Switzerland
"cars 8,743 10,109 13,047 9,239 2.2 W. Germany
Canada
Other 44,524 33,777
Total canned fruits 395,261 321,350 376,238 374, 5C5 9.7
Craned JU^'CGS - call ens
;' I
^ v- 3 n o
3,740 3,051 2,693 3,026 4.5 Canada
fr_, ,t, sinnle strength
anc concert ' 6,358 5,2^9 5,257 5,294 3.5 Canada
e, 'Png.e str. and cone. 14,249 11,935 10,115 11,607 12.5 Canada
France
W. Germany
continued
-------
Table IV-8. Exports of major canned and frozen fruits and juices, 1970-1973 (continued)
Product IP/0
_Canned_j u_i_ces ( conti nued )
"(gallons)
Tomato 1,589
Other 6,190
Total canned juices 32,135
Frozen juices
Orange, frozen and concen. 6,097
Grapefruit, frozen and concen. 939
Other - 779
Total frozen juices 7,815
1971 1972
1,461 1,592
6,850 8,910
28,516 28,568
7,839 8,335
998 1,101
804 1 ,026
9,641- 10,462
% of
1973 pack
(1973)
2,536 2.5
10,243
32,706 12.1
11,093 6.3
1,428 16.5
1,304
13,825 6.9
Major countries
Japan
Saudi Arabia
Canada
Canada
Sweden
United Kingdom
W. Germany
Canada
Australia
W. Germany
Source: The Almanac of the Canning, Freezing and Preserving Industries, 1974.
-------
Table IV-9. Exports of major canned vegetables and frozen fruits and vegetables, 1970-1973
Product
Canned vegetables
Tomatoes & tomato products
Corn
Asparagus
Dry beans, baked and other
Cther
Total canned vegetables
rozen Bruits & vegetables (all)
1970
40,608
15,574
7.485
7,638
31,281
102,587
30,342
1971
( n n n
34,758
14,740
4,484
4,893
25,842
84,717
24,036
1972
1 kc \
42,864
20,372
3,822
6,528
30,256
103,842
36,493
1973
77,984
51,611
4,053
11,743
36,124
181,515
65,129
% of
pack
9/3)
3.2
3.9
2.9
0.7
-
2.2
1.1
Major countries
Canada
Japan
Hong Kong
Sweden
W. Germany
,- ranee
Nigeria
Switzerland
Dominican Republic
United Kingdom
Bel gium-Luxembbourg
Canada
United Kingdom
Denmark
Sweden
Bermuda
Australia
W. Germany
Sou
The Almanac of the Canning, Freezing and Preserving Industries, 1974
-------
a. The relative importance of the food item in terms of total food
expenditures.
b. The price elasticity of the consumer's demand for the product in
question as indicated by demand response relative to a given price
change.
c. The income elasticity of the consumer's demand, i.e. changes in
demand associated with changes in income.
d. The cross-elasticity of demand, representative of the demand inter-
relationships between a specific product and substitutes.
The analysis of demand characteristics is a complex process and is, at best,
approximate only. It becomes particularly complex when interrelationships
among commodities are considered and where changes in demand characteristics
over time are important.
Partly because of the complexity of this subject, there are relatively
few studies available. The most recent, comprehensive study was completed
in June, 1970 and published in March, 1971. This study "Consumer Demand
for Food Commodities in the United States, with Projections for 1980" was
the result of work by Drs. P. S. George and G. A. King and was published
by the California Agricultural Experiment Station as Giannini Foundation
Monograph 26.
The study analyzes the demand for food commodities in the United States
in the postwar period using both time-series and cross-section data. Income-
consumption relationships are based on data from the 1955 and 1965 USDA house-
hold food consumption surveys.
The analysis of cross-section data emphasized: (1) effects of grouping
observations, (2) choice between expenditures and quantities as the de-
pendent variable, (3) effects of household size on income-consumption re-
lationships, (4) shifts in the regression ct .:fficients (intercepts and in-
come elasticities) between 1955 and 1965, and (5) regional variations in the
income-consumption relatipnships.
A demand interrelationship matrix was developed for 49 commodities or com-
modity groups at the retail level. Commodities were classified into 15
separable groups and all direct and cross elasticities for commodities
within a group were estimated directly. The cross elasticities corres-
ponding to commodities outside a given group were estimated through assump-
tions of cardinal separability. The synthesis of demand interrelationships
was achieved by the use of restrictions on demand equations for an individual
consumer as suggested by Frisch (1959) and quantified by Brandow (1961).
Consideration also was given to the measurement of time trends on consumption,
Marketing margins were analyzed and demand interrelationships were developed
at the farm level.
Projections of 1980 consumption per capita were developed for individual
commodities and group aggregates. These projections are based on a specifi-
cation of constant real prices, exogenous projections of real income per
capita, and continuation of past time trends for certain commodities.
IV-19
-------
a. Fruit and Vegetable Expenditures in Relation to Food and Total Expenditures
The relative importance of consumer expenditures for fruits and vegetables as
a percentage of total food expenditures and expenditures for all purposes is
shown in Table IV-10. These data are based on major food consumption surveys
conducted by the USDA in 1955 and 1965. The data show that in terms of rela-
tive importance of expenditures, fruits and vegetables are essentially equal,
each representing approximately eight, percent of total food expenditures and
1.9 percent of total consumer expenditures. As a group, expenditures on
fruits and vegetables were approximately equal to expenditures on dairy pro-
ducts and cereal and bakery products, but were only half as important as meat
expenditures. When compared to similar estimates made by Brandow-- in
1961, these data show that fruits had held their relative importance,
but vegetables had decreased slightly in relative importance during the
ten year period.
Within the general "fruit" category, processed fruits accounted for 41 per-
cent of total expenditures and within the general "vegetable" category,
processed vegetables accounted for £.9 percent of total expenditure0,, in-
dicating that relative expenditures for processed vegetables were slightly
greater than for processed fruits.
Considering increases in per capita consumption of processed fruits and
vegetables and increased costs of processing which have occurred in the
last ten years, it is probable that the relative importance of expenditures
for processed fruits and vegetables vs. fresh products has increased.
b. Demand Elasticity
Three typos of demand elasticity are relevant to the question of the ability
of processors to pass increased costs forward to consumers in terms of
higher prices: (1) price elasticity, (2) cross elasticity and (3) income
elasticity. Again, definitive studies on demand elasticity are limited,
and the basis for these elasticities is the George and King study described
under section (a) of this Chapter. Table IV-11 shows demand and income
elasticities for selected processed fruits and vegetables.
(1) Price-elasticity is shown by the underscored coefficients in the
table. The coefficient shows the percentage change in quantity
taken in response to a one percent change in price. All coefficients
are negative indicating that an increase in price will induce a
— Brandow, George h., "Interrelations Among Demands for Farm Products and
Implications for Control of Market Supply," Pennsylvania Aqr. Exp. Sta.
Bui. 680, 1961 .
IV-20
-------
Table IV-10. Fruit and vegetable expenditures as a proportion of
retail food and total expenditures
Commodity
Fruit
Fresh
Canned
Frozen
Dried
Total Fruit
Vegetables (ex. potatoes)
Fresh
Canned
Frozen
Dried
Total Vegetables
Meats, Poultry and Fish
Dairy Products
Cereal and Bakery Products
Other Food Products
Total all Food
Total Nonfood
Proportions expressed
Food Expenditures
4.85
2.22
.75
.37
8.19
4.27
3.00
.75
.37
8.39 •
33.85
15.35
14.62
19.60
100.0
-
as a percentaqe of
All Expenditures
1.10
.51
.17
.09
1.87
.97
.68
.17
.09
1.91
7.72
3.50
3.33
4.46
22.79
77.21
Source: George, P. S. and G. A. King, "Consumer Demand for Food Commodities
in the United States with Projections for J930," California Agri-
cultural Experiment Station, Giannini Foundation Monograph
Number 26, March, 1971.
IV-21
-------
Table IV- 11 . Selected fruit and vegetable demand and income elasticities
Selectea Canned
Fruits
Frozen 'Dried
Fruits Fruits
"^roze
"^ ried
o c -L ._ •_ .
?,- V e (-•
n Fruits - 1 <
Fruits
i d Canr-d Fruits
:hes
"T, '^ ° ?
t \ egetabies
r-r 3 se tables
O
ed Canned Vege:
atoes
Canned Fruits
e tables
0.
0079
0184
0011
Cui
003
004
003
0005
003
.003
.0641
.0000
-.0001
.0002
.00006
.0003
.00006
.0001
Peache^
.013
. 106
-.759
/155
-. 00004
.001
.001
.001
.001
.001
1-' .e- Frozen
apple Vege.
,0005
.0001
. 125
-.826
.000005
.0003
.0005
.0003
.0005
.0003
.0009
.0001
.0004
.00002
-1.03
.015
.016
.015
.016
.015
Dried
Vege.
. 001
.0001
.0005
.00003
.007
-.48
.059
.00003
.014
.0004
Selected Canned
Vegetables
Corn
„ 002
.0003
.0009
.00006
.010
.078
-.255
.00000
.047
.0004
Tomatoes
.001
.0001
.0005
.00003
.007
.00000
.00001
-. 176
.033
.0002
Peas
.002
.0003
.001
.00007
.012
.024
.059
.056
-. 185
.0006
Other
Canned
Fruits &
Vege.
.009
.0003
.001
.00007
.002
.0003
.003
.001
.003
-.40
In corn •
.651
.315
.341
.447
.616
.217
.025
.173
.032
.200
rce: George, ?. S. and G. A. King, "Consumer uernand for Food Commodities in the United States with Projections for
1980," California Agricultural Experiment Station, Giannini Foundation Monograph Number 26, March, 1971.
-------
decrease in quantity demanded by consumers. A coefficient of -1.0
(e.g. frozen fruits) indicates that the quantity demanded varies
proportionately to the change in price—unit elasticity. A co-
efficient of greater than -1.0 (e.g. frozen vegetables, -1.03)
indicates that the quantity demanded varies proportionately at a
greater rate than the change in price—an elastic demand. A co-
efficient of less than one (e.g. canned tomatoes, -.176) indicates
that the quantity taken varies proportionately at a lower rate than
the change in price—an inelastic demand.
It is important to note that, with the exception of frozen fruits
and frozen vegetables, the processed fruits and vegetables shown
in this table have relatively inelastic demands. In order of
elasticity, the products shown are:
Item Elasticity coefficient Elasticity 'type
Frozen vegetables -1.03 Slightly elastic
Frozen fruits -1.00 Unit elasticity
Canned pineapple -.826 Slightly inelastic
Canned peaches -.759 Slightly inelastic
Dried fruits -.650 Moderately inelastic
Dried vegetables -.480 Moderately inelastic
Canned corn -.255 Inelastic
Canned peas -..185 Inelastic
Canned tomatoes -.176 Inelastic
As seen from these data, the demand for dried products is more
inelastic than that for frozen products and the demand for canned
products is more inelastic than that for either the frozen or
dried forms. Also, the demand for vegetables tends to be more in-
elastic than that for fruits. For products with an inelastic
demand, an increase in price will result in less than proportion-
ate decreases in total revenues. As a result, based on demand
elasticity alone, the opportunities to pass forward increased
costs as higher prices should be greater for products .with an in-
elastic demand.
(2) Cross-elasticities are shown in Table IV-11 by the coefficients
(other than those underscored) under each commodity. For example,
the coefficient of cross-elasticity between canned peaches and
canned pineapple is .155 indicating that for a one percent in-
crease in the price of canned peaches, there would be a 0.155
percent increase in the demand for canned pineapples. In general,
the higher the cross-elasticity coefficient, the closer the sub-
stitute relationship between the two products, A cross-elasticity
of 1.0 would indicate perfect substitutes. As seen from Table VI-11,
substitution relationships between fruits and vegetables and between
canned, frozen and dried forms are not very close. This means that
there would be relatively minor shifts between products or product
forms as the result of a price increase associated with attempts
to pass on increased costs of effluent abatement.
IV-23
-------
(3) Income elasticity - Income elasticity of demand reflects the pro-
portionate change in quantity demanded of a specific product in
relation to a proportionate change in incomes of buyers. Income
elasticity coefficients are shown in the last column of Table IV-11.
In general, the higher the coefficient, the more responsive is the
demand to a change in income. All food products, as a group, have
an income elasticity coefficient of .176 indicating that expenditures
for food, in total, are relatively unresponsive to changes in income.
For those processed fruit and vegetable products listed, the follow-
ing situation existed:
Product
Frozen
Frozen
Canned
Canned
Dried
fruits
vegetables
pineapples
peaches
fruits
Dried vegetables
Canned tomatoes
Canned peas
Canned corn
Coefficient
.661
.616
.447
.341
.315
.217
.173
.032
.023
Income Elasticity Relative
to all Food Products (1.176)
High
High
High
Slightly
Slightly
Slightly
Average
Low
Low
nigher
higher
higher
B. Supply
The supply of processed fruits and vegetables consists of three parts:
(1) current domestic pack, (2) carry-in stocks and (3) imports. In the
long run, this supply is essentially equal to total demand since the entire
supply eventually is consumed. In the short run, supplies and demand do
not balance exactly and this imbalance is reflected in the variations which
exist in carry-in volumes, i.e.', that volume of processed product which has
not been sold by the beginning of a new pack season and is "carried in" as
a part of the total supply for the coming year.
1. Pack
Pack data are
year's crop.
representative of the processing volume from the current
These data show the volume of pack for major commodities in
standardized cases. Analysis of pack data shows the relative importance
of the various commodities and trends in recent years. Data are given for
the period 1969-70 through 1973-74. Canned pack statistics are from the
Nft^nal Canners Association, frozen pack data are from the American Frozen
Fooa Institute.
IV-24
-------
Canned vegetable packs are shown in Table IV-12.
These data show the following dominant products:
1973-74 Pack Percent
Product (OOP cases) of Total
Tomatoes and tomato products 101,553 31.4
Sweet corn 55,228 17.'
Green beans 50,887 15.7
Green peas 29,558 9.1
Total, 4 commodities 237,226 73.3
Other products with packs above five million cases are: sauerkraut, beets,
sweet potatoes, spinach, asparagus, lima beans, carrots and white potatoes.
These eight products accounted for 60,225,000 cases in 1973-74 or 18.6 per-
cent. This, plus the 73.3 percent represented by the four major commodities,
totals 91.9 percent, leaving 8.1 percent of the total pack to be accounted
for by all other canned vegetables.
One product not listed on the preceding table but yet is considered one
of the more dominant products is dry beans which on the 1972-73 season
had 68 million cases canned.
Trends in volume of pack during the past five years are as follows:
Up strongly Up moderately Steady Down__m_odGrate1y
Tomatoes Green beans Green peas Sweet potatoes
Sweet corn Carrots Beets
Spinach Wax b°ans Sauerkraut
Mushrooms M--xed vegetables Asparagus
Leafy greens Pumpkin and squash
Field peas Lima beans
Carrots and peas
Pimentos
Okra
Succotash
Canned fruit packs are shown in Table IV-13.
Dominant products are as follows:
Product Pack, 1973-74 (OOP cases) Percent of Total
Peaches 24,473 25.2
Applesauce 15,166 15.6
Pineapple 14,981 15.4
Fruit cocktail 13,384 13.8
Pears • 9,813 10.2
Total - 5 fruits 77,817 80.2
IV-25
-------
Table IV-12. Summary of canned vegetable packs, 1969-1974-
l\3
cn
Pack, 000 Cases
Product
Tomatoes & tomato products - total
Tomatoes, whole peeled
Tomato juice
Tomato catsup
Tomato chili sauce
Tomato puree
Corn, Sweet
Beans, Green
Peas, Green
Potatoes, Sweet
Beets
Sauerkraut
Asparagus
Spinach
Potatoes, White
Carrots
Pumpkin and Squash
Beans, Wax
Mixed Vegetables
Beans, Lima
Leafy greens
Peas, field
Carrots and Peas
Mushrooms
Pimentos
Okra and Tomatoes
Succotash ,
Okra
Total
— Source: Division of Statistics,
— Includes only No. 10's or -larger.
— 1970 pack, data not available for
-/ 1958 pack.
— ^ 1972 pack, data not available for
— ' 1972 pack, data not available for
1959-70
82,387
32,036
33,653-,
8,019^
1,665
7,014
49,387
42,481
32,071
21,499
11,339
10,569
6,817
6,577
6,110
5,463
5,244
4,858
4,357
3,596
3,440
2,946
2,438,,
2,032-x
876
475
383
368
296,714
National Canners
1971-72.
1971 & 1973.
1973.
1970-71
91,131
39,017
35,952-,
8,711-'
1,504
5,947
46,995
43,189
23,697
9,846
11 ,310
12,088
5,972
7,270
6,602
5,338
3,973
4,382
4,367
2,776
3,527
2,393
2,086A/
2,032^
627
348
339
443
295,781
Association
24/303 cans
1971-72
98,218
38,367
38,4117/
12,134^
1,462
7,844
53,757
45,213
33,137
10,056
10,430
11 ,266
5,542
7,675
7,849
5,310
-f ,581
4,797
4,482
3,116
4,443
2,742
2,1055/
3,637-'
738
378
338
355
320,226
1972-73
95,987
43,301
31,074,,
10,161-'
1,746
9,705
52,957
44,383
35,081
9,461
10,021
10,008
5,848
8,255
5,022
5,529
4,064
3,173
4,135
2,116
2,776
2,637
2,001,,
3,636-'
650
326
331
261
306,653
Estimated 1973-74
101,553
45,431
33,9367,
10,528^-'
1,763
9,895
55,223
50,887
29,558
9'461fy
1 0,021-F-y
10,008-'
5,794
8,944
5,022f'
5,529^
4,632
4,115
5,891
3,150
4,029
2,817
2,186,,
3,637-'
269
264
400
283
323,678
-------
Other important canned fruits are apricots and cranberry sauce, total pack
of these two products, 1973-74 was 8,807,000 cases or 9.1 percent of total
pack. Thus, these seven fruits accounted for 89.3 percent of the total
canned fruit pack.
There has been a slight decline in the volume of canned fruit packed over
the past five years but no real trend is evident.
Canned fruit juice packs are also shown in Table IV-13. Grapefruit, pine-
apple, apple and orange are all major pack items with packs in excess of
14 million cases. All packs shown- are hot-pack, single-strength equivalent
basis.
There appears to be a slight decline in the pack of canned pineapple juice,
but other canned juices have maintained their volume over the past five
years.
Frpzen vegetab1e packs, 1969-70 through 1973-74 are shown in Table IV-14.
These data show the dominant position (in terms of pounds frozen) of
potatoes, which accounted for over 50 percent of the total frozen vegetable
pack in 1973-74. Other major commodities are as follows:
Product 1973-74 Pack (OOP Ibs.) Percent of Total
Peas 387,749 7.5
Corn, cut 294,223 5.7
Beans, green and wax 290,861 5.6
Carrots 231,688 4.5
Broccol i 213,165 JL_2_
Total - 5 products 1,417,686 27.5
These five products, plus frozen potato products account for 79.7 percent
of the total pack of frozen vegetables. The trend in the pack of frozen
begetables over the past five years is definitely upward, increasing by
32 percent.
The relative changes in frozen pack 1969-1973 were as follows:
Up strongly Up moderately Steady Decrc-"-re_
Corn-on-cob Beans, lima baby Corn, cut Beans, lima, Fordhook
Carrots Potato products Peas, green Mixed vegetables
Spinach Cauliflower
Beans, green & wax Broccoli
Brussels sprouts
IV-27
-------
Table IV-13. Summary of canned fruit and fruit juice packs, 1969-1973—
Pack (000 cases - basis 24/2'2)
FRUITS
Apples (b)
Applesauce
Apricots
Blackberries
Blueberries (a)
Boysenberries (d)
Raspberries
Strawberries
RSP Cherries
Sweet Cherries
Cranberries (b)
Figs (c)
Frt. Cocktail (c)
Fruit Salad (c)
Grapef. Seg. (b)
Mixed Fr. (c)
Peaches
Pears
Pineapple (b)
Purple Plums
Total Fruits
cmiTT V iTprr V D ,
rt\'Ji i uoiUt-o
Apple
Grapefruit
Oranga
Blended Citrus
Pineapple
Total Juices
Total Fruits and
Juices
1969-70
2,877
16,758
5,543
178
237
21
33
42
1 ,505
947
3,519
334
16,686
788
3,515
728
37,538
10,590
16,871
2,209
120,919
13,390
22,124
14,296
2,420
25,322
77,552
198,471
1970-71
2,090
14,131
3,263
156
129
33
57
51
978
663
3,881
370
13,081
658
3,506
548
29,602
8,610
17,813
840
100,963
(Ba
14,118
25,993
15,452
2,500
25,715
83,778
184,741
1971-72
2,358
15,148
3,26"
169
209
12
18
33
1,041
536
3,453
205
13,334
784
2,752
695
25,762
10,309
17,652
1,199
98,932
?is 24/2 's)
13,696
26,177
13,852
1,983
24,840
80,548
179,480
1972-73
2,162
11,942
3,041
124
179
. n.a.
14
39
1,299
393
3,501
n.a.
11,855
724
2,587
752
24,016
9,063
16,540
394
88,725
13,832
28,262
17,053
2,135.
20,140
81,422
170,147
1973-7-
3,246
15,166
4,094
26
275
n.a.
n.a.
n.a.
579
503
4,713
n.a.
13,384
752
3,027
736
24,473
9,813
14,981
1 ,261
97,029
14,793
26,576*
14,385*
1,932*
20,590
78,276
175,305
^a' Includes huckleberries.
* ' Pack beginning year shown.
^c' California.
^ ' Include:* younqberries.
(e)
x ' Pack not yet compi
led. See
indi vi dual
commodities
for packs to
May 1974.
j_/ Source: Division of Statistics, National Canners Association.
Estimated.
n'a- Not avallable.
-------
Table IV-14. Summary of frozen vegetable packs, 1969-1973-^
ro
vo
Product
Potato products
Peas
Corn, cut
Beans, green and wax
Broccoli
Carrots
Spinach
Mixed vegetables
Beans, lima, baby
Corn-on-cob
Cauliflower
Beans, lima, fordhook
Brussels sprouts
Other vegetables
Total
— Source: American
1969-70
2,048,408
367,323
289,268
197,799
153,784
150,945
107,182
101 ,400
82,562
73,914
69,744
55,792
40,083
177,027
3,915,231
Frozen Food Instit
1970-71
2,404,389
344,520
216,097
212,362
185,157
173,054
145,694
110,333
73,012
80,889
59,782
35,844
42,663
231,935
4,316,731 •
.ute.
Pack (000 Ibs.)
1971 -72
2,565,118
348,418
226,835
228,763
189,600
143,681
156,991
112,388
73,898
106,893
67,659
40,690
49,195
264,232
4,574,361
1972-73
2,593,848
340,075
273,776
260,941
234,344
165,879
160,050
118,677
92,634
133,064
94,070
52,968
55,845
605,160
5,181,331
1973-74
2,691,073
387,749
294,223
290,861
213,165
231 ,688
159,501
99,435
98,112
166,830
96,098
51,577
56,836
678,660
5,515,808
-------
Frozen fruit packs, 1969-70 to 1973-74 are shown in Table IV-15.
Dominant frozen fruits are:
Frozen Fruit 1973-74 Pack (OOP IDS.) Percent of Total
Strawberries 168,552 25.9
Apples and sauce 135,086 20.8
Cherries RSP 109,368 16.8
Peaches 81,388 12^5
Total - 4 products 494,394 76.0
These four products account for 76 percent of the frozen fruit pack. Other
significant fruits packed include blueberries and red raspberries. The
pack of frozen fruits nas remained relatively steady during the past five
years.
Frozen fruit juice packs are shown in Table IV-16. The frozen juice pack
consists almost entirely of frozen orange concentrate, the 1973-74 pack
being 176,073,000 gallons (or 93 percent) out of a total of 189,25-1,000
gallons. Led by frozen orange concentrate, the pack of frozen fruit juices
has grown rapid!v during the past five years, the 1973-74 pack being 161
percent of the- i969-70 volume.
2. Carryin.
Carryin or carryover represents that volume of processed product which has
not been sold by the beginning of a new pack season and is "carried in"
as a part of the total supply for the coming year. Carryin is influenced
by a number of factors, but two predominate: (1) size of the previous year's
pack as influenced by the volume of production of fruits and vegetables for
processing and (2) consumer demand. Packers watch year-end carryins very
closely in pi a- n'ng their pack and pricing policies for the corning year.
A low carryin i.> an evidence of a strong demand as related to available
supplies.
Carryin for selected canned fruits and vegetables for the period 1969-1973,
is shown in Table IV-17. Carryin data are not available for all products,
but those shown in Table IV-17 represent the major pack items. In general,
1973-74 carryins were below average for all products except canned asparagus
where carryin was slightly above the 1969-73 average. Excluding asparagus,
average carryin of canned fruits and vegetables were as follows:
Carryin as percent of 1973-74 pack
Item 1973-74 Average 1969-73
Canned vegetables 8.1 % 17.5 %
Canned fruits 16.8 % 32.8 %
IV-30
-------
Table IV-15. Summary of frozen fruit packs, 1969-1973-^
Pack (000 Ibs)
Product
Strawberries
Cherries RSP
1969-70
178,693
140,588
Apples and sauce 122,293
Peaches
Blueberries
Raspberries,
Blackberries
Other fruits
berries
Total
— Source:
Table IV-
Product
Concentrated
juices
Orange
Grapefruit
53,527
37,663
red 27,657
27,184
and
90,578
678,283
American Frozen
1970-71
301,572
121,271
100,370
47,471
21,836
25,409 '
29,186
73,573
620,688
Food Institute
16. Summary of frozen fruit jui
1971-72
199,399
159,408
96,999
59,924
30,441
24,467
27,536
67,304
665,478
ce packs,
Pack (000 qa
1969-/0
citrus
-
108,043
5,920
Grapefruit-orange 36
Limade
Tangerine
Other miscall
concentrates
fruit juices
Total
852
1,051
aneous
and 1 ,661
117,563
1970-71
126,402
4,294
16
1,345
785
1,534
134,346
19/1-72
125,187
6,870
18
' 1,648
1,090
2,088
136,901
1972-73
146,842
145,570
130,377
46,316
30,932
20,485
21,164
70,374
612,062
1 969-1 973-/
1)
. T 972-73
134,229
8,798
22
1,498
1,220
2,824
148,591
1973-7^
168,552
109,368
135,086
81,388
44,376
26,625
8,249
76 ,.520
650,164
1973-74
176,073
8,658
3
936
1,072
2,512
189,254
— Source: American Frozen Food Institute
IV-31
-------
Table IV-17. Carryin, selected canned fruits and vegetables, 1969-73
GO
ro
Carryin "[000 cases)
Product
Tomat-'js, whole peeled
"os, to jjice
,.orn, sweet
Beans, green and wax
Bcdf^, lima
Peas green
Asparagus
Pu.rpKi.i and squash
App-es
Applesauce
Apricots
Peaches
Cherries, sweet and sour
Fruit, cocktail
Pears
Pineapple
Purple plums
1969
10,507
8,424
10,662
11,786
1,130
8,374
1,774
697
1,238
2,693
1,276
8,673
212
3,316
2,784
5,864
251
1970
6,361
6,490
9,618
9,708
1,300
6,618
1,725
955
1,417
4,170
3,379
13,544
482
3,426
2,990
6,811
917
1971
6,486
5,872
7,412
7,568
675
4,945
1,004
1 ,329
1 ,031
3,090
2,275
9,563
490
3,453
3,288
7,787
450
1972
4,356
6,723
7,098
6,166
718
5,659
933
1,106
717
3,327
862
6,174
558
4,336
3,688
8,663
376
19/3
4,117
2,205
3,599
2,763
162
4,060
1,490
480
290
1 ,315
487
2,397
199
2,335
2,431
7,012
57
Ave. 1969-73
6,365
5,943
7,678
7,598
797
5,931
1,385
913
939
2,919
1,656
8,070
388
3,373
3,036
7,227
422
Source:
The Almanac of the Canning, Freezing and Preserving Industries, 1974 and the Fruit Situation.
ERS, USDA.
-------
From these data it is seen that 1973-74 carryins were only half the 1969-73
average. It is also seen that carryins of canned vegetables are normally
only half as great as those for canned fruits. These smaller carryins
for 1973-74 were resultant of a reduced production of commodities pri-
marily due to poor weather conditions. The smaller supply increased
general prices which, in turn, encouraged liquidation of inventories.
Carryin for selected frozen fruits and vegetables for the period 1969-73,
is shown in Table IV-18. For frozen vegetables, 1973-74 carryins of beans
and peas were below the 1969-73 average, broccoli and spinach were about
average and carryins of asparagus, brussel sprouts, cauliflower and sweet
corn were above average. In total, 1973-74 carryins of frozen vegetables
were only 1.5 percent below the 1969-73 average. Carryin of frozen
vegetables averaged approximately ?8 percent of the 1973-74 pack.
Carryins of frozen fruits in 1973-74 were generally below the 1969-73
average, the only exceptions being raspberries and frozen concentrated
orange juice. Excluding orange juice, the 1973-74 carryin was only 73
percent of the 1969-73 average. Orange juice 1973-74 carryin was 60 per-
cent of the 1969-73 average.
Carryin of frozen fruits in 1973-74 averaged 28 percent of the 1973-74
pack as compared to 36 percent for the 1969-73 average carryin.
3. Imports
Imports of canned and frozen fruits and vegetables are not an important
factor in the total U. S. market, except for specific products shown in
Table IV-19. Substantial imports of canned apple and pear juice are re-
ceived, mainly from France and Switzerland. In 1972 imports of apple and
pear juice were equivalent to nearly half the U. S. apple juice pack.
Canned pineapple end pineapple juice imports are important (1972, 36 per-
cent and 16 percent of paci:) and originate primarily in Mexico, the
Philippines and Asia. Approximately half of the frozen strawberry pack
is accounted for by imports from Mexico and approximately a third of the
frozen blueberry pack is imported from Canada. Canned tomatoes and tomato
paste and sauce are important import items (15 and 9 percent) and come pri-
marily from Portugal, Italy and Spain. Imports of canned mushrooms,
primarily from Taiwan, make up over a quarter of the U. S. supply.
C. Industry Pricing Processes
The fruit and vegetable canning, freezing and preserving industry is large
and complex in terms" of the number and diversity of firms and plants and
is geographically scattered. It is highly competitive, both in terms of
product sales and raw product procurement. Due to the need for a predictable
flow of uniform, high-quality products, it often negotiates production con-
tracts with growers which gives it a measure of control over quantities,
IV-33
-------
Table IV- 18. Carryin, selected frozen fruits and vegetables, 1969-73
Product
i"«sp6ragus
". beans
•- beans
i ccoli
B'-jssels sprouts
uli flower
Swc .t corn
Ci-t-en peas
Spi ;_n
Apples
Apricots
Cherries
Grar _•
Peaches
Strawberries
Blackberries
Bl ueberries
Red raspberries
Frozen cone, orange juice
1969-70
15,184
66,259
90,127
35,837
14,705
25,503
110,603
147,012
41,757
51,300
' 4,400
33,500
2,300
35,100
94,500
5,700
14,300
8,200
(gal) 17,400
1970-71
10,973
62,522
62,495
48,020
10,410
23,003
112,411
136,698
20,457
58,100
8,100
38,400
1,300
28,300
116,700
8,700
16,600
8,700
26,600
Ccirryjn (
1971-72
6,913
45,174
52,099
65,804
1,1 ,040
16,904
53,532
110,117
24,344
39,600
7,000
20,600
3,800
19,200
110,300
10,000
6,800
6,300
22,600
^000 Ibs)
1972-73
12,000
49,400
49,000
85,000
15,900
34,600
94,700
139,000
57,000
23,100
3,700
39,700
3,300
22,100
95,600
5,600
8,000
5,000
27,700
1973-74
15,000
41 ,000
62,000
60,600
16,700
30,100
103,800
116,000
36,000
20,900
5,200
27,100
2,000
8,200
78,700
5,900
9,500
8.200
47,400
Ave. 1969-73
12,014
52,871
63,144
59,052
13,751
26,022
96,019
129,765
35,912
38,600
5,680
31,860
2,540
22,580
99,160
7,180
11,040
7,280
28,340
Source: The Fruit and Vegetable Situations, ERS, USDA.
-------
Table VI-19. United States' imports of canned and frozen fruit ?nd vegetable products, 1970-1972
Product
Canned Fruit Juices
Apple and pear juice
Pineapple juice
Canned & Frozen Fruits
Blueberries, frozen
Pineapples, canned
Strawberries, frozen
>—*
,',, Canned Vegetables
01 Tomatoes, paste & sauce
Tomatoes
Mushrooms, prep. pres.
except dried
Unit
gal.
gal .
000 Ibs.
000 Ibs.
000 Ibs.
000 Ibs.
000 Ibs.
000 Ibs.
1970
16,900
13,595
11,099
239,773
109,738
91,382
128,534
24,808
1971
34,024
13,143
8,433
259,685
84,565
97,817
108,557
30,763
1972
25,566
10,680
10,141
249,578
. 85,235
118,128
158,630
52,111
% of
U.S.
pack
1 /
49. 2 I/
15.9
32.8
35.6
50.6
9.4
15.3
28.7
Principal
countries
of origin
Switzerland & France
Phil ippines & Mexicc
Canada
Philippines
Taiwan
Mexico
Malaysia
Thailand
Mexico
Portugal
Italy
Spain
Taiwan
Source: The Almanac of the Canning, Freezing and Preserving Industries.
~~ Percent of U.S. apple juice pack as statistics for pear juice were not available.
-------
varieties and production conditions for raw products. In some states, pri-
marily in California, it operates under marketing orders which permit a
measure of control over the volume and/or quality of raw fruits and vege-
tables used for processing. This section will consider three elements of
the pricing process: (1) market competition and price determination, (2)
grower contracts and (3) marketing agreements and marketing orders.
1. Market Comoetition and Price Determination
Although a relatively high percentage of the total pack of canned and frozen
fruits, vegetables and specialty foods is produced by a small number of
major processors, there exist large numbers of medium and small processors
and as a result the industry remains highly competitive.
Products are relatively standardized and are sold by grade. Recent labeling
legislation has increased the requirements for label information and has
resulted in more definite standardization of label inn.
Once a canning or freezing season is underway and prices have found the
level dictated by supply conditions, known pack and carryin, prices remain
relatively stable throughout the marketihg season. Table IV-20 shows quarterly
prices as reported, for the 1970-71 and 1972-73 seasons. This price stability
is evident. Reported prices for cherries were stable through the season,
prices for peas, corn, green beans and tomatoes varied within a narrow range
and prices for peaches showed a slight upward trend. Although reported prices
are relatively stable, actual net sales prices vary in that many sales are
made on-a specification-bid basis, especially to national retail food
chains and competition is evidenced through cash discounts, advertising and
promotion allowances and credit arrangements.
An appreciable part of the pack, of both canned and frozen products is packed
and sold under private buyer labels—especi-Jly labels of such major food
chains as Safeway or A&P. In excess of 40 percent of the pack of both canned
and frozen products are s.old under private buyer labels, with greater em-
phasis on private buyer labels being found among medium and small packers.
Large, nationally-advertised brands (e.g. Del Monte or Birdseye) tend to
sell at a premium over private buyer label products.
Although brokers play a major role in marketing both canned and frozen fruit,
vegetables and specialty food products, the importance of direct sales to
food chains is increasing and these chains purchase over half of the canned
pack and 30-40 percent of the frozen food pack in the United States.
Buyers commonly specify quality levels for products which they purchase and
packers must compete on a quality-pri ,.e aid basis.
r -^
-------
Table IV-20.
Canners f.o.b. price, major canned fruits and vegetables, by
by quarters, 1970-71 and 1972-73I/
Product Unit
Date
1970-71
Green beans, snap 24/303
midwest, ex. std. cut
Corn, sweet
midwest, fancy, gold 24/303
Peas, sweet
midwest, ung. ex. std. 34/303
Tomatoes
Calif, std. 24/303
Cherries, RSP
midwest, water 24/303
-
Peaches
Calif, ch. cling 24%
— Source: Biweekly issues of "The
Aug.
Oct.
Jan.
Apr.
Sept.
Jan.
Apr.
July
July
Oct.
Jan.
Apr.
Sept.
Jan.
Apr.
July
July
Oct.
Jan.
Apr.
Sept.
Jan.
Apr.
July
Canning
1-
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Trade
$3
3
3
3
$3
3
3
3
$2
3
$3
3
3
3
5
5
5
•
$5
5
5
M
.00
.05
.05
.20
.50
.50
.50
.50
.95
.35
.60
.45
.50
.70
.15
.15
.15
.80
.60
.70
and
- 3.
- 3.
- 3.
- 3.
- 3.
- 3.
- 3.
- 3.
- 3.
3.
3.
- 3.
- 3.
- 3.
- 3.
- 3.
$5.
- 5.
- 5.
- 5.
- 6.
- 6.
6.
- 6.
10
15
15
25
55
55
60
75
20
35
35
40
70
70
70
80
00
25
25
25
10
10
60
25
monthly
Price
1972-73
$3.
3.
3.
3.
$3.
3.
3.
3.
$3.
3.
3.
3.
$3.
$6.
issues
30
30
40
40
40
55
60
65
50
50
50
50
70
85
of
- 3.
_ ^
- 3!
- 3.
- 3.
- 3.
- 3.
- 3.
- 3.
- 3.
- 3.
- 3.
- 4.
4.
4.
4.
$6.
6.
6.
6.
$6.
- 6.
6.
7.
40
40
55
55
65
70
75
80
55
55
55
55
00
00
00
00
25
25
25
25
80
95
95
20
"Kood Production Management."
IV-37
-------
Strong national trade associations exist and help provide market information
to their members. Similar information is regularly published in specialized
trade magazines and this information plus that available from federal (USDA)
and state agencies provides the industry with a good information base.
The canned and frozen fruit, vegetable and specialty foods industries oper-
ate within an organized and relatively stable price climate. Nevertheless,
the industry is highly competitive and prices are determined by carryins,
packs and national economic conditions rather than by price leadership or
by relentless competition among processing firms.
2. Grower Contracts
The fruit and vegetable processing industry, and the vegetable industry in
particular, depends heavily on contractual arrangements with growers. More
than two-thirds of the raw product supplies of fruits and vegetables are
produced under contracts with canners as were over half of the raw products
for freezers. Most of the remaining volume of raw product was produced by
growers not under contract. Backward integration into production is not a
major supply factor in the fruit and vegetable processing industry.
Contracting with growers is deemed necessary to secure a predictable quantity
and quality of raw_product and assists processors in reducing the risks of
year-to-year raw product variations without investing capital resources
directly in farm production.
Provisions governing varieties, acreage, quality and delivery terms are
normally specified in grower contracts. Extensive use of these provisions
reflects the preoccupation of processors with quality control and the flow
of raw product into thsir facilities. Other provisions of grower cpntracts
relate to use of fertilizers, herbicides and pesticides.
Price provisions of grower contracts vary. Nearly all small and medium-sized
processors provided a price guarantee in grower contracts,. Many of the pro-
cessors not providing price guarantees in grower contracts are large pro-
cessors, e.g. in California, where grower bargaining associations are prevalent,
Growers and canners often enter into contract agreements calling for delivery
of specified quantities and qualities of products at prices to be determined
through later negotiation.
Regardless of the specific terms of grower-processor contracts, these con-
tractual arrangements introduce a degree of rigidity into the pricing
structure of raw fruits and vegetables which tends to restrict the ability
of processors to pass increased costs backward to producers in the form of
lower producer prices. Also, the producer has alternate production options
which allows him to produce other crops if processors attempt to lower com-
modity prices significantly.
IV-38
-------
3. Marketing Agreements and Marketing Orders
Marketing agreements and orders are intended to give growers, handlers and
processors of fruits and vegetables legal authority to regulate (within speci-
fied limits) the volume and/or quality of marketings and to raise funds for
insepction, promotion and research. Two general classes of agreements and
orders exist, Federal and State. Federal orders are based on enabling legis-
lation known as the Agricultural Marketing Agreement Act of 1937 as amended.
Similar enabling legislation has been provided by 10 states.
Enabling legislation for marketing orders and agreements is intended primarily
for the benefit of producers of agricultural commodities. Producers, in con-
cert with handlers, are authorized to collectively regulate the marketing of
a commodity and to engage in other specified types of joint activity intended
to enhance the level and stability of returns to producers of the commodity.
Regulations and activities are formulated and implemented in accordance with
handlers, are authorized to collectively regulate the marketing of a commodity
and to engage in other specified types of joint activity intended to enhance
the level and stability of returns to producers of the commodity. Regulations
and activities are formulated and implemented in accordance with provisions
of the relevant enabling statute subject to the approval of the U.S. Secre-
tary of Agriculture or his counterpart in the State government. The principal
regulations and activities authorized by Federal enabling legislation and by
most of the State enabling statutes are:
1. The establishment and enforcement of minimum standards of grade
• size, maturity, or other attributes of quality in the marketing of
an agricultural commodity.
2. Limitation of the quantity of the coiiimodity marketed in total or by
grade, size, maturity, or other attributes of quality during a speci-
fied time period. Such limitations may differ among markets for'the
commodity in time, space or form.
3. Regulation of the characteristics of pack and containers applicable
in marketing the commodity.
4. Specification and prohibition of trading practices deemed to be unfair.
5. Posting of prices.
6. Research.
In addition to the foregoing regulations and activities which may be under-
taken singly or in combination; most State statutes authorize marketing orders
for the purpose of conducting nonbrand promotion of an agricultural community.
The Agricultural Marketing Agreement Act, as amended, authorizes paid adver-
tising for specified commodities.
IV-39
-------
Although marketing orders and agreements are sometimes considered to be syn-
onomous, there are important distinctions between them. A marketing agree-
ment is a purely voluntary arrangement between the Secretary or his State
counterpart and individual handlers of an agricultural commodity. The terms
of the agreement may include those regulations and activities specified
previously but are not limited to those. A marketing order may be issued
only with the approval of a specified majority of producers and in some
cases only when a majority of handlers indicate their approval by signing a
marketing agreement containing terms and conditions parallel to the order.
But once an order has been approved and issued, its terms and conditions are
binding upon all relevant producers and handlers in the industry. In practice,
the marketing agreement is employed principally as an adjunct to marketing
orders which by their nature are a more effective device for concerted mar-
ket regulation.
Federal and State legislation for marketing orders differ in several respects.
For example, most fruits and vegetables for canning and freezing are ineligible
for use of a Federal marketing order but are eligible for orders under legis-
lation provided in California, Colorado, Georgia, Michigan, New York, Utah,
Washington, and Wisconsin. Each of the currently effective enabling acts
focuses upon regulation of marketing, not, upon production of agricultural
commodities. However, some State statutes, unlike the Federal act, authorize
the direct application of marketing quotas upon producers. The Federal act
specified the attainment of parity price as a goal of marketing orders; State
statutes contain broader, less precise objectives.
It is apparent that a marketing order might alter significantly the structure,
conduct, and performance of the market at the producer level. Producers acting
in concert through- the order may attain a degree of monopoly power which is
generally unattainable to them as individuals. However, the economic gain
which the producer group may potentially secure under a marketing order is
dependent upon numerous variables-, the structure of the relevant markets,
the characteristics of demand in the relevant markets, the nature of producer
supplier relationships, the nature of the provisions implemented under the
order, the proportion of the relevant market supply regulated by the order.
Thus, evaluation of the potential or realized economic benefits of marketing
orders requires consideration of the terms and conditons of the order and the -
particular economic circumstances of the industry in question.
Major commodities, for which State orders permit regulation of volume, grade
or rate of flow of products into processing markets include: cling peaches,
Bartlett and hardy pears, cranberries, strawberries, Brussel sprouts, dry
peas and lentils, olives and dried fruits (prunes, figs, raisins).
Each marketing order is administered by an advisory board of growers and
handlers/processors. Prior to the opening of a new pack season, the advisory
board formulates a marketing program for that year which provides guidance
for the order in its efforts to influence the volume and/or grades/sizes
packed and relates this program to anticipated prices. An analysis is made
IV-40
-------
of the coming marketing season, either by the advisory board or by a desig-
nated agency (e.g. in California the Giannini Foundation of Agricultural
Economics at the University of California). The advisory board considers
this analysis and other information on carryin stocks, etc. and then meets to
formulate its marketing program for the coming year.
Marketing orders for processed fruits and vegetables, although not important
over all varieties packed, are important for such canned products as peaches
and pears. The existence of marketing orders tends to introduce a measure
of year-to-year and intra-year stability in prices of those commodities
covered by such orders.
D. Processing and Marketing Margins_
The consumer's food dollar must pay for all the materials and services in-
volved in producing, processing and distributing food. Large cost increases
in nearly all phases of processing and marketing—including labor, packaging
and transportation—are a major factor in widening margins and rising retail
prices.
Margins for different commodities and for different marketing functions vary
widely among products due, mainly, to differences in the amount and type of
processing, packaging and bulkiness.
Marketing margins for selected products are reported regularly by the
Economic Research Service, USDA in the "Marketing and Transportation
Situation." The only processed fruit and vegetable items included are
applesauce, frozen orange juice, canned whole tomatoes, tomato catsup
and frozen French fried potatoes. For the purpose of this study, only
tomato products are of primary concern. At periodic intervals, more in-
clusive special stuJies are made, for example "Pi-ices, Margins and Farm
Value for Canned and Frozen Fruits, Vegetables and Juices Sold in Selected
Markets, 1965-66-1969/70," Statistical Bulletin No. 477, Economic Research
Service, USDA. Another recent study "Developments in Marketing Spreads for
Agricultural Products in 1973," ERS-14 (1974), Economic Research Service,
USDA, investigated in detail the components of marketing margins for those
products regularly reported in the Marketing and Transportation Situation.
In addition to these published margin estimates, it is possible to con-
.struct gross margin estimates from published price data — farm value, f.o.b.
processor, and retail price. Although farm value and f.o.b. processor prices
are available for most canned and frozen products, the retail price series,
published by the Bureau of Labor Statistics, is more limited. In addition,
there is a problem of matching qualities, unit equivalents and locational
factors as represented by the various price series.
Within these data limitations, an analysis of the margins for canned and
frozen fruits and vegetables has been made.
IV-41
-------
Retail prices of most canned and frozen fruits and vegetables increased
in 1972-73. Higher prices for most processed deciduous fruits were mainly
the result of reduced supplies. Both the season's pack and carryin were
below the previous year. Canned and frozen vegetable supplies were about
the same as a year earlier; however, higher processing costs and strong
demand resulted in price increases at the retail level. The marketing spread
increased, in absolute values, for most processed fruits and vegetables—
in some cases at a higher rate than the retail orice increase. Overall,
the farmer's share of the retail food dollar for processed fruits and
vegetables for 1973 averaged about 19 percent—about the same as in 1972.
1. Margins - Specific Products - Grower - Processor - Wholesale ft Retail
Current and historical data were available for a limited nuirber of major
commodities. Data for the period 1965-1969 were largely from the publica-
tion "Prices, Margins and Farm Value for Canned and Frozen Fruits, Vegetables
and Juices," Statistical Bulletin No. 477, Economic Research Service, U.S.D.A.
Data subsequent to 1969 came from the "Marketing and Transportation Situa-
tion," ERS, USDA or were calculated by DPRA from published price series.
Examination of these data in Table IV-21 concerning margins shows the
following relationships:
Product
Corn, canned
Peas, canned
Tomatoes, whole canned
Peas, frozen
Peaches, canned
Pears, canned
Trend in margin
Grower
1965-73 1970-73
down
down
down
steady
steady
down
steady steady
down down
down steady
Processor
1965-73
down
down
steady
up
steady
up
1970-73
steady
steady
steady
steady
up
up
Wholesale-Retailer
1965-73
up
up
up
down
steady
steady
19/0-73
steady
stead:
up
steady
down
down
Over the period 1965-73, these data show a general decrease in the percentage
of the sales dollar going to producers, a decrease for processors of canned
vegetables, an increase in processor margins for frozen vegetables and canned
fruits and an increase in relative margins at the wholesale-retail level for
canned vegetables, steady margins for canned fruits and decreasing margins
for frozen vegetables.
IV-42
-------
Table IV-21.
Marketing margins for selected canned arid frozen fruits and
vegetables, 1965-1973 I/
Product
Corn, canned
Peas, canned
Tomatoes, canned,
Tomato catsup
Peas, frozen
Year
beginning
1973
1972
1971
1970
1969
1968
1967
1966
1965
1973
1972
1971
1970
1969
1968
1967
1966
1965
whole 1973
1972
1971
1970
1969
1968
1967
1966
1965
1973
1973
1972
1971
1970
1969
1968
1967
1966
1965
Margin
as percent
Grower Processor
(%)
11.6
11.4
10.5
11.1
14.0
15.0
14.0
14.0
14.0
15.6
15.2
14.9
15.5
17.0
18.0
18.0
17.0 '
16.0
9.7
11.8
11.5
12.2
13.0
15.0
16.0
14.0
16.0
11.4
16.8
16.4
16.7
17.0
16.0
17.0
17.0
18.0
17.0
(%)
41.6
39.6
40.7
39.3
46.0
44.0
55.0
57.0
56.0
40.4
40.5
40.1
35.5
51.0
49.0
47.0
43.0
43.0
58.3
63.2
62.4
58.7
58.0
50.0
57.0
62.0
58.0
51.4
50.0
51.1
51.6
62.3
39.0
. 38.0
40.0
42.0
32.0
of retail
Wholesale-
retail
(%}
46.8
49.0
48.8
49.6
40.0
41.0
31.0
29.0
30.0
44.0
44.3
45.0
49.0
32.0
33.0
35.0
40.0
41.0
32.0
25.0
26.1
29.1
29.0
35.0
27.0
24.0 '
26.0
37.2
33.2
32.5
31.7
20.7
45.0
45.0
43.0
40,0
51.0
price
Total
(*)
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
10C.O
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
IV-43
(cont.)
-------
Table IV-21. (Continued)
Year
Product beginning
Peaches, canned 1973
1972
1971
1970
1969
1968
1967
1966
1965
Pears, canned 1973
1972
1971
1970
1969
1968
1967
1966
1965
Margin as percent
Grower Processor
~~00~
17.3
19.3
20.1
19.9
20.0
21.0
23.0
19.0
19.0
21.4
19.4
22.1
23.1
19.0
23.0
30.0
18.0
26.0
/ o-M
(/o)
55.4
52.9
49.3
47.4
43.0
49.0
55.0
46.0
53.0
50.0
49.4
47.8
42.8
38.0
39.0
45.0
• 39.0
39.0
of retail
Wholesale-
retail
(*)
27.3
27.8
30.6
32.7
37.0
30.0
22.0
35.0
28.0
28.6
31.2
30.1
34.1
43.0
38.0
25.0
43.0
35.0
price
Total
(*)
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
Source: USDA, ERS, "Prices, Margins and Farm Value for Canned and Frozen
Fruits, Vegetables and Juices," Statistical Bulletin No. 477,
and USDA, ERS, "Marketing and Transportation Situation",
IV-44
-------
2_. Margins - Grower - Processor On 1 y
For a number of other canned fruit and vegetable products, retail orices
were lecLing and as a result grower-processor-wholesaler and retailer margins
could not be calculated. However, for these products data on farm price and
earners f.o.b. plant price were available and it was nossible to calculate
the farmer's share of the earner's f.o.b. price. The farmer's price used
is the "on-farm" price as reported by the Statistical Reporting Services,
USDA. The earner's price is the spot selling price, f.o.b. cannery as
reported in "Food Production Management".
Data on the farmer's share of the earner's f.o.b. plant pries are shown
in Table IV-22. A substantial degree of variation exists depending on the
value of the raw product and the degree of processino involved. The fanner's
share varied from a low of about 10 percent for sliced beets to a maximum of
44 percent for canned asparagus. In general, the farmer's share of the
processor's price was higher for fruits than for veoetables. An interesting
situation is observed for the 1967-63 cherry cron where the farmer's share
was very high as a result of an unusually short crop (50;' of normal) of
cherries. This illustrates the sensitivity of prices of canned fruits and
vegetables to available supply.
One other relationship is apparent from these data. In general, the
farmer's share of the earner's price declined slightly during the 1967-1973
period (9.9 percent). It is interesting to note that snap beans, for which
consumption has increased rapidly, has had a substantial decline in the
grower's share of the earner's price and that commodities for which demand
has not been as strong, e.g., sauerkraut and spinach showed little change in
the farmer's share of the processor's price.
E. Exoected Price Ch<.,.oes
The ability of the fruit and vegetable canning, freezing and preserving
industry to pass ircreased pollution control costs forward to consumers
in the form of higher retail prices or backward to the producer as lower
prices for raw product, will depend on a number of factors and factor
combinations existing in the industry. Major determinants will include:
* Demand factors
a. Trends in per capita demand
b. Price elasticity of demand
c. Income elasticity of demand
d. Cross-elasticity of demand-substitutes
IV-45
-------
Table IV-22. Farmers' share of the canner's price, selected
fruits and vegetables for processing, 1973-74, 1970-71
and 1967-68 I/
Prod u : t
Asparagus; canned
Beans, green snap, canned
Beets, sliced, canned
Corn, sweet, whole gr. , canned
Peas, green, sweet, canned
Sauerkraut, canned
Spinach, canned
Tomatoes, whole, peeled, canned
Apricots
Cherries, RSP, canned
Peaches
Fanner's share
1973-74
7%)
44.1
21.6
10.0
19.7
25.2
11.8
11.7
15.6
23.0
34.2 (1972-73)
26.1
of canner
1970-71
(%)
44.1
24.0
10.3
20.5
28.8
12.3
12.5
14.2
19.5
37.5
29.9
's price (%}
1967-6£
(W~
45.0
28.3 •
10.5
19.5
33.3
12.0
12.7
17.3
27.4
58.0*
29 . 7
* Short crop, approximately 60 percent of normal.
If Source, calculated from data in The Almanac of the Canning, Freezing
and Preserving Industry.
IV-46
-------
* Supply factors
a. Trends in domestic production of raw fruits
and vegetables
b. Trends in imports of processed fruits,
vegetables and specialty food nroducts
* Industry organization and competition
a. Levels of profits within the industry
b. Competitive structure of the industry
c. Concentration or production in the industry
d. Size distribution of firms
e. Specialization versus diversification
f. Processor margins
g. Institutional factors affecting pricing
1. Demand Factors
In general, demand for canned and frozen fruits, juices,
vegetables and specialty foods has been rising, both in per
capita and absolute terms. This reflects changing tastes and
preferences, a demand for convenience foods associated in
part with a higher proportion of women employed outside the
home, higher consumer incomes and improvements in processing
technology and retail store self-service especially for
frozen foods. The demand for dried fruits arid vegetables
has dropped substantially as has the demand for most fresh
vegetables and fruits. Export demand is important for certain
canned fruit and juices and has increased in recent years.
2. Supply Factors
The supply of processed fruits, vegetables and juices consists
of three parts: domestic pack, carryin from previous year's
pack and imports. During the past five years, total canned
vegetable pack has increased 9.1 percent, canned fruit packs
were down 19 percent and canned fruit juice packs were steady.
Frozen vegetable packs were up strongly, up 41 percent,
frozen fruit packs were relatively steady and frozen juice packs
(primarily frozen orange concentrate) were up 61 percent.
Carryins for canned and frozen fruits, vegetables and
juices for 1973-74 were generally below levels of the
past five years. Imports are not generally an important
supply source for most commodities, but are important in
a few products (e.g. mushrooms, pineapple, blueberries, etc.).
IV-47
-------
3. Industry organization and_co_mpeti_tipn
Although a relatively small number of large, multi-plant, multi-
product firms process and distribute a high percentage of the total
fruit end vegetable pack, the industry is still very competitive, no
one firm being dominant. There are large numbers of medium and small
plants and while for some products production is concentrated geo-
graphically, for others oroduction and processing is scattered through-
out the United States. Plants tend to specialize along functional
(e.g. canning) and commodity (e.g. tomatoes) lines. Although one
product may be predominant, most plants pack two or more different
products through the same facility. Although specialized canning or
freezing plants exist, plants which both can and freeze are common.
Processor share of the retail price normally account for 40 to 60
percent, with the 40 to 50 percent range being the most common.
Two major institutional factors exist in the fruit and vegetable
processing industry which affect raw products supplies and prices
for fruits and vegetables for processing. State marketing orders
give growers and processors a measure of control over the volume of
products processed, either through volume or grade and size pro-
ration. Grower-processor contracts tend to establish prices packers
will pay for raw products and introduce rigidities into the raw product
price.
4. Anticipated price impacts of effluent control programs
a. Possibility of lower raw product prices — For most fruits and
vegetables for processing, grower margins (the percentage the
grower receives of the retail price) are relatively low and
have been decreasing. In addition, growers have other production
alternatives and in some commodities, grower bargaining associa-
tions, grower-processor contracts and State market orders tend to
fix the price on the supply of raw product for his plant. In
addition, rising per capita and total demands put increasing
pressures on packers to expand supplies or to add to existing
sources of supplies of raw products for their plants. As pro-
cessors are forced to extend their supply areas to obtain larger
supplies of raw product to meet expanding demand, transportation
costs increase and the competitive position of existing suppliers
is strengthened. As a result of these forces, it is doubtful
that processors would be successful in efforts to compensate for
increased costs of effluent controls by lowering prices paid to
growers for raw products.
b. Possibility of passing forward costs to consumer as higher
prices.
Two situations exist when consideration is given to the possi-
bility of passing effluent control costs forward to the consumer
as higher prices:
IV-48
-------
(1) In the short-run, there would appear to be little opportunity
for such cost transfer. The fruit and vegetable processing
industry is extremely competitive and although large firms
exist, no one is dominant.
Although a relatively large proportion (up to 70 percent) of
the industry is on municipal sewers or has acceptable effluent
treatment systems in place, these plants will face additional
effluent treatment costs as user fees for firms on sewer sys-
tems are increasing rapidly and substantially and as'users
are obligated to reimburse sewage utilities for their "fair
share" of investments in municipal sev/age systems necessary
to upgrade such systems to meet EPA standards.
«-,
Although fruit and vegetable processing plants normally
operate at levels up to 70-75 percent of capacity, such
"surge" capacity is necessary to meet seasonal processing
peaks and to provide for variations in processing volumes
from year to year. Without such surge capacity, processors
at times would have to bypass fields ready for harvest -
product for which they have grower-processor contracts and
for which they are obligated to pay - at a substantial loss
to the processor.
Finally, food prices have reached the point where additional
price increases are meeting strong consumer resistance.
For these reasons, it is doubtful that impacted processors
could be able to recapture effluent control costs by increasing
consumer prices in the short-run.
(2) In the long-run, the ability of processors to pass forward
cost increases in the form of higher consumer prices will be
dependent on the demand characteristics for the individual
products. In general, better opportunities for price increases
would exist for those products having relatively low demand
elasticities. Even under long-run conditions, it is not
expected that a complete pass-through of costs will be possible
since competitive conditions in the industry coupled with con-
sumer resistance to increasing prices would restrict oppor-
tunities for price increases. As a result, processors would
be forced to absorb out of profits most of the increased costs
of effluent controls.
No major shift from processed to fresh forms of fruits and
vegetables is anticipated. The increasing demand for processed
fruits and vegetables, both canned and frozen, is the result
of consumer demand for convenience foods and because of the
wider availability of processed fruit and vegetable foods.
The increase in consumer prices which would be required to
offset effluent control costs, would generally be too small
to cause consumers to switch back to fresh products.
IV-49
-------
The importation of fruits and vegetables into the United
States is based largely on the fact that, for some products,
such as pineapple or strawberries, U.S. production is either
limited or is too expensive. For other imports, e.g. Italian
tomato paste, style of pack is a major determinant. In
addition, instances exist where lower costs of production
overseas more than offset higher transportation costs and
import duties. In most foreign producing areas, processors
are not faced with the requirements for control"ing air pollu-
tion or effluents or for plant safety (OSHA) systems, which
are required by the U.S. producer. This gives such foreign
processors a further competitive advantage in supplying U.S.
markets.
IV-50
-------
V. ECONOMIC IMPACT ANALYSIS METHODOLOGY
This study's economic impact analysis utilizes the basic industry infor-
mation developed in Chapter I-IV and the pollution abatement technology
and costs provided by Environmental Protection Agency as described in
Chapter VI. The impacts examined include:
Price effects
Financial effects
Production effects
Employment effects
Community effects
Other effects
The required impact analysis is not a simple sequential analysis; rather
it employs interacting feedback steps. The schematic of the analytical
approach is shown in Figure V-l. Due to the fundamental causal relation-
ships among the financial and production effects and the other impacts,
a greater emphasis is devoted to plant closure analysis.
Fundamentally, the impact analysis is similar to that usually required
for any capital budgeting study of new investments. The problem is one
of deciding whether a commitment of time or money to a project is worth-
while in terms of the expected benefits. The analysis is complicated by
the fact that benefits and investments will accrue over a period of time
and that, in practice, the analyst can not reflect all of the required
imponderables, which by definition must deal with future projections.
In the face of imperfect and incomplete information and of time constraints,
the industry segments are described in the form of financial budgets of
model plants. Key non-quantifiable factors were considered-in the inter-
pretation of the quantified data. Actual financial results will deviate
from the model results, and these variances will be considered in inter-
preting the findings based on model plants.
A. Fundamental Methodology
The fundamentals for analysis are basic to all impact studies. The core
methodology is described here as a unit with the specific impact analysis
discussed under the appropriate heading following this section.
The core analysis for this study was based upon synthesizing the physical
and financial characteristics of the various industry segments through
representative model plant projections. Estimated financial profiles and
cash flows are presented in Chapter III. The primary factors involved
V-l
-------
Industry
Industry
Structure
Segmentation
Industry
Financial
Data
EPA Pollution
Control Costs
Plant Closures!.,
*1 Due to Control
E m pi o y rn e nt
Effects
vt
C c i. i m u n i t y
.ects
Model Plant
Parameters
Budget
Data
Development
Model
Financial
Analyses
Price
Increases
T
Shutdown
Analysis
\7
Production
Expected
Effects
Foreign
Trade
Effects
Industry
Pricing
Financial
Profiles
Figure V-I. Schematic of irnpa ct analysis of rfflucni control guidelines,
V-2
-------
in assessing the financial and production impact of pollution control
are profitability changes, which are a function of the cost of pollution
control, and the ability to pass along these costs in higher prices. In
reality, closure decisions are seldom made on a set of well-defined and
documented economic rules. They include a wide range of personal values,
external forces such as the ability to obtain financing, or the relation-
ship between a dependent production unit and its larger cost center whose
total costs must be considered.
Such circumstances include but are not limited to the following factors:
1. Inadequate accounting systems or procedures. This is
especially likely to occur in small, independent plants
which do not have effective cost accounting systems.
2. Insufficient production units. This is especially true of
plants where the equipment is old and fully depreciated and
the owner has no intention of replacing or modernizing them.
Production continues as long as labor and materials costs are
covered and/or until the equipment fails entirely.
3. Personal values and goals associated with business owner-
ship that override or constrain rational economic rules.
This complex of factors may be referred to as the value of
psychic income.
4. Production dependence. This is characteristic of a plant that
is a part of a larger integrated entity which either uses raw
materials being produced profitably in another of the firm's
operating units or supplies raw materials to another of the
firm's operations where the source of supply is critical.
When the profitability of the second operation more than off-
sets the losses in the first plant, the unprofitable operation
may continue indefinitely because the total enterprise is
profitable.
5. Temporary unprofitability. This may be found whenever an owner-
operator expects that losses are temporary and that adverse con-
ditions will change. His ability to absorb short-term losses
depends upon his access to funds through credit or personal re-
sources not presently utilized.
6. Low (approaching zero) opportunity costs for the fixed assets
and for the owner-operator's managerial 'skills and/or labor.
As long as the operator can meet labor and materials costs,
he will continue to operate. He may even operate with gross
revenues below variable costs until he has exhausted his working
capital and credit.
V-3
-------
7. Plant site appreciation. This factor is important in those
situations where the value of the land on which the plant is
located is appreciating at a rate sufficient to offset short-
term losses.
These factors are generally associated with proprietorships and closely
held enterprises rather than publicly held corporations.
While the above factors are present in and relevant to business decisions,
it is argued that common economic rules are sufficient to provide useful
and reliable insight into potential business responses to required in-
vestment and operating costs in pollution control facilities.
The following discussion presumes investment in pollution control fa-
cilities. However, the rules presented apply to on-going operations.
In the simplest case, a plant will be closed when variable expenses(Vc)
are greater than revenues (R) since by closing the plant, losses can be
avoided.
A more probable situation is where VC < R but revenues are less than
variable costs plus cash overhead expenses (TCc) which are fixed in the
short-run. In this situation a plant would likely continue to operate as
contributions are being made toward covering a portion of these fixed
cash overhead expenses. The firm cannot operate indefinitely under this
condition, but the'length of this period is uncertain. Basic to this
strategy of continuing operations in the' firm's expectation that revenues
will increase to cover cash outlay. Identification of plants where TCc >
R, but Vc < R leads to an estimate of pi an Is that should be closed over
some period of time if revenues do not increase. However, the timing of
such closures is difficult to predict.
The next level is where TCc < R. So long as TCc < R, it is likely that
plant operations \>!11 continue if the capitalized value oT earnings (CV),,
at the firm's (industry) cost of capital is greater than the realizable
value (S) of sunk plant investment. If S > CV or CV - S > 0, the firm
could realize S in cash and reinvest and be financially better off,
assuming reinvesting at least at the firm's (industry) cost of capital.
Computation of CV involves discounting the future earning flows to present
value through the discounting function:
l
NPV = TJ A n + i)'"
n=l
where
NPV ~ net present value
A = a future value in ntn year
i = discount, rate al cost of capital
n = number of conversion periods, i.e.
1 year, Z years, etc.
t = time
V-4
-------
It should be noted that a more common measure of profitability is return
on investment (ROI) where profits are expressed as a percent of invested •
capital (book value), net. worth or sales. These measures should not be
viewed so much as different estimates of profitability compared to present
value measures but rather these should be seen as an entirely different
profitability concept.
The data requirements for ROI and NPV measures are derived from the same
basic financial information although the final inputs are handled differ-
ently for each.
1. Returns
For purposes of this analysis, returns for the ROI analysis have been de-
fined as pre-tax and after-tax income and for the NPV analysis as after-
tax cash proceeds. The computation of each is shown below:
Pre-tax income = (R-E-I-D)
After-tax income = (1 - T) x (R-E-I-D)
where
T = tax rate
R = revenues
E = expenses other than depreciation and interest
I = interest expense
D = depreciation charges
Interest in the cash proceeds computation is omitted since it is reflected
in the discount rate (the after-tax cost of capital). Depreciation is in-
cluded in the NPV measure only in terms of its tax effect and is- then added
back to obtain cash flow.
A tax rate of 22 percent on the first $25,000 income and 48 percent on
amounts over $25,000 was used throughout the analysis. ]_/ Accelerated de-
preciation methods, investment credits, carry forward and carry back pro-
visions were not used due to their complexity and special limitations.
2. Investment
Investment is normally thought of as outlays for fixed assets and working
capital. However, in evaluating closure of an on-going plant with sunk
investment, the value of that investment is its liquidation or salvage
- It is recognized that for 1975 the tax is 22 percent on the first $50,000.
However, this is a temporary "anti-recession" regulation and there is no
guarantee that it will be extended beyond one year.
V-5
-------
value (opportunity cost or shadow price).- For this analysis, sunk in-
vestment was taken as the sum of liquidation value of fixed assets plus
net working capital (current assets less current liabilities) tied up by
the plant (see Chapter III for values). This same amount was taken as a
negative investment in the terminal year.
The rationale for using total shadow priced investment was that the cash
flovs do not include interest expenses with interest charges reflected in
the weighted cost of capital. This procedure requires the use of total
capital (salvage value) regardless of source. An alternative would be to
use es investment, r.et cash realization (total less debt retirement) upon
liquidation of the plant. In the single plant firm, debt retirement would
be clearly defined. In the case of the multi-plant firm, the delineation
of the debt by the plant would likely not. be clear. Presumably this could
be reflected in proportioning total debt to the individual plant on some
plant parameter (i.e. capacity or sales). Under this latter procedure,
interest and debt retirement costs would be included in the cash flows.
The two procedures will yield similar results if the cost of capital and
the interest charges are estimated on a similar basis. The former pro-
cedure, total salvage value, was used as it gives reasonable answers and
simplified both the computation and explanation of the cash flows and
salvage values.
Replacement investment for plant maintenance was considered to be equal
to annual depreciation. This corresponds to the operating policies of some
managements and serves as a good proxy for replacement in an on-going
business.
Investpients in pollution control facilities are from estimate:; provided by
EPA. Only incremental values are used in order to reflect in-place facili-
ties. Only the value of the land for control '.'as t?ken ?.s e negative in-
vestment, or "cash out1' value, in the terur :J year.
The above discussion refers primarily to the NPV analysis. Investment
used in estimating ROI was taken as invested capital—book value of assets
plus net working capital.
3. Cost of Capital - After-Tax
Return on invested capital is a fundamental notion in U.S. business. It
provides both a measure of the actual performance of a firm as well as its
This should not be confused with a simole buy-sell situation which
merely involves a transfer of ownership from one firm to another.
In this instance, the opportunity cost (shadow price) of the invest-
ment may take on a different value.
V-6
-------
expected performance. In the latter case, it is also called the cost of
capital and this, in turn, is defined as the weiqhted average of the cost
of each type of capital employed by the firm- -in general terms, equities
and interest bearing liabilities. There is no methodology that yields
the precise cost of capital, but it can be approximated within reasonable
bounds.
The cost of capital was calculated by the "dividend yield plus growth"
method, as follows:
k = -p + g where
k = cost of capital
D = dividend yield
P = stock price
g = growth
Other assumptions made were: (1) long-term interest rates average 9.5 per-
cent, (2) the corporate tax rate is 48 percent, and (3) the growth rate in
dividends will be at least equal to the annual inflation rate which is
estimated at 5 percent.
4 Constr U ct iono f the Cash Flow
The cash flow used in the analysis of BPT (Best Practical Technology) and
BAT (Best Available Technology) effluent control costs was constructed
as follows:
1. Sunk investment (salvage market val >e of fixed -assets plus
net working capital) taken in year t , assumed to be equivalent
to 1976. ~ °
2. After- tax cash proceeds taken for years t-, to t .
3. Annual replacement investment, equal to annual current depreci-
ation taken for years tj to tn. A ten-year depreciation period
was used for the effluent control system.
4. Terminal value equal to sunk investment taken in year t .
5. Incremental pollution control investment taken in year t for
1977 standards and year tg for 1983 standards. °
6. Incremental pollution expenses taken for years t, to t for
1977 standards and years t? to t for 1983 standards, n
if additive to the 1977 standards.
V-7
-------
7. Replacement investment taken in year tn on incremental pollution
investment in BPT on assumption of life of facilities as provided
by EPA.
8. No terminal value of pollution facilities to be taken in year tn.
Land value will probably be assumed to be very snail and/or zero.,
unless the costs provided indicate otherwise.
The length of the cash flow will depend upon the life of the pollution con-
trol technology provided by EPA. The length of the cash flow will be
equal to the life of control equipment specified for 1983 installation.
B. Price Effects
As shown in Figure V-l, price and production effects have interrelated
impacts. In fact, the very basis of price analysis is the premise that
prices and supplies (production) are functionally related variables which
are simultaneously resolved (thus the feedback loop shown in Figure V-l).
The determination of the price impact requires knowledge of demand growth,
price elasticities, supply elasticities, the degree to which regional
markets exist, the degree of dominance exerted by large firms in the in-
dustry, market concentration exhibited by both the industry's suppliers
of inputs and purchasers of outputs, organization and coordination within
the industry, relationship of domestic output with the world market,
existence and nature of complementary goods, cyclical trends in the in-
dustry, current utilization of capacity and, exogenous influences upon
price determination (e.g., governmental regulation).
In vie-,' of the complexity and the diversity of the factors involved in
determining the market price, a purely quantitative approach to the
problem of price effects was not feasible for this study. As a result,
it was necessary to employ value judgments based on experience and on
discussions with industry representatives to estimate the direction and
order of magnitude of price and'supply responses to the change in industry
cost structure which would result from the imposition of pollution controls.
Price responses in the fruit and vegetable processing industry are complex
due to the variety of products processed, the substitution effects within
the processed fruit and vegetable industry and oetween fresh and processed
products, the discretionary changes which the consumer may make in overall
food budgets ana the complex institutional and organization structure of
the industry, nevertheless, an indication of possible price impacts can
be developed through estimating the price increases which would be re-
quired to offset projected effluent control costs. The required price in-
crease car, hp computed by using the NPV analysis described above for in-
cremental pollution cash flow and sales.
V-8
-------
Application of the above NPV procedure to pollution control costs yielded
the present value of those costs (i.e., investment plus operating cost less
tax savings excluding interest expenses). Given this, the price increase
required to pay for pollution control was calculated as
_ (pyp) (iqo)
Ti-T) (WR)
where:
P = required percentage increase in price
PVP = present value of pollution control costs
PVR = present value of gross revenue (sales)
starting in the year pollution control is
imposed
T = tax rate appropriate following imposition
of pollution control
The next step was to evaluate the required price increases against ex-
pectations regarding the ability to raise prices. As pointed out above,
this was a function of a number of factors. In those cases where a few
large plants represent the bulk of production, their required price in-
crease will likely set the upper limit. From this equivalent, which was
quantitative, an initial estimate of expected price increases was made.
C. Shutdown Analysis
The basic shutdown analysis is based upon the technique described above
under Section A and the'expected price increase from the preceding step.
In addition to this analysis, analyses are also made to establish estim-
ated plant closures without the imposition of pollution control or so-
called "baseline" closures. This analysis involves the same financial
analysis technique, without pollution control-.
Based on the results of the NPV analysis of model plants, likely closures
are identified where NPV < 0. Segments or plants in the industry are
equated to the appropriate model (on interpolation) results. Mitigating
items, such as association with a complex, localized raw product sources,
unique market advantages and existing in-place controls and the ability
to finance new non-productive investment are factored in quantitatively
to obtain an estimate of likely closures. BAT costs differ from BPT
costs and closure estimates are required for each condition.
V-9
-------
The impact of these closures is evaluated as the next step (see Figure
V-l). When production impacts are sufficient, the expected prices are
re-evaluated and the shutdown analysis repeated.
D. Production Effects
Potential production effects include changes of capacity utilization rates,
plant closures, and the stagnation of the industry. Plant closures may
be offset in part by increases in capacity utilization on the part of
plants remaining in operation. However, as was pointed out earlier, there
does not appear to be substantial "excess" capacity in the fruit and veg-
etable processing industry when allowances are made for the necessity of
maintaining "surge" capacity as a normal operating requirement. Expected
new production facilities are estimated. The end result is an estimated
production under the conditions presumed for the above closure analysis.
The estimated production under these expectations feeds-back into the price
analysis to verify or revise expected price changes.
E. Employment Effects
Given the production effects of estimated production curtailments — potential
plant closings arid changes in industry growth—a major consideration arises
relative to the impacts of these factors upon employment in the industry.
The employment effects stemming from each of these production impacts in
terms of jobs lost are estimated using the model plant information ,and
Census data on env-"loyinen\. in specified industry segments.
F. Community Effects
The direct impacts of job losses upon a community are immediately apparent.
However, in many cases, plant closures and cutbacks have a far greater im-
pact than just the employment loss. These multiplier effects are reflected
in evaluating payroll losses and income multipliers. For example, the pro-
cessing industry commonly contracts with growers for the production of
those fruits and vegetables processed by individual plants. In these situ-
ations, closure of a plant would mean the loss of a desirable market to
these contract growers—a major loss since production of fruits arid vege-
tables usually results in higher returns than can be obtained with other
crops in the area. Transportation, for both raw products and processed
items, is a major cost and plant closures would have a major impact on
transportation services, especially in sir-aller communities.
V-10
-------
G. Other Effects
Other impacts such as direct balance of payments effects are also in-
cluded in the analysis.
V-ll
-------
VI. POLLUTION CONTROL REQUIREMENTS AND COSTS
Water pollution control requirements and costs used in this analysis were
furnished by the Effluent Guidelines Division of the Environmental Protection
Agency from materials developed by SCS Engineers.I/ These basic data in-
cluded control requirements and costs for individual fruit and vegetable
products and generalized cost information. Specific cost information for
the model plants considered in the impact analysis was developed from these
cost data by EPA, Effluent Guidelines Division.
A. Pollution Contr_o]_ Requirements
Three effluent control levels were considered:
BPT - Best Practical Control Technology Currently Available,
to be achieved by July, 1977
BAT - Best Available Pollution Control Technology Economic-
ally Available, to be achieved by July, 1983
NSPS - New Source Performance Standards, to apply to any source
for which construction starts after the publication of
the proposed regulations for the Standards
Maximum effluent emissions to be permitted under the EPT and BAT control
levels were recommended for individual fruit and vegetable products. The
effluent limitations for NSPS were set equal to those for BAT. Similar
limitations were not provided for combinations of products which are pro-
cessed simultaneously. Therefore, specific limitation guidelines which
conform to the BPT and BAT control levels were not available for all of the
model plants to bo considered in this analysis. In lieu of that informa-
tion, the pre-treatment levels for flow, BOD, and suspended solids are
summarized in Table VI-1, as furnished by EPA Effluent Guidelines Division.
Of the numerous alternative effluent treatment systems available to fruit
and vegetable processors, selected systems were judged by EPA to be super-
ior for meeting the BPT and BAT guidelines. The systems suggested for
attaining BPT guidelines are end-of-pipe biological treatment systems,
either aerated lagoon or activated sludge. Either basic system augmented
with a multi-media filter or chlorination will meet BAT guidelines. The
-' Development Document for Effluent Limitation Guidelines New Source
Performance Standards for the Canned and Preserved Fruit and Vegetable
Industry Point Source Category Phase II, Draft Report, SCS Engineers.
VI-1
-------
Table VI-1. Average rav-' v;astolo;id parameters and average daily ivstev/ater volume during
period of r,iaxin,u:n wasteloetd for model fruit and vegetable processing plants
Corn
Corn
Mushrooms
Mushrooms
F.ushrcoms
Kushrocpis
Pickles
Pickles
Pickles
Sauerkraut
Sauerkraut
Tomatoes
Tomatoes
Tomatoes
Tomatoes
Corn, Peas
Corn, Peas
Corn, Peas
Corn, Peas
Corn, Peas
Corn. Peas
Corn, Fess
Corn, Teas
Corn, Peas
Corn, Peas
Co^n, Peas
Corn, Peas
Broccoli ,
Broccoli.
Broccoli ,
Tomatoes ,
Tor.iotoes ,
Tomatoes ,
Tomatoes ,
Tomatoes ,
Cemmodi t ies
, Green Beans, Carrots
, Green Beans, Carrots
, Green Beans, Carrots
, Green Beans, Carrots
, Green Beans, Carrots
, Green Bccns, Carrots
, Green Beans, Carrots
, Green Beans, Carrots
Cauliflov;cr , Lima Bcens, Spinach
Cauliflower, Lima Beans, Spinach
Caul iflov;er, Lima Beans, Spinach
Dry Beans
D>-y Beans
Dry Beans
Dry Beans
Dry Beans
Plant
type
Canner
Canner
Canner
Canner
Canner
Canner
Canner
Canner
Canner
Canner
Canner
Canner
Canner
Canner
Canner
Canner
Canner
Canner
Canner
Canner
Canner
Canner
Freezer
Freezer
Freezer
Freezer
Freezer
Freezer
Freezer
Freezer
Canner
Canner
Canner
Canner
Canner
to
5,
18,
1,
2,
'j,
1,
6,
10,
6,
9,
1,
4,
25,
150,
3,
12,
37,
120,
TO,
25,
50,
5,
10,
18,
25,
50,
8,
25,
40,
2,
7,
20,
70,
125,
u a 1
ns
500
000
200
500
500
000
500
000
COO
000
500
500
500
030
030
000
000
000
000
000
COO
000
oco
000
000
000
000
009
000
000
000
000
000
000
000
r
m
1
1
2
13
2
7
1
3
1
3
4
8
1
4
7
1
3
11
19
i o,;
Id ]/
.42
.40
.04
.14
.23
.45
.15
.64
.06
.04
.03
.15
.42
.27
.63
.18
.76
.31
.57
.76
.89
.78
.83
.65
.06
.16
.33
.63
.92
.95
.32
.14
.22
.36
.ea
3
3
1
1
• 1
2
2
3
3
3
3
2
2
2
1
1
1
1
1
BOD
niq/1
,200
,200
390
390
390
390
,100
,100
,100
,900
,900
280
280
280
280
,200
,200
,200
,200
,400
,400
,400
,400
,400
,400
,400
,400
410
410
410
470
470
470
470
470
Suspended
So 1 ids i .'!/!
1,500
1,500
210
210
210
210 .
220
220
220
460
460
560
560
560
560
1 ,500
1,500
1,500
1 ,500
1 ,100
1,100
1 ,100
420
420
420
420
420
290
290
290
670
670
670
670
670
continued....
VI-2
-------
Table VI-1. (continued)
Commodities
Cherries, Green Beans, Pears, Plums
Cherries, Green Beans, Pears, Plums
Cherries, Green Beans, Pears, Plums
Cherries, Strawberries, Cane Berries
Cherries, Strawberries, Cane Berries
Cherries, Strawberries, Cane Berries
Pickles, Tomatoes, Dry Beans, Dressings
and Sauces
Pickles, Tomatoes, Dry Beans, Dressings
and Sauces
Pickles, Tomatoes, Dry Beans, Dressings
and Sauces
Pickles, Tomatoes, Dry Beans, Dressings
and Sauces
Brined Products
Brined Products
Brined Products
Potato Chips
Potato Chips
Potato Chips
Potato Chips
Potato Chips
Plant
type
Canner
Canner
Canner
Freezer
Freezer
Freezer
Canner
Canner
Canner
Canner
Canner
Canner
Canner
Dehydrator
De hydra tor
Dehydrator
Dehydrator
Dehydrator
Annual
tons
5,000
10,000
20,000
800
2,000
5,000
2,000
6,000
18,000
60,000
1 ,500
6,000
10,000
1 ,000
2,500
8,000
13,000
30,000
F 1 ow
nild/1
,91
1 .82
3.63
.15
.38
.91
.13
.38
1.17
3.78
.15 1
.64 1
1.06 1
.03 1
.06 1
.10 1
.23 1
.57 1
BOD
mq/1
830
830
830
990
990
990
630
630
630
630
,100
,100
,100
,600
,600
,600
,600
,600
Suspended
Sol ids IVKJ/I
220
220
220
89
89
89
610
610
610
610
220
220
220
1,800
1,800
1,800
1,800
1 ,800
I/
Flow may be converted from million liters per day to million gallons per day by
dividing by 3.785.
Source: Environmental Protection Agency Effluent Guidelines Division.
VI-3
-------
use of spray irrigation for land disposal with zero runoff is also a
recomended system to meet both BPT and BAT guidelines. The components
of these five effluent treatment systems are outlined in Tables VI-2 and
VI-3. Although some processors may elect to use a combination of other
systems, further discussion in this analysis will be restricted to the
effluent treatment systems recommended by EPA.
B. Pollution Control C_osts_
Detailed cost estimates were provided by EPA for the effluent treatment
, systems for each of the model plants to be considered in the impact analysis
From the information provided, total investment costs and total annual cost
were calculated in a manner consistent with other portions of the analysis.
For all effluent treatment systems, except spray irrigation, total invest-
ment cost includes unit capital cost, land cost, and engineering and con-
tingency cost. The cost of land is excluded from total investment cost for
spray irrigation. Total annual cost is the sum of annual operation and
maintenance and annual capital costs. Using the assumptions of ten percent
cost of interest, ten-year life of depreciable assets, zero salvage value,
and one hundred percent recovery of land costs, annual capital cost was
calculated as
[ total_ investment\ +
annual capital cost = ^ 2 ,/ (-10)
nbnland unit capital costs + engineering and contingency costs
Estimated total investment costs and total annual costs are summarized in
Table Vl-4. Cost estimates for any system represent the complete cost of
implementing that system with no previous treatment system in place.
Table VI-5 shows costs per ton of raw product processed.
C. Selection of Effluent Treatment System
Not all direct discharging plants are expected to be able to use the least-
costly effluent treatment system based primarily on the availability of land
for either aerated lagoon or activated sludge. Baseline information pro-
vided by EPA indicates that 92 percent of the plants currently discharging
directly to a v/atercourse will elect to use a biological treatment system to
meet the BPT guidelines. The remaining 8 percent will adopt a zero discharge
land system. Of the plants discharging directly to a watercourse in 1977, 91
percent will use a biological treatment and 9 percent will use zero discharge
land disposal to meet the BAT guidelines. This selection of treatment system
is diatfo ^ed -"n Figure VI-1 . For the impact analysis a high cost system,
act i vat--.I sl:-Hge, and a low cost system, aerated lagoon, will be used. Spray
irrigate . ^tens with runoff will be represented by aerated lagoons for
reasons explained in section D of this chapter.
VI-4
-------
Table VI-2. Summary of treatment components for alternative effluent
reduction systems in fruit and vegetable processing plants
Treatment Component
Spray Irrigation
High head pump station
Transmission main
Retention pond
Distribution system
Tailwater holding pond
Low head pump station
Return transmission main
Aerated Lagoon
Low head pump station
Aerated lagoon
Multi-media filter
Chlorination
Activated Sludge
Aeration basins
Final clarifier
Aerobic digester
Vacuum filter
Aerated polishing pond
Additional units!./
Multi-media filter
Chlorination
Alternative Effluent Reduction Systems to meet:
T'BAT
"Wl
A
X
X
B
X
X
X
X
X
X
X
X
X
X
X
V
A
D
X
X
X
X
X
X
X
X
X
X
X
X
Source: Environmental Protection Agency, Effluent Guidelines Division.
— Snray irrigation system is acceptable to meet BPT and BAT standards
— Additional units required for model plants are listed in Table VI-3,
VI-5
-------
Table VI-3. Summary of additional treatment units required with activated sludge in
model plants of the fruit and vegetable processing industry
en
Modei Plants
Additional Treatment^ Units Required with Activated Sludge
Distended Nutrient No additional
pH Control air flotation addition treatment needed
Corn
''ishrooms
. ickles
Sauerkraut
Tomatoes
Corn, Peas
Corn, Peas, Green Beans, Carrots
Broccoli, Cauliflower, Lima Beans,
Spinach
Tomato, Dry Beans
Cherries, Green Beans, Pears,
Plums
Cherries, Stra\vberries, Cane Berries
Pickles, Tomato, Dry Beans,
Dressinqs and Sauces
Brined products
Potato Chips
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X X
X
X
X
X
X
Source: Environmental Protection Agency, Effluent. Guide! ines Division and prepared by SCS Engineers.
-------
Table VI-4. Estimated total investment (I) and total annual costs (AC) for Best Practicable Control Technology (BPT) and
Best Available Control Technology (BAT) for wastewater effluent treatment for model plants of the
fruit and vegetable processing industry!/
Alternative Effluent
Plant Characteristics
Commodities Plant t'")e
Corn Canner
Corn Canner
Mushrooms Canner
Mushrooms Canner
Mushrooms Canner
Mushrooms Canner
Pickles Canner
Pickles Canner
Pickles Canner
Sauerkraut Canner
Sauerkraut Canner
Tomatoes Canner
Tomatoes Canner
Tomatoes Canner
Tomatoes Canner
Corn, Peas Canner
Corn, Peas Canner
Corn, Peas Canner
Corn, Peas Canner
Corn, Peas, Green
Beans, Carrots Canner
Corn, Peas, Green
Beans, Carrots Canner
Corn, Peas, Green
Beans, Carrots Canner
Corn, Peas, Green
Beans, Carrots Freezer
Corn, Peas, Green
Beans, Carrots Freezer
Corn, Peas, Green
Beans, Carrots Freezer
Corn, Peas, Green
Beans, Carrots Freezer
Corn, Peas, Green
Beans, Carrots Freezer
Broccoli, Cauliflower,
Lima Beans, Spinach Freezer
Broccoli, Cauliflower,
Lima Beans, Spinach Freezer
Broccoli, Cauliflower,
Lima Beans, Spinach Freezer
Tomato, Dry Bean Canner
Tomato, Dry Bean Canner
Tomato, Dry Bean Canner
Tomato, Dry Bean Canner
Tomato, Dry Bean Canner
Cherries, Green Beans,
Pears, Plums Canner
Cherries, Green Beans,
Pears, Plums Canner
Cherries, Green Beans,
Pears, Plums Canner
Cherries, Strawberries,
Cane Berries Freezer
Cherries, Strawberries,
Cane Berries Freezer
Cherries, Strawberries,
Cane Berries Freezer
Pickles, Tomato, Dry Bean,
Dressings & Sauces Canner
Pickles, Tomato, Dry Bean,
Dressings & Sauces Canner
Pickles, Tomato, Dry Bean,
Dressings & Sauces Canner
Pickles, Tomato, Dry Bean,
Dressings & Sauces Canner
Brined Product Canner
Brined Product Canner
Brined Product Canner
Potato Chips Dehydrator
Potato Chips Dehydrator
Potato Chips Dehydrator
Potato Chios Dehydrator
Potato Chips Dehydrator
Annual
tons
5,500
18,000
200
1,500
2,500
5,000
1,500
6,000
10,000
6,000
9,500
1,500
4,500
25,000
150,000
3,000
12,000
37,000
120,000
10,000
25,000
50,000
5,000
10,000
18,000
25,000
50,000
8,000
25,000
40,000
2,000
7,000
20,000
70,000
125,000
5,000
10,000
20,000
800
2,000
5,000
2,000
6,000
18,000
60,000
1,500
6,000
10,000
1,000
2,500
8,000
13,000
30,000
BPT
A - Aerated
I
92
186
47
58
68
84
44
84
107
52
56
40
61
no
303
58
129
253
565
129
225
362
95
146
214
268
383
116
228
300
59
95
173
372
518
99
149
255
44
69
100
40
69
112
255
44
84
107
44
57
63
85
128
Lagoon
AC
19
39
19
22
25
29
21
33
42
20
20
9
13
22
58
15
33
64
156
35
59
98
28
41
60
74
115
40
73
98
22
28
43
83
114
24
33
55
11
21
28
20
28
39
77
21
33
42
19
21
22
28
40
B-Activated
I •
327
562
162
177
190
214
190
252
314
177
177
177
202
352
1,002
264
414
752
1,809
390
582
884
290
390
552
694
1,096
314
544
718
202
290
490
1,069
1,614
264
352
514
177
202
264
214
264
364
624
190
252
314
214
227
240
277
352
Sludge
AC
63
105
60
66
68
76
68
93
113
59
59
36
41
70
197
60
90
158
364
94
139
214
75
100
142
175
274
94
180
246
68
84
115
244
356
63
85
122
39
59
71
76
90
116
203
68
93
113
76
78
80
92
115
BPT 8
C-Sora,y
1
80
138
46
56
62
81
, 56
94
119
46
50
56
80
188
660
60
100
188
412
100
162
262
105
150
225
275
450
150
312
438
70
124
225
580
880
110
162
262
56
78
110
54
78
124
262
56
94
119
46
48
52
62
90
Reduction Systems
BAT^
Irrigation
AC
000)
15
25
14
16
18
23
17
26
33
13
14
10
15
34
116
13
21
37
80
23
34
56
24
32
48
59
94
41
82
113
18
28
42
111
166
22
32
51
11
18
25
16
23
34
69
17
26
33
14
14
16
18
26
BAT
D-Aerated Lagoon
with filtration
I
146
300
71
92
107
139
78
154
213
78
84
74
115
267
806
93
205
410
901
205
370
583
177
264
397
502
745
241
475
550
107
201
369
824
1,176
188
294
476
78
120
190
71
120
218
476
78
154
213
68
85
93
124
194
tc
32
61
35
41
46
55
40
62
78
36
36
17
25
52
153
26
52
98
228
57
94
152
51
72
105
131
204
82
152
193
42
58
90
182
254
45
64
102
21
38
53
37
52
76
145
40
62
78
35
38
40
49
68
E-Activated Sludge
with filtration
!
381
676
186
211
229
269
224
322
420
203
205
211
256
509
1,505
299
490
909
2,145
466
727
1,105
372
508
735
928
1,458
439
792
968
250
396
686
1,521
2,272
353
497
735
211
253
354
245
315
470
845
224
322
420
238
255
270
316
418
AC
75
128
76
85
89
102
87
121
148
74
75
44
54
99
292
72
109
192
436
116
174
268
98
131
187
230
363
136
259
341
88
114
162
343
495
85
116
169
49
76
96
93
114
153
271
87
121
148
92
95
98
113
143
- Spray irrigation is an acceptable system for both BPT and BAT.
Source Environmental Protection Agency, Guidelines Division.
Note: I = Investment
AC = Annual Cost
VI-7
-------
Table VI-5. Effluent treatment costs per ton of raw product processed, by commodity, plant type and size.
Plant Characteristics
^^rcd1 ties Plant t"ne
Corn Canner
Corn Canner
Mushrooms Canner
Mushrooms Canner
Mushrooms Canner
Mushrooms Canner
Pickles Canner
Pickles Canner
Pickles Canner
Sauerkraut Canner
Sauerkraut Canner
Toratoes Canner
Tomatoes Canner
Tomatoes Canner
Tomatoes Canner
Corn, Peas Canner
Corn, Peas Canner
Corn, Peas Canner
Corn, Peas Canner
Corn, Peas, Green
Beans, Carrots Canner
Corn, Peas, Green
Beans, Carrots Canner
Corn, Peas, Green
Beans, Carrots Canner
Corn, Peas, Green
Beans, Carrots Freezer
Corn, Peas, Green
Beans, Carrots Freezer
Corn, Peas, Green
Beans, Carrots Freezer
Corn, Peas, Green
Beans, Carrots Freezer
Corn, Peas, Green
Beans, Carros Freezer
Broccoli , Cauliflower,
Lima Beans, Spinach Freezer
Broccoli, Cauliflower,
Lima Beans, Spinach Freezer
Broccoli, Cauliflower,
Lima Beans, Spinach Freezer
Tomatoes, Dry Beans Canner
Tomatoes, Dry Beans Canner
Tomatoes, Dry Beans Canner
Tomatoes, Dry Beans Canner
Tomatoes, Dry Beans Canner
Cherries, Green Beans,
Pears, Plums Canner
Cherries, Green Beans,
Pears, Plums Canner
Cherries, Green Beans,
Pears, Plums Canner
Cherries, Strawberries,
Cane Berries Freezer
Cherries, Strawberries,
Cane Berries Freezer
Cherries, Strawberries,
Cane Berries Freezer
Pickles, Tomato, Dry Bean,
Dressings & Sauces Canner
Pickles, Tomato, Dry Bean,
Dressings & Sauces Canner
Pickles, Tomato, Dry Bean,
Dressings & Sauces Canner
Pickles, Tomato, Dry Bean,
Dressings & Sauces Canner
Brined Product Canner
Brined Product Canner
Brined Product Canner
Potato Chips Oehydrator
Potato Chips Dehydrator
^otato Crnps Dehydrator
Potato Clips Dehydrator
Potato Chips Oehydrato'-
Annual
tons
5,500
18,r>00
200
1,500
2,500
5,000
1,500
6,000
10.000
6,000
9,500
1,500
4,500
25,000
150,000
3,000
12, COG
37,000
120,000
10,000
25,000
50,000
5 000
10,000
18,000
25,000
50,000
8,000
25,000
40,000
2,000
7,000
20,000
70,000
1'5,COO
5,000
10,000
20,000
800
2,000
5,000
2,000
6,000
18,000
60,000
1,500
6.000
10,000
1,000
2,500
8,000
13, "00
30,000
- Spray irrigation is an acceptable system
Source Environmental Protection
A - Aerated
I
S16 73
10.33
235 00
38.67
27 20
16 80
29 33
14.00
10 70
8 67
5.89
26.67
13.56
4 40
2 02
19 33
10 75
6 84
4.71
12.90
9.00
7 24
19 00
14.60
11 89
10 72
7.66
14 50
9 12
7.50
29 50
13.57
8.65
5.31
4 14
19.80
14 90
12 75
55.00
34 50
20.00
20.00
11.50
6.22
4.25
29 33
14 00
10 70
44.00
22.80
7.88
6.54
4.27
BP
Lagoon
AC
$3 45
2.17
95.00
14 67
10.00
5.80
14 00
5 50
4 20
3.33
2 11
6.00
2.89
0 88
0 39
5 00
2.75
1 73
1.30
3 50
2 36
1 96
5.60
4 10
3.33
2.96
2.30
5.00
2.92
2 45
11 00
4.00
2 15
1 19
0.9!
4.80
3 30
2.75
13.75
10.50
5.60
10.00
4 67
2 17
1.28
14.00
5.50
4 20
19 00
8.40
2.75
2 15
1 33
t,
T
B-Activated
1
$59.45
31 22
810.00
118.00
76.00
43.00
126 67
42.00
31.40
29.50
18.63
118.00
44.89
14 08
6.68
88.00
34.50
20 32
15.08
39.00
23.28
17 68
58.00
39.00
30.67
27.76
43 84
39.25
21 76
17 95
101.00
41.43
24.50
15 27
12 91
52.80
35.20
25.70
221 25
101.00
52 80
107.00
44 00
20.22
10.40
126 67
42.00
31 40
214.00
90.80
30 00
21 31
11.73
Hernative Effl jent
Slucae
AC
$11 45
5 83
300 00
44.00
27.20
15.20
45 33
15 50
11.30
9.83
6.21
24.00
9.11
2.80
1.31
20.00
7.50
4.27
3 03
9.40
5.56
4 28
15.00
10 00'
7.89
7.00
S 48
11.75
7 20
6.15
34.00
12.00
5.75
3.49
2.85
12.60
8 50
6.10
48.75
29.50
14 20
38.00
15.00
6.44
3.38
45 33
15.50
11.30
76.00
31 20
10.00
7.08
3 83
3PT 8
C-Sor3y
T
$14.55
7 67
230 00
37.33
24.80
16.20
37.33
15.67
11.90
7.67
5.26
37.33
17.78
7 52
4.40
20.00
8.33
5.08
3.43
10 00
6.48
5.24
21 00
15 00
12.50
11.00
9.00
18.75
12.48
10.95
35.00
17.71
11 25
8 28
7.04
22.00
16 20
13.10
70.00
39.00
22.00
27.00
13.00
6.89
4.37
37.33
15.67
11.90
46.00
19.20
6.50
4 77
3.00
for both BPT and BAT
Agency, Effluent Guidelines Division.
Reduction Systems
BAlI'
Irrigation
' AC
$2 73
1.39
70.00
10.67
7.20
4.60
11.33
4.33
3 30
2.17
1.47
6.67
3.33
1.36
0.77
4.33
1.75
1 00
0.67
2.30
1.36
1 12
4.80
3.20
2.67
2.36
1.88
5.13
3.28
2.83
9.00
4.00
2.10
1 59
1.33
4.40
3.20
2.55
13.75
9.00
5 00
8 00
3.83
1.89
1.15
11.33
4.33
3 30
14.00
5.60
2.00
1.38
0.87
Note • I
AC
D-Aerated Lagoon
with filtration
1
$26 55
16.67
355.00
61.33
42.80
27.80
52.00
25 66
21 30
13 00
8 84
49 33
25 56
10 68
5 37
31 00
17 08
11 08
7 51
20 50
14 80
11.66
35.40
26.40
22 06
20.08
14 90
30.13
19 00
13 75
53.50
28.71
18.45
11 77
9 41
37.60
29.40
23.80
97.50
60.00
38.00
35.50
20.00
12.11
7.93
52.00
25.57
21.30
68.00
34.00
11.63
9.54
6.47
AC
$5.82
3 39
175.00
27.33
18.40
11.00
26.67
10.33
7.80
6.00
3.79
11.33
5 56
2.08
1.02
8.67
4.33
2.65
1 90
5.70
3.76
3.04
10.20
7.20
5.83
5.24
4.08
10.25
6.08
4.83
21.00
8.29
4.50
2.60
2.03
9.00
6.40
5.10
26.25
19.00
10.60
18.50
8.67
4.22
2.42
26.67
10.33
7.80
35.00
15.20
5.00
3.77
2.27
BAT
E-Activated Sludge
with filtration
!
$69.27
37.56
930.00
140.67
91.60
53.80
149 33
53.67
42.00
33.83
21.58
140.67
56.89
20.36
10.03
99.67
40.83
24.57
17.88
46.60
29.08
22.10
74.40
50.80
40.83
37.12
29.16
54.88
31.68
24.20
125.00
56.57
34.30
21.73
18.18
70.60
49.70
36.75
263.75
126.50
70.80
122.50
52.50
26.11
14.08
149.33
53.67
42.00
238.00
102.00
33.75
24.31
13.93
AC
$13.64
7.11
380.00
56.67
35.60
20.40
58.00
20.17
14.80
12.33
7.89
29.33
12.00
3.96
1.95
24.00
9.08
5.19
3.63
11.60
6.96
5.36
19.60
13.10
10.39
9 20
7.26
17.00
10.36
8.53
44.00
16.29
8.10
4.90
3 96
17.00
11.60
8.45
61.25
38.00
19.20
46.50
19.00
8.50
4.52
58.00
20.17
14.80
92.00
38.00
12.25
8.69
4.77
= Investment
= Annual
Cost
VI-8
-------
Figure VI-1. Selection of effluent treatment systems by direct dischargers
Baseline
To meet BPT
To meet BAT
1974
1977
1983
Direct discharge to
a watercourse
/activated sludge~\
I aerated lagoon r
cease operation/
zero discharge land
91%
/activated sludge\
->( aerated lagoon
V cease operation/
^•zero discharge land
Land with direct dis-
charge of runoff
land with direct dis-
charge of runoff
cease operation
land with direct dis-
charge of runoff
cease operation
VI-9
-------
D. Status of Wastewater Treatment
EPA Effluent Guidelines Division has estimated that, under the baseline
conditions, approximately 85 percent of the fruit and vegetable processing
plants have either tie-ins with municipal systems or have zero discharge
land disposal systems (Table VI-6). In either case, further treatment re-
quirements are not expected in terms of the specific limitation guidelines
on which this study was based.
The remaining 15 percent of the plants are direct dischargers and will be
required to conform to the limitation guidelines. Eighty percent of these
plants discharge directly to a water course whereas the remaining 20 per-
cent utilize a land treatment system—spray irrigation—with direct runoff
to a water course. These 20 percent of the direct dischargers are repre-
sented by aerated lagoons in the impact analysis for two primary reasons.
First, EPA Effluent Guidelines has indicated the 20 percent, estimate is
likely high. Second, spray irrigation systems, excluding land costs, are
somewhat similar to the aerated lagoon system.
All but two percent of the direct discharge plants currently have in place
some form of treatment system. This two percent of the plants will be the
only plants to expend the total estimated cost to acquire a system which
will meet BPT guidelines. For each of the remaining plants, the additional
cost for a treatment system will depend on the level of control system
currently in place. As is summarized in Table VI-7, 40 percent of the
direct discharge plants have in place minimum control systems. These
systems are defined as screening with a two-day retention pond that is not
aerated. To improve its present system to meet BPT guidelines, each of
these plants will expend 85 percent of the total cost for a complete system.
Almost half (44 percent) of the plants currently have moderate control
systems in place. Moderate control is defined as screening with a ten-day
retention pond that is aerated to provide odor control. The additional
cost for each of these plants is 50 percent of the total system cost. The
remaining 14 percent of the plants currently have in place an acceptable
control system that will meet BPT guidelines. All of the direct discharge
plants will incur additional costs to improve their treatment systems from
BPT to the BAT level of controls.
The 15 percent of fruit and vegetable plants which are direct dischargers
under the baseline conditions includes 334 of the 2,202 plants considered
in this report. EPA Effluent Guidelines Division provided an estimate
of the distribution of these plants between model plants which were then
placed into industry groups. Table VI-7 illustrates the estimated number
of direct dischargers by model plant and industry group for the fruit and
vegetable processing industry.
The percent direct discharge plants are of total plants represented by a
model ranges from a low of 7.0 percent for the mushroom, dehydrated fruit
and vegetable and potato chip models to a high of 25.0 percent for the
sauerkraut model.
VI-10
-------
Table VI-6. Estimated present and future oercent of fruit and vegetable processors
using each type of disposal system
Percent of Processors using Disposal System o_n Given date
July, 1974 July, 1977 July, 1933
Direct dischargers (Excluding Land
treatment systems) - 12 11 10
Land treatment system with direct
discharge of runoff
Zero discharge land treatment systems
Discharge to municioal system
3
30
55
3
33
53
3
35
52
Source: Environmental Protection Agency, Effluent-Guidelines Division and SCS Engineers.
-------
Table VI- 7. Estimated percentages of direct discharginq fruit and vegetable D^ocessing plants
with various levels of control systems in pl;;ce and corresponding cercentaaes
of additional syst\_i"s cost r.o reac.n 3rT.
Percent of alternative
Level of Percent of direct effluent systems cost
C?niv'ol Systems "ofinitions disc'":;rog plants to re'--'", G?T
Zero Control Systems no systcn 2 ICO
Minimun Control Systems screeni-a with 2-day
retenti -)n pond 40 85
Moderate Control Systerr.s screening v;ith aerated,
10-dsy retention cor,d 44 50
Acceptable Control Systems anv sys~en that rrcets
the oln-is lines 14 0
Source: Environmental Protection Agency, Effluent Guidelines Division.
-------
E. Application of Effluent Control Guidelines
1. Plants processing 2,000 tons or less or raw product per year are not
covered by the interim final or proposed guidelines. These plants
were excluded because neither aerated lagoons or activated sludge
systems are economically feasible for these small plants. The closure
rate for these plants, resulting from the guidelines as analyzed,
was projected to be 52 percent for BPT with an additional 19 percent
for BAT.
2. Plants processing from 2001 through 10,000 tons raw product per year
must meet proposed BPT and BAT guidelines, but are not covered by
interim guidelines. For this group of plants, the technology required
to meet proposed BAT guidelines is the same as for proposed BPT.
Therefore, it has been assumed that the additional costs due to BAT
are negligible and that there would be no incremental impacts due to
BAT.
3. Plants processing more than 10,000 tons raw product per year must meet
both interim final and proposed BPT guidelines and proposed BAT guide-
lines. BPT guidelines for this group of plants are identical for both
the interim final and proposed guidelines. Proposed BAT guidelines for
this group of plants require that filtration be added to the aerated
lagoon or activated sludge treatment.
Detailed baseline conditions were established by combining the information
concerning the level of control system currently in place, Table VI-7, and
the number of direct discharge plants, Table VI-8. An assumption, necess-
itated by insufficient information, was made that the four levels of
control systems in place was uniform throughout the industry.
Table VI-9 summarizes the number of direct dischargers by industry group
and level of controls in place. Out of an estimated 330 direct discharging
plants, 47 or 14% have acceptable controls in place to meet BPT standards
and six plants or 2% of direct dischargers have zero controls in place.
VI-13
-------
Table VI-8. Estimated direct discharging plants in relation to industry group and model plants
SIC
Industry group code
Canned specialties 2032
Canned fruits S vegetables 2033
Pickles, sauces, & dressings 2035
Frozen fruits & vegetables 2037
Dehydrated fruits & veg. 2034
and soup mixes
Potato and corn chips 2099
Total - Industry Groups
Model Plant
Reprocess
Reprocess, brine
Total
Corn
Mushrooms
Sauerkraut
Tomatoes
Blanched vegetables
Blanched & peeled vegetables
Blanche-] vegetables, pitted
and peeled fruits
Reprocess
Reprocess brine
Total
Pickle5
Brined products
Reprocessed
Reprocessed and brine
Total
Blanched
Blanched & peeled vegetables
Pitted, peeled § nonbasic
(berries) fruit
Total
Potato chips
Potato chips
All model plants
Total
plants
152
51
203"
19
58
29
96
134
85
144
259
134
959
129
74
178
114
435"
32
62
35
T2T
160
255
2,202
Direct
A of each
model!/
16.7
16.7
T6.7
7.7
7.0
25.0
20.29/
20. C£7
20.5
14.3
16.7
16.7
16.9
14.0
19.5
16.7
16.7
T6.4"
20.0
20.0
17.9
TsTe"
7.0
7.0
15.0 1
di scharqers
No.
25
Q
"T4"
1
4
7
19
27
18
21
43
22
162"
18
14
30
19
81"
6
12
6
24
1 1
18
330
» of industry
group
12.3
4.4
T"6.7
0.1
0.4
0.7
2.0
2.8
1.9
2.2
4.5
2.3
16.9
3.6
2.8
6.1
3.9
16.4
4.6
9.3
4.7
TO"
7.0
7.0
15.0
- Source: EPA, Effluent Guidelines Division.
2/
- Although EPA, Effluent Guidelines Division, estimated 6.9 percent of total blanched vegetable model plants as
being direct dischargers, it was felt that 20 percent more nearly reflected this model.
-------
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-------
VII. IMPACT ANALYSIS
The impacts considered in this analysis are as follows:
A. Price effects
B. Financial effects
C. Production effects
D. Employment effects
E. Community effects
F. Foreign trade effects
These impacts were analyzed for each of the model plant situations described
in Chapters II and III and were based on physical and financial character-
istics and performance of the model plants and pollution control costs as f
presented in Chapter VI.
A. Price Effects
General pricing processes and pricing relationships for the fruit and vege-
table processing industry were discussed in Chapter IV. It was pointed out
that short run price changes are strongly influenced by supply-related factors
but that long-run changes in price are influenced by changes in consumer
preferences and tastes, population, income, technology and by factors which
affect the cost of these products to the consumer. Although per capita con-
sumption of processed fruits and vegetables increased steadily during the
1960's, there has been a leveling off and slight decrease in 1974 and 1975
as increasing prices are meeting greater consumer resistance. Consumers are
moving back to increased consumption of fresh products and there has been a re-
surgence of interest (as evidenced by spectacular increases in garden seed sales)
in home gardening. For certain commodities (e.g. mushrooms, frozen strawberries,
tomato paste — see Foreign Trade Impacts) imports have increased rapidly as
distributors seek lower-cost sources of supplies.
In general, it was concluded that processors would find little opportunity
to pass increased costs, associated with effluent -treatment requirements,
backward to growers. Processor-grower margins have been decreasing, there is
increasing pressure on supplies, many products are produced under processor-
grower contracts or are covered by marketing orders which permit a degree of
supply regulation by growers and finally, most growers have other production
alternatives which may be more attractive if raw fruit and vegetable prices
were reduced.
The ability of processors to pass costs forward to consumers in the form of
higher prices is limited.
VII-1
-------
In the short-run, there would appear to be only limited opportunities
for such cost transfer. The fruit and vegetable processing industry is
very competitive and although large firms exist, no one is dominant.
In addition, food prices have risen to the point where additional price
increases are meeting strong consumer resistance. Even though processed
food prices have increased in recent years, reports from processors indicate
that the rate of increase has been lower than the rate of increase in their
costs. As a result, processors have already been forced to absorb a part
of the cost increases which they have experienced.
In the long-run, the ability of processors to pass forward cost increases
in the form of higher consumer prices will depend partly on the demand
characteristics of the individual products. In general, better opportunities
for price increases would exist for those products having relatively low de-
mand elasticities. Even under long-run conditions, it is not expected that
a complete pass-through of costs will be possible since competitive con-
ditions in the industry coupled with consumer resistance to increasing
prices would restrict opportunities for price increases. As a result, pro-
cessors would be forced to absorb out of profits most of the increased costs
of effluent controls.
1. Price Increases Required to Offset Effluent Control Costs
A series of model plants were developed for representative segments of the
fruit and vegetable processing industry. For these plants financial costs
and returns were synthesized and rates of return, cash flows and net present
values were calculated to measure the financial performance of these plants.
Effluent control costs were developed by EPA for this same structure of model
plants. Based on these financial profiles and effluent control costs, the
price increases, at the plant level, which would be required to offset effluent
control costs, were calculated. Table V1I-1 summarizes the required price
increases for the model plants under specified effluent treatment systems.
Table VII-1 shows the price increase required to pay for incremental effluent
control costs by type of plant, size of plant, commodities processed, type of
effluent treatment system and extent of in-place treatment facilities and treat-
ment level (BPT or BAT). The indicated price increases would relate to f.o.b.
plant prices assuming that all plants could pass such price increases on to dis-
•tributors, retailers and finally to the consumer. However, competitive con-
ditions in the industry would limit the price increase to the lower levels
required by larger plants, if in fact these plants were able to recapture
these costs through higher prices.
The ability of larger firms to pass forward increased costs is illustrated by
a recent (July, 1975) article in the Wai 1 Street Journal which quoted the
president of a major fruit and vegetable processor with the statement that
his firm would increase product prices to the wholesale and retail trade about
five percent in response to overall cost increases expected to be about five
to six percent. This same article indicated that this five percent increase
VII-2
-------
Table VII-1. Price increase required to offset incremental pollution control costs, aerated lagoon and activated
sludge at three in-place treatment levels
CDPN
MUSHROOMS
PICKLE
SAUERKRAUT
CCSN-PEA
C3RN-PEA-GB-CARROT
CO»N-P£A-G8-CARROr
BPQC-CLFL-LB-SPIN
TOMATO-CRY SEAN
C HE RRY-GS-P EAR-PLUM
CHERRY-STR8-CNBR
IX££
CAN
CAN
CAN
CAN
CAN
CAN
CAN
FREZ
FPEZ
CAN
CAN
FREZ
_LCitf-
5500
18000
200
1500
2500
5000
1500
6000
10000
6000
9500
1500
4500
25000
150000
30CO
12000
37000
120000
10000
25COO
50000
5COO
10000
13000
25000
50000
8000
25COC
40000
2000
7010
20000
7COOO
125000
5000
10000
2C03C
80C
2000
5000
LAG
_££!_
3.9*
2.2
7.9*
1.3
0.9
0.5
2.3?
0.9
0.7
1.3*
1.3
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1.5
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1.8
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12.8*
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1.6
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13.8*
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32.8*
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1.5
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7.8
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4.7
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7.8
7.4
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3.5*
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15.5*
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_fl£I_
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1.0
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1.6
1.2
2.9t
1.6
0.8
-------
Table VII-1 (continued)
PICKLE-TCMT-CP-OESA CAN
BRINEC PRODUCT
POTATO CHIP
CAN
DtHY
.IC£iS_
2000
bCOO
1 8030
6COOO
1500
6000
icocn
1000
2500
8000
13000
30000
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_a£i_
i.i*
0.6
C.3
0.2
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2.2
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1.7
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D G E
_a
-------
was substantially below the 25 percent increase in prices of last season
which were in response to a 37 percent increase in costs.
Several generalizations can be observed from the data in Table VII-1.
1. , Price increases required to offset effluent treatment costs using
activated sludge systems are two to three times those required by
using aerated lagoons.
2. Price increases required to offset effluent control costs when no
treatment systems were in place were 84 percent of costs when "moderate"
controls were in place and were 48 percent of costs when "minimum"
treatment systems were in place.
3. Price increases required to offset BPT costs were 67 percent of those
required by BAT for aerated lagoons and 87 percent for activated
sludge systems.
4. Price increases required to offset effluent control costs for extra
small plants, 2,000 tons and under raw product, were generally severe
(4 percent or above) at BPT and BAT levels and for small plants, 5,000
tons raw product and under, were generally severe at BAT levels.
Although the industry will attempt to recover costs through price increases
where possible, it will be impracticable for each plant to change prices in-
dependently. Two industry-related factors will limit the ability of plants
to increase prices: (1) a high proportion of the industry (estimated at 55
percent) is currently discharging through municipal sewers, in most cases at
costs which are apparently below those incurred by plants with their own
waste treatment systems and (2) larger plants, with lower unit waste treat-
ment costs would tend to establish a ceiling, in terms of price increases,
which would limit the ability of smaller plants to pass effluent costs for-
ward. Assuming thai direct dischargers would be limited to price increases
required by the largest plants, the situation would be as shown in Table
VII-2.
With aerated lagoons at BPT levels, all model plants except corn (2.2),
sauerkraut (V.3), corn-pea-green bean-carrot freezers (1.9) and brined pro-
ducts (2.4) would be restricted by competition to a price increase of one
percent or less. The figures in ( ) indicate the limiting price increases
for these plants. With aerated lagoons at BAT levels, mushrooms, tomato,
corn-pea, broccoli-1ima bean-cauliflower-spinach freezers, tomato-dry bean
plants, cherry-strawberry-cane berry freezers and pickle-tomato-dry bean-
dressings and sauces plants would be at the one percent or below level and
all other plants would be above the one percent level.
For activated sludge systems only the pickle-tomato-dry bean-dreasings and
sauces plant would be restricted to a one percent price increase. Most other
plants fall in the range between 1.1 and 5.0 percent except for corn canners
and brined product plants and the corn-pea-green bean-carrot freezing plant
at the BAT level.
VII-5
-------
Table VII-2. Limits to price increase, direct dischargers, as established by largest plants, no system in place
1% or less
Lagoon Act. Sludge
Model Plant
Corn
Mushrooms
Pickle
Sauerkraut
Tomato
Corn, pea
Corn, pea, green bean, carrot
Corn, pea, green bean, carrot
Broc., Clfl, lima bean, spinach
Tomato, dry bean
Cherry, green bean, pear, plum
Cherry, strawberry, cane berry
Pickle, torn., dry bean, 0 & S
Brined product
Potato chip
Type
C
C
C
C
C
C
C
F
F
C
C
F
C
C
D
BPT
X
X
X
X
X
X
X
X
X
X
X
BAT BPT BAT
X
X
X
X
X
X
XXX
X
1.1 - 2.0%
Lagoon Act.
BPT BAT BPT
X
X X
X X
. X
X
X
X
X
X
X X
X
X
Sludge
BAT
X
X
X
X
X
X
Price increase limit (%)
2.1 - 3.0% 3.1 - 5.0% 5.1 or greater
Lagoon Act. Sludge Lagoon Act. Sludge Lagoon Act. Sludge
BPT BAT BPT BAT BPT BAT BPT BAT BPT BAT BPT BAT
XX XX
X
X X
X
X X
X XX
X
X X XX
-------
Given these assumptions concerning the ability of impacted plants to pass
increased costs forward in terms of higher prices, it must be concluded
that those segments of the fruit and vegetable industry which are most
highly impacted by interim final and proposed effluent controls would not
be able"to overcome these added costs by increases in the prices of pro-
ducts sold.
B. Financial Effects
In order to measure the financial impacts of interim final and proposed
effluent controls on the fruit and vegetable canning, freezing and pre-
serving industry, income rates of return and cash flows were calculated
for the various sizes and types of model plants with and without effluent
control costs. Rates of return were calculated on model plant invested
capital and on sales. Analyses made include the following:
1. After-tax income
2. After-tax return on sales
3. After-tax return on invested capital
4. Annual cash flow
5. Net present values.
1. After-Tax Income
Table VII-4 shows the after-tax income (in $000) for each condition of each
model plant for the alternative treatment systems. These income figures
which assume no price change can be compared to the baseline situation before
the imposition of pollution control costs.
guidelines
The very
low or
In each case, the income goes down as the plants Move from BPT
to BAT and from aerated lagoon treatment to activated sludge.
small plants in eight of the model plant groups show extremely
negative income under most conditions of pollution control.
2. After-Tax Return on Sales
In Table VII-5 , the after-tax return on sales that would result under varying
conditions of pollution control, assuming no price changes were made. From
this table, a comparison of the before or baseline condition can be made
with the many options of installed pollution control.
In the baseline case, the return on sales varies from 0.7 percent to a
high of 5 percent for the full range of model plants. Depending on the
treatment assumed, the after condition shows a very wide range from a low
of -27.7 percent to a high of 4.3 percent. The average drop is well over
one percent.
VII-7
-------
3. After-Tax Return on Invested Capital
All model plants show a positive return on the after-tax income related to
invested capital in the baseline case in Table VI1-6. The baseline range
varies from a low of 0.6 percent to a high of 10.3 percent. With the
added costs and added investment of treatment facilities, these return
figures go down to a low of -5.3 percent and a high of 9.6 percent for
aerated lagoon treatment. For activated sludge treatment, the figures go
down further to the range of -13.2 percent to 9.1 percent.
4. Cash Flow
Model plant cash flows in $000's are shown in Table VII-7, both before
imposition of treatment costs (baseline) and after imposition of treatment.
The after treatment cash flows are shown for two types of treatment:
aerated lagoons and activated sludge for both BPT and BAT and at three
different levels of partial treatment.
Four of the smallest models show a negative cash flow under some of the
treatment configurations. These are the same plants that show negative'
returns on sales and invested capital in previous analyses.
The other 49 models, however, do have positive cash flows under the assump-
tion of no price change and the various levels of treatment, imposed.
5. Net Present Value
The results of the net present value of the model plants before and after
the imposition of BPT and BAT control levels are shown in Table VII-B
These analyses were run with an assumed discount rate of 8 percent which
approximates the cost of capital for this industrial segment. From this
table, it appears that five specific groups of model plants, i.e. corn,
pickle, broccoli - cauliflower - lima beans - spinach, cherry - strawberry -
cane berry, and potato chip processing plants will not achieve this discount
'rate after the imposition of controls.
Only one group of plants, cherry - strawberry - cane berry, do not achieve
this discount rate in the base case. These net present value results as a
whole show a different pattern than do the previous five analyses in that
the negative results show up for all sizes of plants or a particular com-
modity or group of commodities rather than being primarily related to
size of plant.
VII-8
-------
( 6. Rationale for Use of "Average Year" Profitability
Financial data developed for this project from industry surveys, were
based on the year 1973. Profitability levels were given for 1973 and
also indicate the profitability during the best and worst year, 1969-
1973. These data, plus other information, indicate that for most seg-
ments of the canning and freezing industry, 1973 was a better-than-
average year. For three categories of plants: canning only, freezing
only and canning and freezing, over 50 percent of the survey respondents
identified 1973 as the high profit year and 1969 as the year of lowest
profits.
This profitability relationship is confirmed by a report prepared for
the National Canners Association in March, 1975, by Touche Ross and
Company, up-dating a previous profitability series. Table VII- shows
the results of this analysis. The data show clearly that, during the
past five years, 1973 was clearly the most profitable, with pre-tax
return on sales of 5.5 percent. It is also apparent that an average return
on sales is 4.4 percent -- 80 percent of the 1973 level. The 4.4 percent
average return existed for the three-year average, 1971-73 10-year
average, 1961-70 and the 13-year average, 1961-73.
On the basis of these data, it was concluded that 1973 (5.5 percent)
was a better-than-average year, that 4.4 percent return was more
representative.
Although the returns data shown in Chapter III are based on 1973 as
represented in the model plant financial analysis, for the purposes of
the economic imoact analysis, the profit before tax in the model plants
has been reduced to 80 percent of the 1973 level by increasing costs by
about one percent in the plant budgets to accomplish this change.
Two exceptions to this change were made. First, mushroom canners do not
look on 1973 as an exceptionally good year. Early in 1972 began what is
known as the "year of recall" and this negative effect continued into
1973. These recalls were started by the discovery of contaminated
product for one canner and the publicity which this problem created
resulted in reexamination of many canners and many batches. The adverse
publicity attendant to this contamination problem, even though the con-
• tamination was infinitesimal in magnitude, resulted in significant recalls
affecting both sales and prices, increasing costs, reducing profits and
resulting in plant closures. Since 1972, approximately 10 mushroom
canners have closed permanently or temporarily -- some of the closures
definitely due to the recall. As a result, 1973 profitability levels were
used for mushroom plants.
The second .exception is potato chip processors. Indications from industry
returns are that 1973 was no better than an average year while 1971 and
1972 were considered to be better-than-average in terms of profitability.
Therefore, for potato chip processors, 1973 profitability levels were
used in the impact analysis.
VII - 9
-------
7. Availability of Capital
The ability of a firm to finance new investment for pollution abatement is
a function of the ability of the firm to generate new capital from one or
more of the following sources: (1) borrowings from outside sources, (2) new
equity capital generated through the sale of common or preferred stock,
(3) internally generated funds - retained earnings plus the stream of funds
allocated to depreciation of fixed assets.
For each of the three major sources of new investment, the most critical
set of factors is the financial condition of the individual firm. For
debt financing, the firm's credit rating, earnings record over a period
of years, existing debt-equity ratio and the lenders' confidence in manage-
ment will be major considerations. New equity funds through the sale of
securities will depend upon the firm's future earnings as anticipated by
investors, which in turn will reflect past earnings records. The firm's
record, compared to others in its own industry and to firms in other similar
industries, will be a major determinant of the ease with which new equity
capital can be acquired. In the comparisons, the investor will probably
look at the trend of earnings for the past five or so years.
Internally generated funds depend upon the margin of profitability and
the cash flow from operations. Also, in publicly held corporations, stock-
holders must be willing to forego dividends in order to make earnings
available for reinvestment.
The condition of tha firm's industry and general economic conditions are
also major factors in attracting new capital. The industry will be com-
pared to other similar industries (other manufacturing industries) in
terms of net profits on sales and on net worth, supply-demand, relation-
ships, trends in production and consumption, the state of technology,
impact of government regulation, foreign trade and other significant
variables. Declining or depressed industries are not good prospects for
attracting new capital. At the same time, the overall condition of the
domestic and international economy can influence capital markets.
The food canning and freezing industries in the United States are highly
competitive with a large number of relatively small firms. Profit margins
on sales are low and highly volatile both for individual plants and for
the industry as a whole. Detailed information on the profit position of
respective type and size companies is simply not available and only broad
industry averages can be obtained.
The fruit and vegetable canning, freezing and preserving industry is
characterized by a large number of small single plant firms with approx-
imately 55 percent of the total number firms being categorized as small.
However there is a substantial concentration of production in the larger
firms, as follows.
VII-10
-------
Percent of total value of shipment
SIC Industry Segment 20 largest firms 50 largest firms
^
2032 Canned specialties 94 99
2033 Canned fruits & vegetables 52 70
2035 Pickles, sauces & dressings 62 80
2037 Frozen fruits & vegetables 73 93
2034 Dehydrated fruits & vegetables 75 96
2099 Potato and corn chips 72 87
Total industry 66 83
Profits in the industry vary substantially from firm to firm and from year
to year. In general profitability levels for small plants are lower than
for larger plants (see Tables III-2 - 111-25, pages 111-20 - 111-34). The
stability of these small firms is largely dependent on seasonal variations
in supplies of raw product and year-to-year variations in product prices.
In contrast to these small, single plant firms, which are highly impacted
by local conditions, the larger firms are more highly diversified, both in
terms of products processed and locations. Many of the larger firms are
also major processors of non-fruit and vegetable items, e.g. fish, canned
puddings, snack foods, etc. These products not only provide product diversi
fication, but in some instances permit "off-season" utilization of plant
and equipment.
Firms in the fruit and vegetable processing industry are characteristically
seasonal in their financing requirements for working capital. This season-
al ity factor makes it necessary for the short-term borrowing of funds to
finance seasonally produced commodities that are marketed throughout the
year. This need for short-term funds further limits the ability of most
members of the industry to obtain long-term financing for' purposes such as
capital expenditures for pollution abatement.
In addition to the additional demand for capital as a result of meeting the
pollution abatement requirements, the industry is currently faced with sub-
stantial requirements for additional capital to meet:
a. Other Federal regulations (FDA, FEA, USDA and OSHA) which have
caused and will continue to cause increased costs.
b. The conversion of energy systems to alternate fuels and improved
technology to reduce total energy consumption.
In a recent study completed by Development Planning and Research Associates,
Inc. for the National Commission on Water Quality!/ , it was estimated that
— Economic Impact of Water Pollution Controls on Selected Food Industries
Volume IV. The Fruit and Vegetable Processing Industry, National Com-
mission on Water Quality, Contract No. WQ SAC011, June, 1975.
VII-11
-------
capital investments required for pollution control, as a percent of pro-
jected baseline capital investments (without pollution control), for BPT
(1977) and BAT (1983) by industry segments were as follows:
Pollution control investment as percent
of projected baseline capital investment
Segment
Canned specialties
Canned fruits & vegetables
Dehydrated fruits & vegetables
Pickles, sauces & dressings
Frozen fruits & vegetables
BPT (1977)
(X)
5.4
53.3
58.5
19.9
19.6
Incremental
BAT (1983)
1.7
24.1
37.5
9.7
11.8
Baseline capital investments represent those which the industry would
have made in the absence of pollution control requirements. Such
investments would include expenditures for new plants, modernization
of plants and equipment and other capital additions made in the industry.
As illustrated by these data, the required investment for pollution control
(for direct discharges only) for BPT represents an amount equivalent to
20 to 50+ percent of the entire projected capital investment for all industry
segments except canned specialties. In addition, the increment required to
reach BAT equals 10 to 37.5 percent for all segments except canned special-
ties.
There has been a steady decline in the number of plants in the fruit and
vegetable processing industry. For those segments included in this analysis,
the total number of plants dropped from 3166 in 1958 to 2379 in 1972, a
decrease of 787 pi an Is or 25 percent.
Most of this decline has
by the following data.
come from the closure of small plants, as illustrated
. Segment
Canned specialties
Canned fruits & vegetables
Pickles, sauces & dressings
Frozen fruits & vegetables
Dehydrated fruits & vegetables
Potato and corn chips
Percent of total plants by no. employees
Less than 20 20-99 100 or more
employees employees employees
1958
1958
(%)
36
43
67
38
58
74
1972
(X)
57
40
62
8
51
69
1972
33
39
25
33
26
20
20
33
27
39
29
23
1958 1972
31
18
8
29
16
5
23
27
10
53
20
8
VII-12
-------
For all segments, except canned specialties, the proportion of large plants
increased and the proportion of small plants decreased, 1958-1972.
In view of the problems facing small fruit and vegetable processors and the
substantial investments required for effluent control systems, these plants
may encounter severe problems in securing required capital. Although large
firms have greater ability to generate capital from internal sources, from
sale of securities and from borrowings, the amounts of investment are large
and the cost of acquiring capital is high, so that capital availability
will pose problems to many of these firms as well.
Capital availability problems, although not quantified and explicitly con-
sidered in the plant closure analysis, were implicit in the closure projections
made. The principal factors considered in the closure analysis, other than
required price increases, were financial performance factors. Those plants
with severe financial impacts resulting from pollution controls were
projected to close. In most instances, these plants were either marginally
profitable or unprofitable in the absence of pollution controls. Because
of their less-than-satisfactory performance, securing capital for investment
in pollution controls for these plants would be difficult. For those plants
which continued with acceptable levels of profitability after the imposition
of pollution controls, it is assumed that capital availability would not
present serious problems since these plants would have the repayment capacity
necessary to retire loans made to finance pollution control systems.
VII-13
-------
Table
Calendar
Year
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
VII- 3 . Pre-tax return on
vegetables industry, 1961-
All
Firms
5.3
4.1
5.3
5.1
6.0
6.2
6.3
3.5
1.3
2.7
3.5
4.1
5.5
sales*, canned fruits
1973, unaudited I/
Over
$100 Million
Sales
p _i_
5.4
4.4
5.6
5.3
5.9
6.0
6.0
3.8
2.2
3.5
3.6
4.0
5.4
and
Under
$100 Million
Sales
4.9
2.3
3.8
4.4
6.4
7.1
7.6
2.0
(2.7)
(.6)
3.0
4.7
5.8
Three Year Average -
1971-1973 4.4 4.4 4.7
Ten Year Average -
1961-1970 4.4 4.7 3.3
Thirteen Year Average -
1961-1973 4.4 4.6 3.7
Number of Firms 31 5 26
Dollar Sales -
1973 (millions) $3,148 $2,448 . $700
* Pretax profit is after interest and before taxes and extraordinary
items.
All pre-tax margins are weighted averages.
For cooperatives, reported pre-tax profits were on an established
value basis.
_!/ Source: Touche Ross and Company, Study for National Canners Asso-
ciation, March, 1975.
VII-14
-------
Table VII-4. After-tax income, model plants, baseline condition and after BPT and BAT controls, three levels of in-olace
treatment ($000)
5.0?.. IN PLACE,
"LS-'-^C-'S
PTCKLC
SVJc'X=iUT
TAN
CAN
CAM
CAM
C4N
C : ;M-P£A-GS-C/>PRrT
BRTC-CLFL-CB-SPIN FREZ
TC^ATO-OHY BEAN
CHER^Y-GB-PEAR-PLU" CAN
CI-F.O.RY-STRS-CNBR
FREZ
_I2i!i_ £AS<
5500
ir.o^o
200
1500
2501
5000
1500
60~Q
100-50
60CO
9500
1500
4500
25000
150000
30 PO
12'ICO
3 7 COO
170000
10000
250TO
WOO "
53 "'o
1CPPO
15000
25000
5QCPC
8"iOO
25COO
40000
2000
7000
20000
70000
125000
5 "00
1°0~1
20000
ana
2010
50") j
;L1N£
8
29
2
?l
34
64
14
59
1C1)
75
95
11
24
101
755
,-3
102
301
966
71
171
3? }
41
76
107
l'-7
2fl6
57
222
695
22
53
158
360
633
77
149
291
19
37
f>3
LAG
_fi£J_
-11
1
-17
3
20
48
-4
41
66
64
P4
3
14
88
722
20
83
265
878
;2
138
273
26
53
74
1C5
228
35
182
641
5
40
134
312
568
C-4
130
260
9
26
67
C C N
_fiil_
-24
-24
-33
-15
3
34
~?4
25
66
56
75
-4
4
71
667
IP
73
246
fl37
40
118
247
9
36
48
73
177
8
Z38
589
-15
23
108
.756
•'188
52
U2
233
1
14
53
S L U
_£2i_
-59
-73
-61
-42
-20
22
-54
5
46
42
62
-26
-13
61
642
-24
51
211
756
17
92
211
-15
19
27
48
132
-4
122
560
-43
3
93
221
430
41
101
222
-19
-4
43
D G E
_£'!_
-73
-SB
-77
-61
-42
3
-74
-24
26
34
54
-34
-26
44
586
-36
40
192
715
-2
73
181
-40
-8
-9
14
81
-48
78
507
-65
-29
66
164
350
29
83
195
-79
-22
29
LAG
_SEI_
-8
6
-14
6
22
51
-1
43
89
66
85
5
16
90
727
21
36
271
891
55
143
286
28
56
79
111
236
38
183
649
8
42
138
319
578
66
133
765
H
27
49
CON
_££!_
-19
-13
-28
-9
9
39
-17
30
72
59
78
-1
7
75
680
14
77
254
856
44
126
260
15
42
57
84
193
18
150
605
— Q
28
115
271
510
56
117
242
4
19
57
S L U
_fi£l_
-49
-56
-51
-32
-10
29
-43
16
56
47
67
-20
-6
67
659
-15
59
225
788
26
104
230
-3
28
39
63
155
9
137
580
-33
13
103
242
461
47
108
233
-13
4
49
0 G E
_SA1_
-60
-77
-65
-48
-28
15
-60
-5
39
•40
60
-26
-17
52
612
-25
49
208
752
14
87
204
-24
10
17
35
112
-26
100
535
-51
-11
80
194
393
36
93
210
-21
-10
37
LAG
got
0
18
-7
13
27
56
6
50
97
69
89
7
20
95
739
24
93
283
922
62
155
305
33
64
90
126
257
46
202
668
14
48
146
336
601
71
139
276
14
31
75
0 C N
_3.£I_
-7
8
-15
5
21
49
-3
42
87
65
85
4
15
36
711
?1
87
274
901
55
145
29C
27
56
78
110
232
34
180
642
5
39
133
308
561
65
130
262
1C
2 f
6P
S L U
_££!_
-25
-15
-29
-7
12
43
-18
34
77
58
73
-6
8
81
698
7
76
256
861
45
132
272
20
48
67
97
2C9
31
172
627
-7
32
126
290
532
59
125
257
2
21
63
C G E
-SAT.,
-31
-27
-37
-17
4
36
-28
27
67
54
74
-10
3
72
671
2
71
247
840
39
122
257
10
39
55
81
ie4
19
15C
601
-18
23
112
262
492
53
116
243
-3
14
56
-------
Table VII-4. (continued)
P!C
-------
Table VII-5. After-tax return-on-sales, model plants, baseline condition and after 8PT and BAT controls, three
levels of 1n-p1ace treatment (%)
50% IN PLA^E
LAGOON
-£-D-H-a.Q 0 I T Y.
C03N
MUSHROOMS
PICKLE
SA'JERKRAUT
TCHATQ
CCSN-PEA
CC«N-PEA-G8-CAPPOT
CO*N-PEA-GB-CfiRROT
9 ROC -C LF L-L B- S P I N
TC1ATO-OPY 6FAN
CHERRY-GB-»EAR-PLUN
CHERRY-STRB-CNBR
IIEE
CAN
CAN
CAN
CAN
CAN
CAN
CAN
FPSZ
FPEZ
CAN
CAN
FRE,f
_IDliS_ Sfi.SiLUiE
5500
18000
200
1500
2500
5000
1500
6000
10000
6000
9500
1500
4500
25000
15000O
3000
120OO
370 00
1200 00
10'300
25 000
50 000
'•000
lO'OOO
VI 000
2 5000
'JOOOO
8000
25000
40000
20OO
7 COO
20030
70000
125000
5000
1COOO
20000
800
2000
5000
1.1%
1.2
0.7%
1.0
1.0
0.9
J .6%
1.4
1.5
4.2%
5.0
4.0*
2.9
2.8
4.7
4.5%
3.7
3.5
3. 5
3.0%
2.8
2.8 '
4.3%
4.0
3.8
3. 7
3.6
1.4%
1.8
3.4
3.3?
2.t
2.5
2.1
2.2
3.8%
3.6
3.6
1.7?
1.4
1.2
_SET_
-1.5%
0.0
-6.1%
0.2
0.6
0.7
-0.4%
1.0
1.2
. 3.6%
4.4
1.2%
1.8
2.5
4.5
3.1*
3.0
3.1
3.2
2.2*
2.3
2.3
2.7?
2.8
2.6
2.7
2.S
0.9*
1.4
3.2
C.7%
1.8
2.1
1.8
2.-C
3.1%
3.2
3.2
0.9%
1.0
1.0
_a&i_
-3.3%
-1.0
-12.0%
-0.7
0.1
0.5
-2.6%
0.6
0.9
3.1*
4.0
-1.3*
0.5
2.0
4.2
1.6?
2.6
2.9
3.0
1.6%
2.0
2. I
1.0%
1. ?
1.7
i. a
2.2
0.2%
1. I
2.9 '
-2.2%
1.0
1.7
1.5
1.7
2.5%
2. 7
2.f3
0.'%
0.5
O.P
SLUDGE
_a£j_
-3.0%
-3.1
-21.8%
-2.0
-0.6
0.3
-6.C%
0. 1
C.7
2.3%
3.3
-9.3%
-1.6
1.7
4.0
-3.9*
1.8
2.5
2.7
0.7%
1.5
, 1-8
-l.t?
1.0
1.0
1.2
1.7
-0.1%
1.0
2.8
-6.5%
0. 1
1.5
1.3
1.5
2.0%
2.5
2.7
-1.8?
-0. 2
0.6
_£AI_
-9.8%
-4. 1
-27.7%
-2.9
-1.2
0.0
-8.2%
-0.6
0.4
1.9%
2.8
-12.2%
-3.2
1.2
3.7
-5.8%
1.5
2.3
2.6
-0.1%
1.2
1.5
-4.3?
-0.4 '
-0.3
0.4
L.O
-1.2*
0.6
2.5
-9.6%
-1.3
1.1
1.0
1.2
1.4*
2.0
2.4
-2.7%
-0.8
0.4
LAGOON
_fi£I_
-1.0*
0. 3
-5.0%
0.3
0.6
0.7
-0. 1%
1.0
1.3
3.6%
4.5
1.7%
2.0
2.5
4.5
3.3?
3. 1
3.2
3.2
2.3*
2.4
2.4
3.0*
3.0
2.8
2.8
3.0
0.9*
1.5
3.2
1.1*
1.9
2.2
1.9
2.0
3.2*
3.2
3.2
1.0?
1.0
1.0
_flAJ_
-2.6%
-0.6
-10. 1%
-0.4
0.3
0.6
-1.9%
0.7
1.0
3.3*
4.1
-0.3*
0.9
2.1
4.3
2.2%
2.8
3.0
3.1
1.8*
2.1
2.2
1.6?
2.2
2.0
2.1
2.5
0.4%
1.2
3.0
-1.3?
1.3
1.8
1.6
1.8
2.7%
2.9
2.9
0.4*
0.7
0.9
SLUDGE
_££!_
-6.6%
-2.3
-18.4%
-1.5
-0.3
0.4
-4.8%
0.4
0.8
2.6%
3.5
-7.1%
-0.7
1.9
4.1
-2.3%
2.1
2.6
2.9
l.l*
1.7
1.9
-0.3*
1.5
1.4
1.6
2.0
0.2*
1.1
2.9
-4.8*
0.6
1.6
1.4
1.6
2.3*
2.6
2.8
-1.2*
0.2
0.7
_£A1_
-8.1*
-3.2
-23.4?
-2.3
-0.8
0.2
-6.6%
-0. 1
0.6
2.2*
3.1
-9.6*
-2. 1
1.5
3.8
-3.9?
1.8
2.4
2.7
0.6?
1.5
1.7
-2.6*
0.5
0.6
0.9
1.4
-0.7*
0.8
2.7
-7.5*
-0.5
1.3
1.1
1.4
1.8%
2.3
2.6
-2.0?
-0.4
0.5
LAG
_££!_
-0.0*
0.7
-2.5?
0.6
0.8
o.e
0.6*
1.2
1.4
3.9%
4.7
2.6%
2.4
2.7
4.6
3.8%
3.4
. 3.3
3.3
2.6*
2.6
2.5
3.5*
3.4
3.2
3.2
3.3
1.1?
1.6
3.3
2.0?
2.2
2.3
2.0
2.1
3.4%
3.4
3.4
1.3%
1.2
1.1
D C N
_£A1_
-0.9%
0.3
-5.5%
0.2
0.6
0.7
-0.3%
1.0
1.2
3.6t
4.5
1.5%
1.8
2.4
4.4
3.3%
3.2
3.2
3.3
2.3?
2.4
2.4
2.81
3.0
2.7
2.8
2.9
0.8*
1.4
3.2
0.8%
1 .8
2.1
1.8
1.9
3.1%
3.2
3.2
0.9?
1 .0
1.0
S L U C G E
..EEI.
-3.3*
-0.6
-10.4%
-0.3
0.4
0.6
-2.0%
0.8
1.1
3.2%
4.1
-2.0%
1.0
2.3
4.4
1.1%
2.8
3.0
3.1
1.9?
2.2
2.3
2.1%
2.5
2.4
2.5
2.7
0.8*
1.4
3.1
-l.l?
1.4
2.0
1.7
1.8
2.9*
3.0
3.1
0.2*
0.8
0.9
SAT,.
-4.2*
-1.1
-13.3%
-o.e
0.1
0.5
-3.1*
0.6
1.0
3.0*
3.9
-3.5*
0.3
2.0
4.2
0.3*
2.6
2.9
3.0
1.6?
2.0
2.1
1.1%
2.1
1.9
2.1
2.3
0.5*
1.2
3.0
-2.7?
1.1
1.8
1.5
1.7
2.6%
2.8
3.0
-0.3*
0.5
0.8
-------
Table VII-5. (continued)
NONE IN P|-ACE
i_ i*E£ _:
P1CKLE-TCHT-CE-OCSA CAN
BRINED PRODUCT CAN
POTATO CHIP DFHY
.I2NL. fl
2000
6CH
1*000
60000
1500
60CO
1COOO
1000
2500
8000
13000
30000
AifLlME.
3.7*
3.4
3.4
3.4
5.0*
4.2
4.9
2.5*
2.1
1.7
1.4
C.V
LAG
_EEI_
3.1*
3.2
3.3
3.3
2.2*
3.1
3.8
-0. IT
1.3
1.3
1.1
0.7
DON
_fiS.I_
2.6*
3.0
3.2
3.2
-1.0*
2.3
2.R
-2.7*
0.3
1.1
0.9
0.6
S L
_&£!_
1.5*
2.6
3.0
3.2
-7.0*
1.4
1.8
-9.8*
-2.5
0.5
0.5
0.3
U 0 G E
-&AJL
I. I*
2.4
2.9
3. 1
-10.8*
0.3
0.7
-12.4*
-3.7 •
0.1
0.2
0.2
LAG
_£•£!_
3.2*
3.2
3.3
3. 3
2.7*
3-3
3. -3
0.3*
1.4
1.4
1.2
0.7
DON
_BAJ_
2.8*
3.0
3.2
3.3
0.2*
2.5
3. 1
-1.8*
0.7
1.2
1.0
0.6
S L U
_0£I_
1.9*
2.7
3.1
3.2
-4.9%
1.8
2.3
-7.8* -
-1.6
0.7
0.6
0.4
D G E
_fiAI_
1.5*
2.5
3.0
3.2
-8.1*
1.1
1.4
10.1*
-2.7
0.4
0.4
0.3
LAG
_££!_
3.4*
3.3
3.3
3.3
3.9*
3.6
4.3
1.2*
1.7
1.5
1.3
0.8
-*"^ in,
0 C N
_££!_
3.2*
3.2
3.3
3.3
2.4*
3.2
3.8
0.2*
1 .4
1.4
1.2
0.7
ri-m-c
S L U
_££!_
2.6*
3.0
3.2
3.3
0. 1*
2.8
3.3
-3.3*
0.3
1. 1
0.9
0.6
0 G E
-BAI-
2.4*
2.9
3.2
3.2
-1.8*
2.4
2.9
-4.6*
—0.3
1.0
0. 8
0.5
-------
Table VII-6.
After-tax return-on-investment, baseline condition and after BPT and BAT controls
three levels of in-place treatment (3>)
KOAE_1N PLACE . .. .
L A G C C N
COMMODITY
CORN
MUSHROOMS
PICKLE
SAUERKRAUT
TC*ATO
CCRN-PEA
CORN-PEA-G3-CARROT
CGRN-PEA-G6-C/SPROT
BR3C-CLFL-L8-SPIN
TC^A TO-DRY PEAN
CHERRY-G8-PEAR-PLU*
CHrR,Y-$TRe-CM6R
TYPE
CAN
CAN
CAN
CAN
CAN
CAN
CAN
FP.EZ
FREZ
CAN
CAN
F3EZ
_ICiiS_ f
5500
18COO
200
1500
2500
5000
1500
6000
10000
6000
9500
1500
4500
25000
150000
3000
12000
37000
123000
10000
25000
5CCOO
5000
10000
13COO
25000
50COO
8000
25000
4CCOO
2000
7COO
20000
70000
125000
5000
1CCOO
20001
800
2COT
5000
IASEL tNP
1.8*
2.5
0.3*
0.6
0.6
0.7
3.5%
3.5
4.1
6.2*
6.9
4.5%
5.0
3.4
9. 1
6.81!
C.9
7.8
8.4
6.2*
6.4
6.8
• 5.0*
5.5
6.0
6.0
6.6
3.3%
5.C
1C. 3
7.0*
5.5
5.2
3.9
3.9
9.1%
1C. I
9.2
4.4%
3.9
3.8
_gP J_
-2.2*
0. 1
-2.7*
C. 1
0.4
0.5
-C.9*
2.3
3.1
5.1*
5.9
1.2*
2.8
2.9
8.5
4.3*
0.7
6.6
7.4
4.2*
4.9
5.4
2.9*
3.6
3.8
4.0
4.S
1.9*
4.0
9.2
1.4*
3.e
4.3
3.3
3.4
7.C*
e.2
7.8
2. 1*
2.6
3.0
gj\j
-4.5*
-1.7
-5.3*
-0 4
0. 1
0.^
-5. .:*
i .'-
2.3
4.'>*
5.?
-1.,.'*
0. J
2. -i
7.5
2.2*
0.6
5.9
6.9
3. I*
4.0
4. 7
1.0*
2.3
2.7
2.6
3.6
0.4*
2.9
8.2
-3.9*
1.9
3.3
2.6
2.9
5.3*
6.5
6.7
0.3%
1.4
2.3
S L U C C E
2E1_
-8.9*
-4.6
-8.7*
-1.2
-0.4
0.2
-10.0*
0.3
1.6
3. 1*
4.1
-6.8*
-2. 1
1.9
7.1
-4.1*
0.4
4.8
5.9
1.2*
3.0
3.8
-1.5*
1.2
1.3
1.6
2.6
-0.2*
2.5
7.7
-9.5*
0.2
2.8
2.2
2.5
4.0%
5.3
6.3
-3.5*
-C.4
1.9
Bfl j _
-10.3*
-5.9
-10.8*
-1 .8
-C.8
0.0
-13.1*
-1.3
0.9
2-5*
3.5
-R.4*
-4.0
1.3
6.3
-5.8*
0.3
4.. 2
5.5
-0. 1*
2.3
3.2
-3.7*
-0.5
-0.4
0.4
1.5
-2.4%
1.6
6.8
-13.2*
-2.2
1.9
1.6
2.0
2.7*
4.5
5.3
-5. 1*
-2.0
1.2
LAG
fiEI
-1.6*
0.5
-2.3*
0.2
0.4
0.5
-0. 1*
2.5
3.3
5.3*
6.0
1.7*
3.2
3.0
8.6
4.7*
0.7
6.7
7.6
4.5*
5.1
5.6
3.2*
3.9
4. 1
4.2
5.2
2.1*
4. 1
9.3
2.2*
3.8
4.4
3.4
3.5
7.3*
8.5
8. C
2.4*
2.8
3.1
15* JN PLACE _ . 50* IN PLACE
0 0 N
£AJ_
-3.7*
-1.0
-4.5*
-0.3
0.2
0.4
-3.8*
1.7
2.6
4.7*
5.5
-0.3*
1.3
2.4
7.8
2.9*
0.7
6.2
7.1
3.5*
4.3
5.0
1.7*
2.7
2.8
3.0
4.0
1.0*
3.2
8.5
-2.2*
2.4
3.6
2.8
3.0
5.8*
7.1
7.0
C.8*
1.9
2.5
SLUDGE
BEL_
-7.7*
-3.7
-7.5*
-0.9
-0.2
0.3
-8.3?
0.9
1.9
3.6*
4.5
-5.5*
-1.0
2.1
7.4
-E.5X
0.5
5.2
6.3
1.9%
3.4
4.2
-0.3*
1.7
1 .9
2.2
3.1
0.5*
2.9
8.1
-7.5*
1.1
3.1
2.4
2.7
4.6*
6.4
6.7
-2.4*
0.4
2. 1
_£L6I
-9.0*
-4.3
-9.4*
-1.4
-0.5
0.2
-11.1*
-0.3
1.3
3.0*
4.0
-7.0*
-2.8
1.6
6.7
-4.1?
0.4
4.7
5.9
0.9*
2.8
3.7
-2.3*
0.6
0.3
1.2
2.2
-1.3*
2.0
7.3
-10.9*
-0.8
2.3
1.9
2.2
3.4*
5.2
5.8
-3.9*
-C.9.
1.5
LAG
RPT
-0.1*
1.4
-1.2*
0.4
0.5
0.6
1.3*
2.9
3.6
5.7*
6.4
2.8*
4.1
3.2
8.8
5.5*
0.8
7.2
7.9
5.2*
5.6
6.1
3.9*
4.5
4.9
4.9
5.8
2.6*
4.5
9.7
4.1*
4.4
4.8
3.6
3.7
8.0*
9.1
8.5
3.2*
3.2
3.4
0 C N
fiJSI_
-1.4*
0.6
-2.5*
0.2
0.4
0.5
-0.6*
2.4
3.2
5.3*
6.0
1.5*
2.9
2.8
8.3
4.7*
0.8
6.3
7.7
4.5*
5.2
5.7
3.0*
3.8
4.1
4.2
5.0
I .9*
3.9
9.2
1.5*
3.5
4.2
3.2
3.4
7.1*
8.2
7.9
2.2*
2.7
3.0
S'L u o o E
_££!_
-4.4*
-1.1
-4.5*
-0.2
0.2
C.5
-3.8*
2.0
2.8
4.6*
5.4
-1.8*
1.5
2.6
8.1
1.3*
0.7
6.2
7. 1
3.5*
4.6
5.2
2.1*
3.2
3.4
3.6
4.4
1.7Z
3.7
8.9
-1.9*
2.8
3.9
3.0
3.2
6.3*
7.8
7.7
0.4*
2.0
2.8
Q A T
-5.5*
-1.9
-5.7*
-0.5
0.1
0.4
-5.7*
1.5
2.4
4.2*
5.1
-3.0*
0.5
2.3
7.6
0.4t
0.6
5.9
6.9
2.9*
4.2
4.9
1.1*
2.5
2.7
2.9
3.8
1.0*
3.2
8.5
-4.4*
2.0
3.4
2.7
2.9
5.5*
7.0
7.1
-0.5*
1.4
2.4
-------
Table VII-6. (continued)
L A G C 0 N
.c.g » .M..O.D...I T Y HEE
PICKLE-TCMT-CB-DCSA CAN
SEINED PRODUCT CAN
POTATO CHIP CEHY
SLUDGE
LAGOON
_IOtlS_ BASILIC _B£I_ _fiAI_ _fiEI_ _m_ _££!_
2000
6000
18000
toooo
1500
6000
10000
1000
2500
8000
. 13000
30000
3.1*
4.0
7.6
9.9
7.6*
t.?
7.C
4. 5*
3.3
2.8
2.4
1.9
7.6*
3.6
7.2
9.6
3.1*
4.5
5.1
-0. 1*
2.2
2.2
1.8
1.4
2.2*
3.4
6.9
9.4
-1.3*
3. I
3.6
-4.3*
0.6
1.8
1.5
1.1
1.2*
2.9
6.5
9.1
-7.5*
1.9
2.2
'-12.2*
-3.7
0.7
0.7
0. 7
0.8*
2.6
6.2
8.9
-11.1*
0.4
0.8
-15.0*
-5.4
0.2
0.3
0.4
2.7*
3.7
7.3
9.7
3.8*
4.7
5.4
0.6*
2.4
2.3
1.9
1.5
-£AI_
2.3*
3.5
7.0
9.4
0.2*
3.5
4.0
-2.9*
1.1
1.9
1.6
1.3
SLUDGE
_a£i_
1.5*
3.0
6.7
9.3
-5.5*
2.5
2.8
-10.2*
-2.5
1.0
0.9
0.8
-EAI_
1.2*
2.8
6.4
9.0 .
-8.7*
1.4
1.7
-12.8*
-4.0
0.6
0.7
0.6
LAG
2.9*
3.8
7.4
9.8
5.6*
5.3
6.0
2.1*
3.0
2.5
2.1
1.7
WW« 111,
DON
2.6*
3.7
7.2
9.6
3.4*
4.6
5.2
0.3*
2.4
2.2
1.9
1.5
ri-jn.1:
SLUDGE
-££!_ _fiAI_
2.1*
3.4
7.0
9.5
0.1*
3.9
4.4
-4.8*
0.4
1.7
1.5
1.3
1.9*
3.3
6.9
9.4
-2.2*
3.2
3.7
-6.6*
-0.4
1.5
1.3
1.1
-------
Table VII-7. Estimated annual cash flow, model plants, baseline condition and after BPT and BAT controls,
three levels of in-place treatment ($000)
PItKLE
SAUERKRAUT
TC«ATO
_C_E_i!_tl_Q_a.
CC<3N CAN
CAN
CAN
CAN
CAN
CAN
CC3N-PEA-GB-CARRQT CAN
CC"N-PEA-G8-CARROT FREZ
BR3C-CLFL-L8-SPIN FREZ
TC^ATO-ORY BEAN CAN
CHERRY-G6-PEAR-PLUM CAN
CHERRY-STRB-CNBR FREZ
_IQH£_ Bj
5500
18COO
200
1500
2500
5003
1500
6000
10000
6000
9500
1500
4500
25000
150000
3000
12000
37000
120300
10000
25000
50000
5000
10000
18CCO
25000
50000
8COO
25000
40000
2000
7000
20000
70000
125000
5000
10000
20000
800
2000
5000
i$EJ.JLiiE
31
85
44
264
428
607
27
114
191
137
169
31
60
266
1140
57
197
481
1416
141
371
633
87
148
257
307
586
148
387
Sll
35
102
276
723'
12C7
127
224
441
32
62
130
L A C
_&£!_
21
74
30
252
420
599
13
104
179
HI
163
27
56
264
1134
54
191
469
1380
134
359
611
81
139
244
290
553
137
368
ees
23
S3
268
7C9
1189
123
219
434
26
57
123
CON
_2AI_
13
61
15
237
4C8
591
-3
95
170
125
157
24
51
262
1130
48
188
465
1371
129
354
603
72
133
237
281
538
122
349
857
8
87
• 261
698
1174
120
215
429
22
51
118
S L U
_EET_
-4
39
-3
218
392
587
-22
es
160
121
153
12
43
261
1127
31
187
466
13P6
126
3bO
599
60
130
232
277
541
118
341
846
-10
76
25C
690
1164
118
211
423
11
41
116
D G E
_fi£!_
-12
25
-17
202
375
572
-38
63
151
116
148
7
35
259
1122
22
184
462
1377
115
345
591
43
114
214
266
527
66
322
818
-27
54
243
678
1150
114
207
418
5
28
111
LAG
_££!_
23
77
32
254
421
60C
16
1C5
181
132
164
28
57
264
1135
55
192
471
1386
135
361
615
82
140
246
293
558
139
371
889
25
94
270
711
1191
124
219
435
27
58
124
DON
_£A1_
16
67
20
242
412
593
2
98
173
127
159
25
53
263
1131
50
189
468
1378
131
356
608
76
136
240
285
545
129
354
865
13
89
264
701
1179
121
216
431
23
54
120
S L U
_2E1_
2
48
5
226
400
590
-14
92
163
124
156
15
47
262
1129
37
189
468
1391
129
354
604
63
133
236
282
548
126
348
855
-3
82
254
695
1171
119
213
425
15
46
118
D G E
-BJ.I-
-5
37
-7
213
385
581
-28
77
157
119
151
11
40
260
1125
3C
186
465
1383
123
349
597
53
125
229
274
536
102
332
832
.-17
67
248
685
1159
116
210
422
9
36
114
LAG
_££!_
27
82
37
253
424
603
21
1 09
185
134
166
29
59
265
1137
56
194
475
1398
138
365
622
84
143
250
298
569
142
377
898
30
96
272
716
1198
125
221
438
29
60
!26
G C N
_flAI_
23
78
30
253
f-7.0
599
14
104
181
131
163
28
56
264
1135
54
193
473
1394
135
362
618
81
141
247
294
562
137
368
684
24
93
269
710
1191
124
219
435
27
58
124
S L U
—SH.I-
15
69
21
245
416
597
5
102
176
129
161
23
54
263
1133
49
192
474
1401
134
361
616
80
139
245
292
564
137
364
878
16
90
263
706
1166
122
217
432
24
56
123
C G E
_MI_
n
63
14
237
409
593
-4
98
171
126
158
21
51
263
1131
46
191
472
1397
132
356
612
75
136
241
287
557
132
355
865
7
87
26C
701
117S
121
216
430
21
52
120
-------
Table VII-7. (continued)
PtCKUE-TCwT-CB-DtSA CAN
^RINEO PRODUCT
PCTATO CHIP
CEHY
2000
6COO
18000
60000
1500
6000
10000
1000
2500
8000
13000
300CO
NCKF IN PLACE __15* IN PLAC£__
LIKE
180
454
983
2507
43
137
172
41
93
240
307
394
LAG
-BEI-
173
446
872
2488
22
127
159
29
E6
233
3CO
384
CON
_&£!_
167
438
862
2472
19
118
150
15
75
227
292
375
S L U
_aEi_
160
421
854
2456
C
113
141
-14
48
219
284
366
D G E
_fiAI_
153
423
f45
2440
-16
99
130
-28
33
2C8
273
357
LAG
_fi£I_
174
447
873
2491
34
128
161
31
87
234
301
385
0 0 N
_£AI_
169
440
665
2477
24
121
154
19
79
229
294
378
S L U
_fi£I_
163
434
859
2464
8
116
146
-5
57
222
287
370
0 G E
-BAT
157
427
R50
2450
-6
109
138
-17
45
216
281
363
LAG
-BPT
177
450
877
2497
39
132
166
35
90
237
303
389
50* IN'
0 C N
_£AL_
174
446
87?
2469
33
127
161
30
66
233
3CO
385
P1A££_
S L U
_E£I_
170
443
869
2481
27
125
157
15
77
229
295
380
C G E
..SAT...
167
439
864
2473
19
120
152
e
71
226
2S2
376
-------
vii-o. net present values of model plants, baseline condition and after BPT and BAT controls, three levels of in-olace treatment
50%-I NOPLACE.,
C 0_M M..O D I . T .Y
CCRN
'•USHSQCWS
PICKLE
SAUERKRAUT
TCMATO
CCSN-PEA
CCRN-PEA-G8-CARROT
CCRN-PEA-G8-CARROT
SPOC-CLFL-LB-SPIN
TCMATO-ORY BEAN
CHERRY-GB-PEAR-PLUM
JXE£
CAN
CAN
CAN
CAN
CAN
CAN
CAN
FPEZ
FREZ
CAN
CAN
_JQN.S_ Zi
5500
18000
200
1500
2500
5000
1500
6000
10000
6000
9500
1500
4500
25000
150000
3000
12000
37000
120000
10000
25300
50COO
5000
10COO
18000
. 25000
50000
6000
25000
40000
2000
7000
20000
70000 .
125000
5000
10000
20000
^S.£J.Iii£
66
122
152
709
1156
1267
15
10
77
656
805 .
165
244
865
5466
258
777
1790
5461
456
1253
2033
370
612
997
1167
2291
176
108
4907
123
275
744
1559
2609
464
759
1476
LAG
BPT
-71
-124
48
585
1016
1101
-131
-175
-155
547
692
1C8
163
724
5C83
167
5£3
14CO
4521
249
896
1446
208
370
ft I
723
1564
-50
-314
4338
-2
113
483
1028
1872
321
550
1130
C C N
_1A.T_
-129
-214
-11
530
954
1022
-212
266
-274
502
647
76
116
602
4692
130
513
1268
4235
172
766
1246
126 '
259
474
511
1234
-189
-582
4031
-87
8
308
647
1326
241
428
944
S L U
_££!_
-443
-540
-27C
343
776
845
-543
-431
-549
323
473
-101
-9
435
4249
-1C8
233
83C
3218
-102
428
767
-70
26
169
141
680
-359
-902
3523
-388
-208
-33
92
458
88
258
751
D G 6
_££!_
-510
-650
-348
288
715
766
-636
-521
-667
279
428
-136
-56
312
3858
-157
163
698
2932
-179
298
567
-152
-85
'2
-71
350
-498
-1170
3217
-491
-313
-2C8
-2SO
-88
8
136
565
LAG
_BEI_
-48
-87
63
603
1037
1126
-107
-147
-120
563
709
117
175
745
5140
161
612
1458 '
4662
280
950
1534
232
406
694
789
1673
-16
-251
4423
19
133
522
11C8
1983
342
581
1182
DON
_fiA.I_
-97
-164
17
557
984
1059
-171
-225
-221
526
671
91
13t
641
4808
149
553
1346
4419
215
839
1364
163
312
553
609
1392
-135
-478
4162
-51
48
373
783
1518
275
478
1024
S L U
_fl£I_
-353
-437
-188
398
833
908
-448
-365
-455
373
522
-58
29
499
4432
-50
315
974
3555
-18
552
957
-4
114
293
294
922
-279
-751
3731
-293
-135
84
312
781
144
333
860
D G E
_fi£I_
-411
-519
-253
351
781
841
-527
-442
-556
336
484
-87
-11
395
4100
-85
255
862
3311.
-84
441
787
-74
20
151
114
641
-397
-978
3470
-380
-225
-65
-12
316
77
230
702
LAG
_££!_
5
-1
100
647
1086
1184
-51
-83
-39
602
749
136
204
795
5274
212
680
1595
4991
353
1074
1740
289
491
819
945
1927
63
-103
4622
62
194
614
1294
2241
392
655
1303
0 C K
_BAI_
-23
-46
77
620
1055
1144
-89
-128
-99
579
726
122
160
733
5079
194
645
1529
4848
314
1009
1640
248
436
735
839
1762
-7
-237
4469
29
141
526
1103
1968
353
594
1210
S L U
_££!_
-165
-207
-28
526
966
1056
-229
-211
-236
490
639
43
117
650
4858
77
505
1310
4340
177
841
1400
150
319
583
654
1485
-92
-397
4215
-96
34
356
826
1534
276
509
1113
D G E
BflT
-194
-252
-60
499
935
1016
-274
-256
-295
468
617
26
94
589
4662
58
470
1244
4196
138
775
1300
109
264
499
548
1321
-161
-531
4062
-139
-19
268
635
126C
236
448
102C
-------
Table VII-8. (continued)
COM M_0-D L T_
CHgPRY-STRB-CNBR
P!CM.£-TCI*T-Ce-Of
9HINED PRODUCT
POTATO CHtP
-X- UEE _!£!£_
FREZ 800
2000
5000
ISA CAK 2000
6COO
18000
60000
C*N 1500
6000
10000
CEHY 1000
2500
8000
13000
30000
BAifLIUE "
28
-41
-245
638
1656
3328
9689
203
595
816
113
203
455
440
-226
LAG
_££!_
-39
-163
-412
521
1502
31C5
9240
87
412
565
1
90
329
279
-461 .
0 C N
-E£I_
-78
-220
-'-•00
'•80
1428
2963
9007
23
321
466
-62
41
278
217
-548
S L U
_££!_
-254
-380
-659
216
1152
2672
8548
-257
156
191
-479
-226
7
-77
-870
0 G 6
_MI_
-298
-442
-747
166
1078
2550
8315
-350-
65
72
-557
-287
-45
-139
-957
LAG
_a£i_
-29
-144
-387
547
1525
3139
9307
104
439
619
22
1C8
348
303
-425
CON
_£M_
-60
-193
-462
504
1462
3035
9109
55
362
518
-31
66
304
250
-500
S L U
_fi£I_
-207
-329
-597
280
1228
2770
8719
-170
222
285
-373
-161
74
0
-773
D G E
_£AI_
-244
-378
-672
236
1 165
2667
8521
-245
145
184
-439
-202
30
-52
-648
LAG
..BPI.
-5
-102
-328
585
1579
3216
9465
145
504
700
59
149
392
359
-343
0 C N
_m_
-22
-131
-372
559
1542
3156
9343
117
459
641
35
125
366
328
-387
S L U
PPT
-99
-211
-452
427
1404
3000
9118
12
376
504
-140
-9
231
181
-548
D G E
-Bfll.
-120
-239
-496
402
1367
293S
9002
-26
331
444
-172
-33
2C5
150
-592
-------
C. Production Effects
For purposes of an impact analyses an additional segmentation to that
in Chapter II of this report is necessary, i.e., development of various
types and sizes of model plants that represent those in industry. The
segmentation in Chapter II shows general characteristics of industry
groups (canning, freezing dehydrating) of firms within a group and of
plants within a firm. Therefore, this section of Chapter VII, Impact
Analyses, will include:
1. Segmentation of Industry to Model Plants
2. Baseline Closures
3. Projected Plant Closures Above Baseline Resulting from
Pollution Controls, and
4. Production Losses Due to Plant Closures
1. Segmentation of Industry to Model Plants
a. Classification of plants and commodities
Several strategies were tried in developing model plants to represent
the industry. Most of these strategies were inferior since the fruit
and vegetable processing industry is comprised of many unique plants.
However, a common denominator of processing function was developed and
is believed to be as good a segmentation basis as is currently available
for modeling this complex industry. Process functions used in this re-
port are:
1. Blanched vegetables,
2. Pitted and/or peeled fruits ,
3. Peeled vegetables,
4. Dehydrated fruits and vegetables,
5. Brined fruits and vegetables,
6. Reprocessed fruits and vegetables, and
7. Nonbasic fruits.
A total of 54 commodities were classified into a process function and
are shown in Table VII - 9, Strawberries-, cane and blueberries were
classified for this study as nonbasic since (l).they did not fit other
basic process functions (mostly washed and quick frozen), (2) they fre-
quently appear in a number of plants and (3) it was necessary to maintain
their identity.
Next, plants listed in the Directory— (1,360) which correspond to the
scope of this study were classified by plant type and commodities processed.
— Judge, Edward E. and Sons, The Directory of the Canning, Freezing and
Preserving Industries, 1974-75.
VII-25
-------
Table VII- 9 Classification of commodities into processing functions
Blanched
Asparagus
Dry Beans
Green Beans
Lima Beans
Broccoli
Brussel Sprouts
Caul if lower
Celery
Corn
Greens
Mushrooms
Okra
Peas
Rhubarb
Spinach
Squash
Vegetable, Misc.
Zucchini
Pitted/Peeled
Fruits
Apples
Apricots
Peaches
Pear
Pineapple
Plums
Cherries
Peeled
Vegetable
Beet
Carrot
Cranberries
Onion
Potatoes
Tomatoes
Process Function
Dehydrated • Brine
Dehydrated Vegetable Artichoke
Dehydrated Fruit Olives
Potato Chips Peppers
Prunes Pickles
Pimento
Sauerkraut
Reprocess
Baby Food
Canned Specialties
Dressings & Sauces
Drinks & Juices
Fruit Cocktail
Figs
Fruits, Miscellaneous
Grapes
Jams & Jell ies
Soup
Nonbasic fruits
Caneberries
Blueberries
Strawberries
-------
In turn, they were partitioned by plant type and processing function(s)
after separating out the signle commodity corn, mushroom, tomato, pickle
and sauerkraut canning plants. Single commodity freezing plants were not
as frequent on a number-of-plants-by-commodity basis and were grouped
under the appropriate multi-commodity freezer process function(s).
Using a process of elimination, single process function plants (blanch
or reprocess, etc.) were grouped first and multi-process function plants
(blanch and peel, etc.) next. The function or functions with the largest
number of plants were used for representative model plants.
The commodities to be used for each model were based partially on judgment
between those commodities appearing most often in the Directory by process
function, and availability of financial data by commodity from survey re-
sults. I/ Fortunately, the largest to nearly largest number of multi-
commodity plants processing a commodity(s) in the Directory data had corre-
sponding survey financial information.
Tables Vll-igto VII-12 show the number of industry plants from the Directory
grouped into model plant process functions by plant type and the commodities
representing the model. Table VII-lQshows the various models representing
canners, Table VII-ll freezers and Table VII-12 dehydrators.
b. Total number of industry plants
To develop the total number of plants in each industry group, two steps were
taken. First, model plants and the corresponding number of industry plants
from the Directory, represented by models. «ers Classified into four digit,
industry groups. Second, the ratio of the number of plants represented by
each model to total plants in an industry group was applied to total in-
dustry group plants shown in the 1972 Census. The Directory is felt to be
the best source of the largest number of plants delineated by commodities
processed and plant type except for dehydrators and chippers. The extrap-
olation of modeled industry plants listed in the Directory to the total
industry group is shown in Table VII-13. As applied, industry plants
listed in the Directory and used in this study were equal to 62 .percent of
the total listed in the Census.
c. Sizing of industry plants
Sizing of industry plants utilizes three sets of data.
— Survey conducted by seven fruit and vegetable processing trade associ-
ations and tabulated by DPRA for purposes of this report.
VII-27
-------
tl'1'1
S1HGLC
Blanch
Prine
Process (unction
I Pi MODUS:
VV u 1 rl-tnt f niH'iin! i t v/n] .int
to. I'uJi ti<", SiiuiU' Multi Plants
Corn,
Mushrooms
Tomatoes
Pickles,
Sauerkraut
X
X
X
X
X
IS
40
74
- 72
21
TOTAL
MULTICOWODITY MODELS:
Blanch
Blanch
Blanch
SUBTOTAL
Blanch, Peel
Blanch, peel
— , peel
SUBTOTAL
Blanched Vegetables. Pit/Peel Fruit
Blanch, Pit/Peel
— , Pit/Peel
Blanch, Pit/Peel, Nonbasic, Reprocess, Peel
Blanch, Pit/Peel, Nonbasic, Reprocess, Peel
Blanch, Pit/Peel, Nonbasic, Peel
Blanch, Dehydrate
SUBTOTAL
Brined Products
Brine
Brine
SUBTOTAL
Corn, Pea
Corn, Pea,
Green Beans,
Carrots
Green Beans,
Cherries,
Pears, Plums
Reprocess, Brine
Reprocess, Brine
, Brine
Reprocess, Brine
Reprocess,
Reuroces',
Peprocess,
Reprocess,
Peprocess,
Repro<.rsi, brine
ppproces',, f.rinf:
Reprocess, ['•• «>?
SUITOTAL
Brir.c-
Bi me
Brine
Pickles,
Sauerkraut
Tomato,
Dry Bean
Reprocess
Reprocess
Reprocess, Blanch, Pit/Peel, Dehydrate
Reprocess. B'anrh
Peprocess, Peel
Reprocess, Peel, Nonbasic
Reprocess, Peel, Blanch
Reprocess, Peel, Pit/Peel
Reprocess, Peel, Pit/Peel, Dehydrate
Reprocess, Peel, Blanch, Nonhasic
Reproces's, Peel, Blanch, Pit/Peel
Reprocess, Peel, Blanch, Pit/Peel, Norbasic, Dehy.
SUBTOTAL
Tomato, Dry
Bean, Pickles,
Dressing and
Sauces
Blanch
Nonbasic
Brine, Pit/Peel
Brine, Blanch, Peel
Brine, Blanch, Pit/feel
Brine, Peel, Nonbasic
fctine, Peel
Brine, Pit/Peel
Brine, Blanch
Peel, Pit/Peel
peel, Blanch
Pit/Peel, Blanch
Deli/. , Blanc*,
Pehy. , Blanch , Pit/PeM, Peel
rinnbtuK, lil-pfh, Pit/Tpol, Peel
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
*
X
X
X
X
X
X
X
X
75
24
99
55
10
65
24
21
53
3
6
108
21
20
41
150
148
13
49
7
8
8
1
6
1
7
13
411
81
20
1
7
21
2
1
18
6
4
12
11
3
1
9
200
1,149
-------
Table VII- 11 Number of industry plants, listed in Directory I/, grouped into
representative model plant processing functions and commodities by
model for freezing plants 2/
Process function
MULTICOMMODITY MODELS:
Blanch
Blanch
Blanch
— , Brine
Blanch, Brine
Blanch, Brine, Reprocess
Blanch, Brine, Nonbasic
Blanch, Brine, Nonbasic, Reprocess, Pit/Peel
SUBTOTAL
Blanch, Peel
Blanch, Peel
Blanch, Peel
Blanch, Peel Nonbasic, Pit/Peel
— , — Reprocess
--- , — Reprocess
— , Peel Reprocess
Blanch, Peel Reprocess
Blanch, Peel Brine
Blanch, Peel Brine, Reprocess
Blanch, Peel Sr'nc, Pit/Peel
Blanch, Peel Reprocess, Nonbasic
— , — Reprocess, Dehy.
— , Peel Brine, Nonbasic
Blanch, Peel Brine, Nonbasic, Reprocess, Pit
SUBTOTAL
Pit/Peel , Nonbasic
Pit/Peel , Nonbasic
Pit/Peel , Nonbasic
— , Nonbasic, Dehy.
Pit/Peel, Nonbasic, Dehy., Blanch
SUBTOTAL
TOTAL FREEZING PLANTS
If Judge, Edward E. and Sons, The Directory of
Model plant
commodities
Broccoli ,
Cauliflower,
Lima Beans,
Spinach
Corn, Peas,
Green Beans,
Carrots
, Peel
Cherries,
Cane berries,
Strawberries
the Canning,
Commodity/plant
Single Multi
X
X
X
X
X
X
X.
X X
X
X
X
X
X
X
X
X
X
X
X
X
X
x^
X X
X
X
X
X
X X
Plants
19
11
4
4
3
1
_12_
50
28
8
20
8
9
3
4
5
2
1
1
2
1
3
95
23
26
1
2
52
197
Freezing and Preserving
Industries, 1974-75.
2J Excludes plants primarily freezing apple, citrus, ootato and frozen specialty
products.
VII-29
-------
Table VII- 12 Number of industry plants, listed in Directory If, grouped
into representative model plant processing functions and commodities by
model for dehydrating plants 2/
Model plant Commoditjes/p1ant
Process function commodities Single Multi Plants
MULTICOMMODITY MODELS:
Dehydrate Potato Chips
Dehydrate X . 11
Dehydrate, Peel, Brine . X 1
Dehydrate, Pit/Peel X 1
TOTAL DEHYDRATE 13 3/
\J Judge, Edward E. and Sons, The Directory of the Canning, Freezing and
Preserving Industries, 1974-75.
2J Excludes plants mostly dehydrating apple, citrus and potatoes.
3/ The Directory has few chippers and dehydrators listed. The Census
shows 178 dehydrating plants for 1972 of which 18 were estimated as
dehydrating apples, citrus and potatoes and thus, excluded. This
study shows a total of 160 dehydrators. The Census also lists 256
potato and corn chips and related product processors which will also
be shown in this study.
VII-30
-------
Table VII-13 Grouping of industry plants listed in Directory —' by model
plant and extrapolation to 1972 Census industry group with both sets
of data adjusted to exclude apples, citrus and potatoes
Model Plant
Process Function
Directory
Plants
% of
Total
Census
Plants
Directory
as a percent
of Census
Plants
2032-Canned Specialties
Reprocess +1 131 75 152
Reprocess, Brine U 44 25 _5T_
Total 175 100 203 86
2033-Canned Fruits and Vegetables
Corn 18 2 19
Mushrooms 40 6 58
Sauerkraut 21 3 29
Tomatoes 74 10 96
Blanched vegetables 99 14 134
Blanched and peeled vegetables 65 9 86
Blanched vegetables, Pit/Peel fruit 107 15 144
Reprocess 27 185 27 259
Reprocess, Brine U 96 14 134
Total 705 TOO 959 74
2035-Pickles, Dressings and Sauces
Pickles 73 26 129
Brined Products 41 15 74
Reprocess U 95 36 178
Reprocess, Brine U 60 _23_ 114
Total 269 100 495 - 54
2037-Frozen Fruits and Vegetables
Blanched vegetables 50 25 32
Blanch and Peeled Vegetables 95 48 62
Pit/Peel and Nonbasic fruit 52 27 ' 35
Total 197 100 129 153
2034-Dehydrated Fruits and Vegetables
Potato Chips 13 (NA) 160
20992-Food Preparations (Chips)
Potato Chips
TOTAL
1,360
(NA)
256
2,202
• 62
(NA) - Not applicable since the Directory had too few dehydrators and chippers listed.
— Judge, Edward E. and Sons, The Directory of the Canning, Freezing and
Preserving Industries, 1974-75
21
Plants processing specific commodities as categorized from the Directory
to this process function cross-over three SIC industry groups. For
instance, the Reprocess processing function may represent, in part, jams
and jellies (2033), baby food (2032), and dressings and sauces (2035).
Reprocess and Brine may represent, in part, dry beans (2032), sauerkraut
(2033) and pickles (2035). Distribution of these plants between the
three SIC industry groups was done by (1) reclassifying commodities already
classified under a process function to a four digit industry group, (2)
assigning number of plants processing these commodities, and (3) rationing
the number of plants under an industry group to the total plants in a pro-
cess function.
Model Plant Process Function
SIC Code
2032
2033
2035
Total
Reprocess
of total Plants
32
45
23
100
Reprocess Brine
% of total Plants
131
135
95
411
22
48
30
100
44
96
60
200
VII-31
-------
1. Census - the data has been partitioned into five size groups--
extra small (XS), small (S), medium (M), large (L), and extra
large XL) -- to show the characteristics of plants within a
four digit industry group. The Census data was reflective
of the small plants in an industry group.
2. Survey - this data has been used to size most of the models
used in this study which tend to correspond closely with the
sizing of Census data. As expected, there are smaller plants
in the industry than responded to the survey. In most cases,
these small plants have been added to models shown in this
study.
3. Directory - through classification of plants and commodities
into model plants and maintaining the approximate sizes of
single plant companies shown, this data was helpful in creating
a few sizes and models not indicated by survey data.
Average sizes of plants and their characteristics in each Census four
digit industry group were developed as explained in Chapter II, Segmentation,
Section C, 2. Briefly, concentration ratio functions of plants, production,
employment and payroll were developed using 1967 Census data (1972 yet un-
published) and applying these ratios to 1972 Census data of total number
of plants, production employment and payroll.
The results of the segmentation of each Census industry group is shown
on the top part of Tables VII-U through VII-19 - The segmentation
of Census data was used as a guide in determining the number of model
plants by size group. As outlined above under item 2, survey results
were largely used in sizing models and will not be the same as Census
industry group sizes of plants. However, two or more model plant sizes
and corresponding number of plants will approximate the production of a Census
industry group average plant size and number of plants. Uhere there are
two or more models with two to five sizes of plants representing a Specified
number of industry plants, the models combined total of production, employ-
ment, payroll and value of production will be, in most cases, within plus
or minus 10 percent of the industry group. Representative model plants
by size group and corresponding production,^employment, payroll and
value of production are shown on the bottom portion of each table on
Tables VII-u through VII-19 •
The last two columns of Tables VII-14 through VII-19 specify whether a
representative model plant size was modeled, i.e., financial results de-
veloped. The segmentation of each Census industry group forced the in-
clusion of some extra small, medium, large and extra large plants not
modeled into the list of representative model plants for the following
reasons:
VII-32
-------
Table VII- 14. Summary comparison of canned specialties, industry group (2032) to representative model plants — plants, production, employment,
payroll, and value of production, 1972
Plants
Industry Group and
Model Plants
Canned Specialties
Size
Code
.
XS
S
M
L
. XL
Total
• Number
128
30
14
14
17
203
Percent
63
15
7
7
8
100
Production
Per Plant
per year
(000 raw
.2
5.1 •
17.5
41.9
106.3
13.9
Total
tons)
28
152
245
587
1,808
2,820
Employment
Per
Plant
(No)
Industry
6
84
247
416
969
143
Total
(000)
Payroll
Per
. Employee
(S)
Total
.(mill 5)
Value of Production Model e.
Per Plant
/mil 1
Total Yes N;
vy
Group -2032
.8
2.5
3.5
5.8
16.5
29.1
Representative Model
Reprocessed:
Tomatoes, Dry Beans
<
*~~*
to
CO
Reprocessed and Brined:
Dry Beans, Dressings and
Sauces, Pickles, and
Tomatoes
Total for all model plants
XS
XS
S
M
XL
XL
Subtotal
XS
XS
S
M
XL
Subtotal
96
9
14
11
10
12
152
32
2
5
3
9
51
203
63
6
9
7
7
8
100
63
4
10
6
17
100
100
.2
2.0
7.0
20.0
70.0
125.0
16.8
.2
2.0
6.0 .
18.0
60.0
12.4
15.7
19
18
• 98
220
700
1,500
2,555
6
4
30
54
540
634
3,189
7
42
m
249
648
900
149
7
42
98
228
578
131
144
.7
.4
1.5
2.7
6.5-
10.8
22.6
.2
.1
.5
.7
. 5.2
6.7
29.3
7,484
7,484
7,484
7,484
7,484
7,484
Plants
7,484
7,484
7,484
7,484
7,484
7,484
7,484
7,484
7,484
7,484
7,484
7,484
7,484
7,484
6.0
18.7
26.2
43.4
123.5
217.8
5.2
3.0
11.2
20.2
48.6
80.8
169.1
1.5
.7
3.7
5.2
38.9
50.1
219.2
.1
3.4
11.7
27.9-
70.8
9.3
.1
1.3
4.7
13.3
46.3
83.6
11.2
.1
1.3
4.0
11.9
39.9
8.2
10.4
18.8
101.4
163.3
390.4 -
1,203.1
1,877
9.6 X
11.7 X
65.8 X
146.3 X
463.0 X
1,003.2 X
1,699.6
3.2 X
2.6 X
20.0 X
35.7 X
359.1 X
420.6
2,120.2
-------
Table VII-li Suninary comparison of canned fruit* and vprjetables, industry group (2033) to representative model plants -- plants, production,
employment, payroll, and value of production, 1972
Plants
Ir.d-.stry :rojp and
Model Plants
Size
Code
Number
Percent
production
Per Plant
per year
TOOO raw
Total
tons )
brnslovrcent
Per
Plant Total
(No) (OOOl
Payroll
Per
Employee
R)
Total
(mill S)
Value of Prediction
Per Plant
(mil
Total
. $) — --
Mcceled
Yes No
Industry Group-2033
Canned Fruits and Vegetables
XS
s
M
I
XL
Total
384
240
143
96
96
959
40
25
15
10
10
100
1.4
6.9
20.7
41.1
61.1
15.6
523
1,660
2,961
3,949
5,863
14,956
16 6.1
52 12.4
122 17.4
208 20.0
282 27.1
87 83.0
6,232
6,Z3i
6,232
6,232
6,232
6,232
38.0
77.3
108.4
124.6
168.9
517.3
.3
1.6
4.7
9.4
14.0
3.6
119.7
379.5
677.0
9o:.e
1,340.2
3,419.0
Representative Model Plants
Blanched Vegetables, single
corrjrodi ty : Corn
Blanched Vegetables, single
commodity: Mushrooms
Brined: Sauerkraut
Peeled Vegetables: Tomatoes
P.
Blanched Vegetables, rculti-
comGdity: Corn, Peas
Bla.irhfd and Pe?"ied Vegetables:
Corn, Peas, Green Beans,
Carrots
Blanched Vegetables and Pitted
and/or Peeled Fruit: Cherries
Green Beans, Pears, Plums
Reprocessed: Tomatoes, Dry
Beans
Reprocessed, Brined: Dry
Beans, Dressings and Sauces,
Pickles, Tomatoes
Total All model plants
S
M
Subtotal
XS
XS
XS
S
Subtotal
S
s
Subtotal
XS
S
M
XL
Subtotal
XS
S
L
XL
Subtotal
S
M
L
Subtotal
S
S
M
Subtotal
XS
S
M
XL
XL
Subtotal
XS
S
M
XL
Subtotal
14
5
19
9
20
15
14
58
19
10
29
34
24
19
19
96
40
60
27
7
134
52
21
13
86
51
43
50
144
1G4
65
64
21
5
259
54
33
27
20
134
959
75
25 •
100
15
35
25
25
100
67
33
100
35
25
20
20
100
30
45
20
5
100
60
25
15
ICO
35
30
35
100
40
25
25
8
2
100
40
25
20
15
100
100
5.5
18.0
8.8
.2
1.5
2.5
5.0
2.7
6.0
9.5
7.2
1.5
4.5
25.0
150.0
36.3
3.0
12.0
37.0
120.0
20.0
10.0
25.0
50.0
19.7
5.0
10.0
20.0
11.7
2.0
7.0
20.0
70.0
125.0
15.6
2.0
6.0
18.0
60.0
14.9
16.8
77
90
167
18
30
. 37
70
155
114
95
. 209
51
108
475
2,850
3,484
120
720
999
840
2,679
520
525
650
1,695
255
430
i .non
l|585
208
455
1,280
1,470
625
4,038
108
198
486
1,200
1,992
16,104
44 .6
110 .6
63 1.2
3 0
16 .3
24 .4
41 .6
22 1.3
47 .9
67 .7
55 1.6
16 .5
38 .9
142 2.7
400 7.6
122 11.7
27 1.1
80 4.8
192 5.2
400 2.8
104 13.9
70 3.6
142 3.0
242 3.1
113 9.7
41 2.1
70 3.0
119 6.0
77 11.1
20 2.1
53 3.4
119 7.6
' 314 6.6
400 2.0
84 21.7
20 1.1
47 1.6
110 3.0
279 5.6
84 11.3
87 83.4
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
6,232
3.7
3.7
7.5
0
1.9
2.5
3.7
8.1
5.7
4.4
10.0
3.1
5.6
16.8
47.4
72.9
6.9
29.9
32.4
17.4
86.6
22.4
18.7
19.3
60.5
13.1
18.7
J/ • *t
69.2
13.1
21.2
47.4
41.1
12.5
135.2
6.9
10.0
18.7
34.9
70.4
520.4
1.2
4.1
2.0
.1
.3
.6
1.1
.5
1.4
2.2
1.7
.3
1.0
5.7
34.3
8.3
.7
2.7
8.4
27.4
4.5
2.3
5.7
11.4
4.5
1.1
2.3
4.6
2.7
.5
1.6
4.6
15.0
28.6
3.6
. 5
1.4
4.1
14.7
3.6
3.9
16.3
20.5
37.3
.9
6.0
9.0
15.4
31.3
26.6
22.0
48.6
10.2
24.0
103.3
551.7
794.2
23.0
162.0
226.8
191.8
608.6
119.6
119.7
148. 2
387.5
56.1
93.9
230.0
3S5.0
52.0
104.0
294.4
335.0
143.0
929.4
27.0
46.2
110.7
294.0
477.9
3,699.8
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
-------
Table viI-16 Summary comparison of pickles, dressings, and sauces, industry group (2035) to representative model plants — production,
employment, payroll and value of production, 1972
Industry Group and
Model Plants
Pickles, Dressings and Sauces
Size
Code
XS
S
M
L
XL
Total
Plants
Number
198
124
74
50
49
495
Percent
40
25
15
10
10
100
Production
Per Plant
per year
(000 raw
.1
1.1
5.8
16.7
44.7
7.3
Total
tons)
14
141
430
834
2,192
3,611
Employrient
Per
Plant
(No)
Industry
2 '
14
49
111
194
42
Representative
Brined, single commodity:
Pickles
<
—•
CO
in
Brined, multi commodity:
Reprocessed: Tomatoes, Dry
Beans
Reprocessed and Brined: Dry
Beans, Dressings and Sauces,
Pickles, Tomatoes
Total for all model plants
S
M
M
Subtotal
S
M
M
Subtotal
XS
S
M
XL
Subtotal
XS
S
M
XL
Subtotal
84
19
26
129
48
n
15
74
116
27
18
17
178
74
17
12
11
114
495
65
15
20
100
65
15
20
100
65
15
10
10
100
65
15
10
10
100
100
1.5
6.0
10.0
3.9
1.5
6.0
10.0
3.9
2.0
7.0
20.0
70.0
11.1
2.0
6.0
18.0
60.0
9.9
7.9
125
' 114
260
500
72
66
150
288
232
189
360
1,190
1,971
148
102
216
660
1,126
3,885
10
40
65
25
10
40
65
26
15
50
120
290
57
15
40
115
275
54
44
Total
(000)
Group-2035
.4
1.7
3.7
5.5
9.5
20.8
Payroll
Per
Employee
($)
7,029
7,029
7,029
7,029
7,029
7,029
Total
(mill $)
2.8
11.9 '
26.0
38.7
66.8 .
146.2
Value of Production Modeled
Per Plant
f nfi \ 1 '
v nn i i . .
.1
.4
1.9
5.4
. 14.4
2.4
Total Yes No
£ \
$ ;
5
45
139
269
707
1,165
Model Plants
.8
.8
1.7
3.3
.5
.4
1.0
1.9
1.7
1.4
2.2
4.9
10.2
1.1
.7
1.4
3.0
6.2
21.6
7,029
7,029
7,029
7,029
7,029
7,029
7,029
7,029
7,029
7,029
7,029
7,029
7,029
7,029
7,029
7,029
7,029
7,029
7,029
5.6
5.6
11.9
23.2
3.5
2.8
7.0
13.4
11.9
9.8
15.5
34.4
71.6
7.7
4.9
9.8
21.1
43.6
151.5
.5
1.9
3.2
1.3
.5
1.9
3.2
1.3
.6
2.3
6.4
20.3
3.3
.6
1.9
5.8
19.4
3.2
2.4
42 X
36.1 X
83.2 X
161.3
24 X
20.9 X
48 X
92.9
69.6 X
62.1 X
115.2 X
345.1 X
592.0
44.4 X
32.3 X
69.6 X
. 213.4 X
359.70
1,205.9
Note: Totals may not add due to rounding.
-------
Table VII- 17 Summary comparison of frozen fruits and vegetables, industry group (2037) to representative model plants
employment, payroll, and value of production, 1972
— plants, production,
Industry Group and
Model Plants
Size
Code
Plants
Number
Percent
Production
Per Plant
per year
(000' raw
Total
tons)
Employneiu
Per
Plant Total
(No) (000)
Payroll
Per
Empl oyee
(5)
Total
(mill $)
Value of Production
Per Plant
(mill.
Total
5)
Modeled
Yes No
Industry Group-2037
Frozen Fruits and Vegetables
XS
S
M
L
XL
Total
52
32
19
13
13
129
40
25
15
10
10
100
1.1
7.9
23.3
62.3
121.6
25.1
58
253
537
810
1,580
3,238
18 .9
68 2.2
172 3.3
302 3.9
513 6.7
132 17.0
Representative Model
Blanched Vegetables: Broccoli,
Cauliflower. Lima Beans, Spinach
<:
i
us
-------
Table VII-lu. Summary comparison of dehydrated fruit, vegetables and soup mixes, industry group (2034) to representative model plants —
plants, production, employment, payroll, and value of production, 1972
Industry Group and
Model Plants
Size
Code
Plants
Number
Percent
• • — •—• •
Production
Per Plant
per year
Total
— -
Employment
Per
Plant
Payroll
Per
Total Employee
(000 raw tons) (No) (000)
Industry Group-2034
(S)
Total
(mill $)
-••-•- -—.—..
Value of
— 5—
Production Modeled
Per Plant Total Yes No
(mi
11. $)
Dehydrated Fruits, Vegetables,
and Soup Mixes
XS
s
M
L
XL
Total
64
40
24
16
16
160
40
25
15
10
10 .
100
.6
5.2
20.9
51.4
86.3
18.4
38
207
501
823
1,380
2,949
5
30
94
195
268
70
Representative
Dehydrated:
Potato Chips
XS
M
XL
XL
Total
64
40
40
16
160
40
25
25
10
100
1.0
8.0
30.0
86.3
18.5
64
320
1,200
1,381
2,965
8
44
120
268
71
.3
1.2
2.3
3.1
4.3
11.2
Model £tetnts
.5
1.8
4.8
4.3 '
11.4
6,768
6,768
6,768
6,768
6,768
6,768
6,768
6,768
6,768
6,768
6,768
2.0
8.1 •
15.6
21.0
29.1
75.8
3.4
12.2
32.5
29.1
77.2
.1
.8
3.3
8.2
13.7
2.9
.1
1.3
4.7
13.6
2.9
6.1
32.8
79.6
130.6
218.9
468.0
6.4 X
52.0 X
188.0 X
217.6 X
464.0
-------
Table VII-19
Summary comparison of potato and corn chips, industry group (20992) to representative model plants -- plants, production, employment
payroll, and value of production, 1972
Potato and Corn Chips
Dehydrated:
Potato Chips
Plants
Production
Mo
del
Gr
PI
Oup
ants
and
Size
Code
Number
Percent
Per
per
Plant
year
Total
PC
Pla
Enployment
Total
Payroll
Value Df Production
Per
Employee
Total
Per Plant
(000 raw tons) (No) (000]
Industry -Group-20992
xs
s
M
L
XL
Total
XS
S
S
M
XL
Total
164
31
23
15
23
256
115
' 51
26
38
26
256
64
12
9
6
9
100
45
20
10
15
10
100
1.
12.5
15.4
30.0
6.6
1.0
2.5
8.0
13.0
30.0
6.7
220
253
287
237
692
1,689
29
145
200
24 <••
420
106
4.7
4.5
4.6
3.7
9.7
27.2
ITT"
7,562
7,562
7,562
7,562
7,562
$)
(mi,
Representative Model Plants
115
128
. 208
494
780
1,725
20
50
140
210
420
107
2.3
2.6
3.6
8.0
10.9
27.4
562
562
562
562
562
35.5
34.0
34.8
.28.0
73.4
205.7
17.4
19.
27.
60.
82.6
7,562 207.1
1.0
6.1
9.3
11.5
22.3
4.9
' .7
1.8
5.8
9.4
22 3
4.9
Total Yes No
164
189
214
173
514
1.254
83
92
151
359
- 580
1,265
-------
1. Census data indicated they exist
2. Survey and Directory data did not indicate their existence,
and
3. It was necessary to include them so that model plant production,
employment and payroll would approximate that shown by Census.
In all cases, as later impact analysis will show, the extra small plants
directly discharging and not modeled, would most probably be impacted to the
point of closure since the next size, small plants, modeled indicate closure
resulting from pollution controls. It was deemed unnecsssary to further
model these extra small plants. The extra small plants not modeled
follow:
1. Canners, of canned specialty plants, represented by models
of Reprocess (tomato, dry bean) and Reprocess and Brine
(tomato, dry bean, pickles, dressings and sauces) with an averag(
size of 200 raw tons per year, and representing 128 canned
specialty (2032) plants.
2. Freezers of fruits and vegetables represented by models of
Blanched Vegetables (broccoli, cauliflower, lima beans, and
spinach) and Blanched and Peeled Vegetables (corn, peas, green
beans, and carrots) with an average size of 1,100 raw tons per
year and representing 33 freezing plants.
The medium, large and extra large plants directly discharging and not
modeled are not expected to be impacted to the point of closure. There-
fore they were not modeled. Specifically, these plants are represented
by the following process functions and plant types:
1. Blanched Vegetables (broccoli, cauliflower, lima beans,
spinach), Freezer, large and extra large sizes of 62,000
and 122,000 raw tons per year and totaling 7 plants with
one plant being estimated as a direct discharger (20 percent
of 7).
2. Blanched and Peeled Vegetables (corn, peas, green beans,
carrots) Freezer, extra large size of 122,000 tons per year,
and totaling six plants with one plant being estimated as a
direct discharger (20 percent of 6 plants).
3. Pitted/Peeled and Nonbasic Fruit (cherries, cane berries
and strawberries) Freezer, medium size of 25,000 tons per
year and totaling 4 plants of which one is estimated to be a
direct discharger (17.9 percent of 4 plants).
4. Dehydrated fruits and vegetables (potato chips) Dehydrator,
extra large size of 86,000 tons per year and totaling 16
plants of which one is estimated to be a direct discharger
(7 percent of 16 plants).
VII-39
-------
2. Baseline Closures
Baseline closures are plants which discontinue operations from a baseline
of 1972 and 1977 in this study and have been estimated through trend analysis
by industry group and size for 1977 and 1983. Tables VII-20 through VII-25
show projected plant number trends by size and industry group as well as total
production (tonnage and value) employees and payroll. These tables will
also be referred to in subsequent sections of this chapter,.
a. Total industry
In general, the number of fruit and vegetable canning, freezing and chipping
plants has been declining since 1958 as shown in Chapter II, Table II-4,
of this report. Among the canning group, however, canned specialty plants
have been increasing while canned fruit and vegetable and pickle, dressing
and sauce plants have declined. Dehydrators of fruits, vegetables and soup
mixes have increased from 1947 to present. These trends are expected to
continue as shown in Tables VII-2Q to VII-25 . There are also trends in
number of plants by size group within an industry group which the above
mentioned tables show. Since closures of one size(s) tend to be dispro-
portionate to entry of another size(s) within an industry group, net closures
by industry group, disregarding size, are shown below.
Baseline Closures
Industry Group 1972-77 1977-83 1972-83
2032 Canned Specialties 0 0 0
2033 Canned Fr. & Veg. 134 116 250
2035 Pickles, Dressings 55 35 go
& Sauces
Total Canners 189 - 151 • 340
2037 Frozen Fr. & Veg. 19 Q 19
2034 Dehydrated Fr. & Veg. 0 0 0
20992 Food Prep. - Chips 26 31 57
Total 234 . 182 416
Plant numbers for the fruit and vegetable processing industry are expected
to decline from 1972 through 1983 at an annual compound rate of about 2.0
percent per year with some increasing an estimated maximum of 1.5 percent
per year and others declining as much as 2.7 percent per year.
b. Industry group
Canned Specialties (2032). Canned specialty plants are expected to continue
to increase from 1972 through 1983 at an approximate rate of 1.5 percent per
year. Expected changes in number of plants by size group follow:
VII-40
-------
Plant Chanoes
Size 1972-77 1977-83 1972-83
XS -1 0 -1
S +2 +3 +5
M +3 +7 +10
L +3 +7 -HO
XL +2 +7 +9
Total +9 +24 - +33
Based on trends as shown in Table VII-2o> it is anticipated that the per-
cent of medium to extra large size plants of total in the .canned specialty
group will increase. The proportion extra small plants are of total is
expected to decline and small plants will stay about the same.
Canned Fruits and Vegetables (2033). Canned fruit and vegetable plants have
been trending downward for several Census periods and are expected to decline
from 1972 through 1983 at an annual compound rate of about 1.5 percent. As
shown in Table VII-21, the proportion of extra small and small plants is
expected to decline relative to total plants in this group. The number of
medium plants is anticipated to decline at this industry's rate, but as a
percent of total, stay the same. The number of large plants is expected
to increase as is the proportion of these plants to total. Although the
proportion of extra large plants to total is expected to increase, the rate
of increase is less than the industry group rate of decline and thus, a
small decline in number of extra large plants. Expected changes in number
of plants by size follow:
Plant Changes
Size 1972-77 1977-83 1972-83
XS -79 -70 -149
S -49 ' -44 -93
M -20 -16 -36
L +18 +15 +33
XL ~4 -1 -5
Total -134 -116 -250
Pickles, Dressings and Sauces (2035). The pickles, dressings and sauces
industry group of plant numbers has been trending downward for several
Census periods and is anticipated to decline from 1972 through 1983 at an
annual compound rate of approximately 1.8 percent. Considering the de-
clining rates of the general industry group and proportion to total plants,
the number of extra small to medium size plants is expected to decline.
VII-41
-------
from 1972 through 1983 (see Table VII-22). The ratio of large plants to
total in the industry group is projected to stay about the same, and since
total industry plants are declining, there is a small expected decline in
large plants. The number of extra large plants is projected to increase
between 1972 and 1983. The anticipated change in number of plants by size
group is:
Plant Changes
Size 1972-77 1977-83 1972-83
XS -26 -22 -48
S -17 -13 -30
M -10 -8 -18
L -6 -4 -10
XL +4 +12 +16
Total -55 -35 -90
Frozen Fruits and Vegetables (2037). The frozen fruit and vegetable in-
dustry group, excluding frozen specialties, has been trending downward
since the Census period of about 1958. The total number of these plants
was about the same for the two periods of 1958 and 1963 (260 and 2!58,
respectively), declined to 1967 (209) and stayed the same in 1972 (209).
A judgment was made to regress the number of total plants to 1977 (according
to a line-of-fit) of 179 plants and hold them constant in 1983 at 179 plants
in accord with the 1958-63 and 1967-72 relationships. The number of frozen
apple, citrus and potato plants were adjusted out of the projected 178
plants by the same ratio estimated for these plants in 1972 (38.6 percent).
The projected numbf- of freezer plants within the scope of this study in 1977
and 1983 is 110 representing compound rates of decline from 1972 of about 3.0
percent and 1.5 percent in 1977 and 1983, respectively. The oroportion of
extra small, small and medium plants to the declining number of total
plants is expected to also decline in this industry. However, the number
of large and extra large plants is expected to increase as shown in Table
VII-23.
.Anticipated changes in number of frozen fruit and vegetable plants by size
group from 1972 through 1983 follow:
Size
XS
S
M
L
XL
Total
VI1-42
Plant Changes
1972-77
-11
-7
-4
+4
-1
-19
1977-83
-5
-2
-1
+6
+2
0
1972-83
-16
-9
-5
+ 10
+1
-19
-------
Dehydrated Fruits, Vegetables and Soup Mixes (2034). The dehydrated fruit,
vegetable and soup mix industry group had been increasing since Census data
was published for this group in 1947 to about 1963 when they appear to have
about leveled out. Therefore, trend analysis indicates a moderate increase
in total plant numbers of about 1.0 percent per year compounded from 1972
to 1983 excluding apple, citrus and potato dehydrators.
The projected trends from 1972 to 1983 in the proportions of extra small
to total plants in this industry group show a slight decline; small to large
plants, steady; and extra large plants, a slight increase. Coupling these
slight changes in proportions of plants to total by size group with a mod-
erate increase in number of total industry group plants, all size groups are
expected to increase in plant numbers from 1972 to 1983. See Table VII-24.
for detail.
The estimated net changes in number of plants from 1972 to 1983 is shown
below.
Plant Changes
Size 1972-77 1977-83 1972-83
XS +3 0 +3
S +3 +1 +4
M +1 +2 +3
L +1 +1 +2
XL +3 +2 +5
Total +11 +6 +17
Food Preparations, Potato and Corn Chips, Curls and Related Products (20992).
The potato and corn chip product class has been declining in plant numbers
for several Census periods. According to trend, this group of total plants
is expected to decline at an annual compounded rate of about 2.3 percent.
There was insufficient Census data to project trends in number of plants by
size group for potato and"corn chip and related products plants. Therefore,
the proportion of plants to total in each size group was assumed constant and
the number of plants to decline at the industry group rate as shown in Table
VII-25 Since the largest portion of total plants is in the extra small size
group,'they account for the largest number of'closures. The estimated changes
in number of plants by size group are as follows: .
Size
XS
S
M
L
XL
Total -26 -31 -57
VII-43
Plant Changes
1972-77
-17
-4
-2
-1
_2
1977-83
-20
-3
-3
-2
-3
1972-83
-37
-7
-5
-3
-5
-------
Table VII-20. Summary of basic assumptions of percent and number of total
plants, production, value of production, employees and payroll by size group for
the canned specialties (2032) industry group for 1972 •
and trends to 1977 and 1983 I/'
1972 1977 1983
Size
XS
S
M
L
XL
TOTAL
Item
Plants
Production
Production
Employees
Payroll
Plants
Production
Production
Employees
Payrol 1
'Plants
Production
Production
Employees
Payroll
Plants
Production
Production
Employees
Payrol 1
Plants
Production
Production
Employees
Payroll
Plants
Production
Production
Employees
Payrol 1
Unit
No.
000 raw tons
$ n'ii 11 ion
000
$ mi 11 ion
No.
000 raw tons
$ million
000
$ million
No.
000 raw tons
$ mi 11 ion
000
$ mill ion
No.
000 raw tons
$ mill ion
000
$ mill ion
No.
000 raw tons
$ million
000
$ million
No.
000 raw tons
$ mill ion
000
$ mill ion
% of
Total
63.0
1.0
1.0
2.8
2.8
15.0
5.4
5.4
8.7
8.7
7.0
8.7
8.7
11.9
11.9
7.0
20.8
20.8
20.0
20.0
8.0
64.1
64.1
56.6
56.6
100.0
100.0
100.0
100.0
100.0
% of
Units Total
128.0 60.0
28.2
18.8
.8
6.1
30-0 15.0
152.3
101.4
2.5
18.9
14.0 R.n
245.3
163.3
3.4
25.9
14.0 8.0
586.6
390.4
5.8
43. 6~
17.0 9.0
1,807.6
1,203.2
16.4
123.3
203.0 100.0
2,820.0 100.0
1,877.0 100.0
29.1 100.0
217.8 100.0
% of
Units Total
127.0 54. n
32.0 15.0
17.0 10.0
17.0 10.0
19.0 11. .0
212.0 100.0
3,038.0 10Q.O
2,955.0 100.0
30-7 100.0
291.5 100.0
Units
127.0
35.0
24.0
24.0
26.0
236.0
3,322.0
4,560.0
32.9
413.5
I/ Historic data source was Census of Manufactures Bureau of Census, and
trends were compiled by DPRA. Apples, citrus and potatoes are excluded.
Value of production and payroll are in terms of current dollars. Production
is assumed to increase at an annual compound rate of 1.50 percent.
VII-44
-------
Table VII-.21 Summary of basic assumptions of percent and number of total
plants, production, value of production, employees and payroll by size group for
the canned fruit and vegetable (2033) industry group for 1972
and trends to 1977 and 1983 I/
1972
Size
XS
S
M
L
XL
TOTAL
Item
Plants
Production
Production
Employees
Payroll
Plants
Production
Production
Employees
Payroll
Plants
Production
Production
Employees
Payroll
Plants
Production
Production
Employees
Payroll
Plants
Production
' Production
Employees
Payroll
Plants
Production
Production
Employees
Payroll
Unit
No.
000 raw tons
$ million
000
$ million
No.
000 raw tons
$ million
000
$ million
No.
000 raw tons
$ million
000
$ mi 1 1 i on
No.
000 raw tons
$ million
COO
$ million
No.
000 raw tons
$ million
000
$ million
No.
000 raw tons
$ million
000
$ million
% of
Total
40.0
3.5
3.5
7.4
7.4
25.0
11.1
11.1
14.9
14.9
15.0
19.8
19.8
21.0
21.0
10.0
26.4
26.4
24.1
24.1
10.0
39.2
39.2
32.6
32.6
100.0
100.0
100.0
100.0
100.0
Units
384.0
523.5
119.7
6.1
38.0
240.0
1,660.1
379.5
12.4
77.3
143.0
2,961.3
677.0
17.4
108.4
96.0
3,948.4
902.6
20.0
124.6
96.0
5,862.8
1,340.2
27.1
168.9
959.0
14,956.0
3,419.0
83.0
517.3
1977
% of
Total Units
37.0 305.0
23.2 191.0
15.0 123.0
13.8 H4.0
11.2 92.0
100.0 825.0
100.0 16,112.0
100.0 5,382.0
100.0 76.36
100.0 692.3
1983
% Of '
Total
33.1
20.7
15.0
18.2
12.8
100.0
100.0
100.0
100.0
100.0
Units
235.0
147.0
107.0
129.0
91.0
709.0
17,617.6
8,306.0
70.25
982.0
l/_ Historic data source was Census of Manufactures, Bureau of Census, and
trends were compiled by DPRA. Apples and citrus are excluded. Production
is assumed to increase at a compound rate of 1.75 percent per year. Value
of production and payroll are in terms of current dollars.
VII-45
-------
Table VII-22. Summary of basic assumptions of percent and number pf total
plants, production, value of production, employees and payroll by size group for
the pickle, dressing and sauces (2035) industry grouo for 1972
and trends to 1977 and 1983 I/
1972
Size
XS
S
. ;
XL
TOTAL
Item
Plants
Production
Production
Empl oy-e-ci
Payroll
Plants
Production
Production
Employees
Payroll
'Plants
Product! on
Production
Employees
Payroll
Plants
Produc ti on
Product! en
FnnTrv '"--••><•
'-•"r ' ^-> ' •
Payrol 1
Plants
Produc lice,
Product! en
Empl oyc es
Payroll
Plants
Production
Producti en
Employees
Payrol 1
Unit
No.
COO raw tees
S mi "i 1 ion
00 ^
uu
$ mi 11 ion
No.
000 raw tons
S nil 1 ion
000
$ mill ion
No.
000 raw tons
$ nmicn
p. on
U-j-.j
$ mi 1 1 i on
j i
i \ V J ,
0?0 raw tens
$ million
0 0 "
$ mi 11 ion
No.
OCO r:.,-: tons
$ million
OCO
$ mi i 1 i on
No,
000 raw tons
S mi 1 "> ion
nno
(J-ju
$ mi 1 1 i on
% of
Total
40,0
0.4
- 0.4
1.9
1.9
25.0
3.9
. 3.9
8.2
8.2
'15.0
11.9
11.9
17,6
17,6
10.0
23.1
23.1
26.7
26.7
10.0
60.7
60,7
45.6
45,6
100.0
100.0
100.0
100.0
100.0
Units
198.0
14.4
4.7
0.4
2.8
124.0
140.8
45.4
1.7
11.9
74.0
429.7
138.6
3.7
26.0
50.0
834,1
269.1
5.6
38.7
49.0
2,191.9
707.2
9.5
66.8
495.0
3,611.0
1,165,0
20.8
146.2
1977
% of
Total Units
39.0 172.0
24.3 107.0
14.7 64.0
10.0 4-1,0
12.0 53,0
100.0 440.0
100.0 4,186.0
IQO.o 1,963.0
100.0 21.3
100.0 209.9
1983
% of
Total
37.0
23.1
13.9
10.0
16.0
100.0
100.0
100.0
100.0
100.0
Units
150.0
94. G
56.0
40.0
65.0
405.0
4,998.3
3,?92.1
22.4
323.9
•_/ Historic data source was Census of Manufactures, Bureau of Census and trends
were compiled by DDRA. Apples, citrus and potatoes are excluded. Production
"is assumed to increase at an annual compound rate of 3 percent. Value of pro-
di,< tion and payroll are in terms of current dollars.
VII-46
-------
Table VII-23. Summary of basic assumptions of percent and number of total .
plants, production, value of production, employees and payroll by size group for
the frozen fruit and vegetable (2037) industry group for 1972
and trends to 1977 and 1983 I/
1972
Size
XS
S
M
L
XL •
TOTAL
Item
Plants
Production
Production
Employees
Payroll
Plants
Production
Production
Employees
Payroll
Plants
Production
Production
Employees
Payroll
Plants
Production
Production
Employees
Payrol 1
Plants
Production
Production
Employees
Payroll
Plants
Production
Production
Employees
Payroll
No.
000
$ mi
000
$ mi
No.
000
$ mi
000
$ mi
No.
000
$ mi
000
$ mi
No.
000
$ mi
000
$ mi
No.
000
$ mi
000
$ mi
No.
000
$ mi
000
$ mi
Unit
% of
Total
40.0
raw tons
llion
llion
raw tons
llion
llion
raw tons
11 ion
1 1 i on
raw tons
11 ion
Hi on
raw tons
1 1 i on
llion
raw tons
llion
11 ion
1.8
1.
5.
5.
25.
7.
7.
12.
12.
15.
16.
16.
19.
19.
10.
25.
25.
23.
23.
10.
48.
48.
39.
39.
100.
100.
100.
100.
100.
8
6
6
0
8
8
9
9
0
6
6
2
2
0
0
0
1
1
0
8
8
2
2
0
0
0
0
0
Units
52.
,0
1977 1983
% of
Total
36.9
% of
Units Total
41.0 33.1
Units
36.0
58.3
13.
0.
5.
32.
252.
59.
2.
13.
19.
537.
125.
3.
20.
13.
809.
189.
3.
23.
13.
1,580.
368.
6.
40.
129.
3,238.
756.
17.
103.
,6
,9
5
0
6
0
2
4
0
5
5
3
1
0
5
0
9
8
0
1
9
7
9
0
0
0
0
7
23.
13.
15.
11.
•
100.
100.
100.
100.
100.
0
9
0
2
0 '
0
0
0
0
25.0 20.6
15.0 12.5
17.0 21.0
12.0 12.8
no.o 100.0
3,939.5 100.0
1,332.3 100.0
19-2 100.0
155.9 100.0
23.0
14.0
23.0
14.0
110.0
4,984.7
2,360.2
22.2
254.3
If Historic data source was Census of Manufactures, Bureau of Census, and trends
. were compiled by DPRA. Apples, citrus and potatoes are excluded. Production
is assumed to increase at an annual compound rate of 4 percent. Value of
production and payroll are in terms of current dollars.
VII-47
-------
Table VII- 24. Summary of basic assumptions of percent and number of total
plants, production, value of production, employees and payroll by size group for
the dehydrated fruit and vegetable (2034) industry group for 1972
and trends to 1977 and 1983 I/
1972
Size
XS
S
M
L
XL
TOTAL
Item
Plants
Production
Production
Employees
Payroll
Plants
Production
Production
Employees
Payroll
Plants
Production
Production
Employees
Payrol 1
Plants
Production
Production
Employees
Payroll
Plants
Production
' Production
Employees
' Payroll
Plants
Production
Production
Employees
Payroll
Unit
No.
000 raw tons
$ million
000
$ million
No.
000 raw tons
$ mil 1 ion
000
$ million
No.
000 raw tons
$ mi 11 i on
000
$ million
No.
000 raw tons
$ mill ion
OOC
$ million
No.
000 raw tons
$ mi 11 i on
000
$ million
No.
000 raw tons
$ million
000
$ million
% of
Total
40.0
1.3
1.3
3.1
3.1
25.0
7.0
7.0
10.7
10.7
15.0
17.0
17.0
20.1
20.1
10.0
27.9
27.9
27.8
27.8
10.0
46.8
46 '.8
38.3
38.3
100.0
100.0
100.0
100.0
100.0
Units
64.0
38.3
6.1
0.4
2.0
40.0
206.4
32.8
1.2
8.1
24.0
501.3
79.6
2.2
15.6
16.0
822.8
130.6
3.1
21.0
16.0
1,380.1
219.0
4.3
29.1
160.0
2,949.0
468.0
11.2
75.8
1977
% of
Total Units
39.0 67.0
25.0 43.0
15.0 25.0
10.0 17.0
11.0 19.0
100.0 171.0
100.0 3,099.4
100.0 720..1
100.0 11.2
100.0 99.1
1983
% of '
Total
38.0
25.0
15.0
10.0
12.0
100.0
100.0
100.0
100.0
100.0
Units
67.0
44.0
27.0
18.0
21 .0
177.0
3,290.1
1,080.7
12.6
136.6
I/ Historic data source was Census of Manufactures, Bureau of Census, and trends
were compiled by DPRA. Apples, citrus and potatoes are excluded. Production
. is assumed to increase at an annual compound rate Of 1 percent. Value of
production and payroll are in terms of current dollars.
VII-48
-------
Table VII- 25 Summary of basic assumptions of percent and number of total
plants, production, value of production, employees and payn 11 by size group for
the chip portion of food preparations (2099) industry group for 1972
and trends to 1977 and 1983 I/
1972
Size
XS
S
M
L
XL
TOTAL
Item
Plants
Production
Production
Employees
Payroll
Plants
Production
Production
Employees
Payroll
Plants
Production
Production
Employees
Payrol 1
Plants
Production
Production
Employees
Payrcl 1
Plants
Production
Production
Employees
' Payroll
Plants
Production
Production
Employees
Payrol 1
Unit
No.
000 raw tons
$ million
000
$ million
No.
000 raw tons
$ million
000
$ million
No.
000 raw tons
$ million
000
$ million
No.
000 raw tons
$ million
000
$ million
No.
000 raw tons
$ mi 11 i on
000
$ million
No.
000 raw tons
$ million
000
$ mi 1 1 i on
% of
Total
64.0
13.1
13.1
17.3
17.3
12.0
15.1
15.1
16.5
16.5
9.0
17.0
17.0
16.9
16.9
6.0
13.8
13.8
13.6
13.6
9.0
41.0
4LO
35.7
35.7
100.0
100.0
100.0
100.0
100.0
Units
164.0
221.3
164.3
4.7
35.6
31.0
255.0
189.4
4.5
33.9
23.0
287.1
213.2
4.6
34.8
15.0
233.1
173.1
3.7
28.0
23.0
692.5
514.1
9.7
73.4
256.0
1,689.0
1,254.0
27.2
205.7
1977 1983
% of
Total
64.0
12.0
9.0
6.0
9.0
100.0
100.0
100.0
100.0
100.0
% of
Units Total
147.0 64.0
27.0 12.0
21.0 9.0
14.0 6.0
21.0 9.0
230.0 100.0
1,958.0 100.0
2,113.1 100.0
32.3 100.0
295.3 100.0
Units
1Z7.0
24.0
18.0
12.0
18.0
199.0
2,338.0
3,543.9
36.6
455.7
\j Historic data source was Census of Manufactures Bureau of Census and trends
were compiled by DPRA. Includes potato and corn chips and related products
only. Production is assumed to increase at an annual compound rate of 3
percent. Value of production and payroll are in terms of current dollars.
VII-49
-------
3. Closure Criteria
The impact of proposed effluent guidelines, in terms of the number of plants
which may be forced to close, must be evaluated in the context of those
major factors which bear on the closure decision. Certain of these factors
can be quantified, others are subjective or personal and are not quantifiable.
There is no neat single equation or system of simultaneous equations which
will mathematically determine the number of expected closures;. In this
situation, the estimate of the number of potential plant closures becomes
a value judgment, based on detailed industry information, established
economic and financial relationship and knowledge concerning the conditions
confronting the industry. It is possible to identify major factors, to
quantify some and to establish threshold values which are indicative of
expected industry actions. Such a process can be organized into a "decision
table" and a psuedo-objective rating system can be developed to predict
plant closures. This is the general process followed in this analysis.
There are six quantifiable factors and one subjective (or X) factor basic
to the closure analysis:
1. Price increase required to offset pollution control costs
2. Reduction in industry incomes if prices are not increased
3. Reduction in industry return on sales if prices are not increased
4. Reduction in return on investment if orices are not increased
5. Alterations in cash flows if prices are not increased
6. Changes in net present values if prices are not increased
7. Other factors (the X factor) including:
a. Competition from imports
b. Competition from substitute products (e.g. fresh)
c. Price and income elasticity of demand -- the importance and
status of the products in the consumers' food budget.
Based on these seven factors, threshold values have been established for
three levels of impact: '
* Seriously impact to the extent that the plant may be expected to
close rather than install the required waste treatment system.
* Medium impact, but sufficiently serious that a combination of
factors may force plant closure.
* Nominal impact so that the plant will install required treatment
systems and remain in operation.
Threshold values established for each of these factors and impact levels
are as follows:
VII-50
-------
1. Price increased required
a. Serious impact - required price increase over 8 percent
b. Medium impact - required price increase 3 to 8 percent
c. Nominal impact - required price increase under 3 percent.
2. After tax income (thousands of dollars)
a. Serious impact - negative after tax income
b. Medium impact - reduction in after tax income of 50 percent or
greater
c. Nominal impact - reduction in after tax income of less than 50
percent.
3. Return on sales
a. Serious impact - negative return on sales
b. Medium impact - drop of greater than one percent, but return
still positive
c. Nominal impact - drop of less than one percent, returns positive.
4. Return on investment
a. Serious impact - negative return on investment
b. Medium impact - return reduced by 50 percent or greater but
still positive
c. Nominal impact - return reduced by less than 50 percent and
still positive.
5. Cash flow
a. Serious impact - negative cash flow
b. Medium impact - cash flow less than annual depreciation
c= Nominal impact - cash flow positive and greater than annual
depreciation.
6. Net present value
a. -Serious impact - negative net present- value
b. Medium impact - net present value less than 50 percent of base case
c. Nominal impact - positive net present value but greater than 50
percent of base case.
7. X factor
a. Serious impact - impact competition, or close substitutes a
serious problem
b. Moderate impact - moderate competition from imports or substitutes,
item a luxury food.
c. Nominal impact - slight competition from imports or substitutes,
item a moderate luxury food.
VII-51
-------
4. Closure Evaluation Procedure
The relative impacts for each quantitative factor were assigned a score
as follows:
Score
* Severe impact 2
* Moderate impact 1
* Nominal impact 0
The X factors were assigned a score of 0, 1, 2, or 3.
On the basis of the seven criteria and the arbitrary weights assigned to
the degree of impact, each of the model plant situations^was scored on each
criterion for each treatment system. The higher the aggregate score on
all seven criteria, the more serious the impact.
These scores were compiled for each model plant for BPT and for BAT under
3 levels of inplace controls based on aerated lagoon costs. The sum of
the 3 levels were then aggregated for each model plant and BPT on BAT effects
added together. To these results was then added the X factor for the
plant based on 0 to 3 points.
From the analysis of all plants by means of these 7 factors, an evalu-
ation or decision scoring table has been established as follows:
Score Impacts result Symbol
23 - 59 Plant will close C
9-22 Plant may close under certain conditions M
0-8 Plant will operate with installed treatments 0
5. Projected Plant Closures
Based on segmentation of the industry, price effects, financial effects
and other factors indicated under closure criteria, projections were made
of potential plant closures by representative model plant group (Table
VII-26) and industry group (Table VII-27).
In general, the extra small and small plants were most highly impacted,
primarily because of economies of scale which exist in pollution control
costs. In addition, those industry segments having lower-than-average
returns suffered, e.g. the freezing industry and pickle processors. The
canning industry was not as highly impacted as most other segments be-
cause of a higher proportion of both larger plants and multi-product
plants.
In summary, the plant closures indicated were as follows:
VII-52
-------
Table VII- 26. Estimated plant closures, direct dischargers, model plant groups, BPT and BAT
Commodities
Mode
1. Corn
la. Corn
2 Mushroom
3 Mushroom
4 Mushroom
5 Mushroom
6. Pickle
7 Pickle
8 Pickle
9 Sauerkraut
10 Sauerkraut
1 1 . Tomato
12. Tomato
13 Tomato
14 Tomato
Plant Group
-- -
j
T ' "
15 Corn Pea
16. Corn Pea
1 7 Corn Pea
18. Corn Pea j
[
39 Corn Pea G.
20 Corn Pea G
21 . Corn Pea G
22. Corn Pea G.
23. Corn Pea G.
24. Corn Pea G.
25. Corn Pea G.
26 Corn Pea G.
27 Broc C F. L
28 Broc C F. I
29 Broc C.F. L
30 Tomato DB
31 Tomato DB
J. Carr
3. Carr;
Type
-
c
c
c
c
c
c
c
c
c
.._ -[
it
)t
B. Carrtt
i Carr
i Carr
B Carr
J. Carr
B Spin
B Spin
B Spin
32 Tomato DB J
33__TpjMtp OB j
34. Tomato DB |
35. Cherry 68 F
36 Cherry 68 F
37. Cherry 68 F
38 Cherry Stri
39. Cherry Stra
40 Cherry Strc
41 Pickle Tom
ear Plu
ear Plu
ear Plu
w B Can
w B Can
w B Can
DB Ores
42 Pickle Tom |DB Ores
43. Pickle Tom
44. Pickle Tom
45. Brined Pro
46 Brined Pro
47 Brined Pro
48. Potato Chip
49. Potato Chip
50 Potato Chip
51. Potato Chip
52 Potato Chip
Total
DB Ores
DB Ores
duct
duct
duct
Dt
Dt
Dt
Dt
Dt
1
r
_L
c
c
c
c
c
c
c
Size Tons
Code [Year
S
M
XS
XS
XS
s
s
M
M
r
s
XS
s
M
XL
XS
c | s
C : L
c
c
c
c
F
F
F
F
F
F
F
F
C ]
XL
S
5,500
8,000
200
1,500
2,500
5,000
1,500
6,000
10,000
6,000
9,500
1,500
4,500
>5,000
150,000
3,000
12,000
37,000
120,000
10,000
25,000
L | 50,000
1
&
S
M
M
L-'
~w
M
5,000
Baseline I/ No. Rep Baseline I/No. Rep Est Dir Discharger Closures
by Model Plants Dir Dischargers Aer Lag Act Sludge
TTO PnrrTJHJ Vfn T977 "T9BW KPT ^STfT "7"BF1 r^AT
14
5
9
20
15
14
84
,9
26
19
10
34
24
19
19
40
11
4
7
16
12
11
—72-
16
23
15
8
27
19
16
19
32
60 48
27 44
7 7
52
21
13
28
10.000J 6
18,000,
25,000
50,000
8,000
25,000
M^' | 40,000
j_
C s ' 7,000
1C I M 1 20,000
C
1 c
- 4- -1
41
18
22
1- 23 \
5
3 1-T]
TT T
9
4
6
12
9
9
63"
14
19
12
6
21
15
14
19
25
38
59
7
32
15
29
19
4
2
7
16 1 18 I 25
1 IT"
19 1 15
3 t 2
10 1 10
S325
287
106 ]_ 90
93 85
XL | 70,0od 48 1 56
XI |l25,GGGi I/ ] 18
1 r
i i
h 1 c
n
n
e B
e B J_
s S S
s S S
S S
&S j
1
[
T~
;
c
c
S 5,000
S I 10,000
M 1 20,000
1
F XS 1 800
p
XS
F 1 S-'
c xs-'
c s
_j_.
M
2,000
5,000
2,000
6,000
18,000
XL 60,000
43
50
41
34
43
16 | 12
5
14
162
42
40
, i ,
C j S J 1,500
C T M
C
_A.-
D XS
D ! S
D | S
D ' M
0 ! XL-J-'
6,000
10~,000
48
11
15
1,000
2,500
8,000
13,000
179
51
66
38
t 4
14
1
0
1
1
1
1
"T2
' 3
3
5
2
7
5
4
3
1
0
0
1
1
._
— 9-
2
3
0 1
0 0
0 |~ F
1 I E
1
1
""T
i
2
4 r 4
2
5
4
3
4
a"1 6
' 12 ~\ 9
5 i
^
8
1
11
4
3
5
1
1
2
3
4
8
3
3
4
1
0
!
i 2
0
4
3
4
JT-
9
8
1
8
_1_
0
' 0
E
1
1
0
0
E
0
0
0
0
0
0
0
0
0
0
0
E
E ,
0
0
E
0
0
0
0
E
0
0
0
0
0
0
0
0
0
3 0 ' 0
2
I- I
-.?..!. 0
0 | 1
o : o
1 0 i 0
3 J 3 T 0 T 0 n
4
2 , 1 [ 0
. ._!__
258 F 54
77 I 18
79 j 15
69
32
27
37
11
r 4
12 j 10
1 "
141 ! 123
38 , 35
4fi
41
10
13
171
46
66
RQ
36
44
14
12
8 ^ 9
~~ 3 i 3
"1
8 L s j
61 4
_ . ,
2 j 2
0
o
22
0
0
c
14 , 0
-r.
5
4
6
1
3 J 2
1 1 1
0
0
0
0
0
0
0 E
1 f" E
rrv-
0
0
0
F.
0
0
0
0
0
0
0
E
E
0
27 t 22 j 22 T" E f E 1
9 1 7 1 7 ! 0 1 n
7 7
7
9
8~1 * -1
-n't" "3-
" f " " ~
171
46
66
34 34
30.000J 82 ^ 84 J_ 84
?,202 1,988 ,861
Baseline - number of plants prior to imposition of
12
7
7
" ? i
3
11
3 J 3
5 * 5 -1
" 3 -*— 2 "
6 6
331 275
effluent contro s
7 i 0
7 0
1
o
f
0
E
1
1
0
0
E
2
0
0
0
0
F
.
0
....
E
0 "
0
0
0
E
0
2
- - -
3 T o
0 j 4
0
0
4
0
0
2
1
0
0
1
4
0
0
0
2
0
0
0
0
1
1
0
0
0 0
" J
F
7
0
0 1 6
0 1 4
fl j 0
_ _..j
0 f 0
• o j o
0 0
E
E,
0
E
n
0 ' 0
0 0
4 4- E 1 F -1
2 j 0 ]_ 0
3 1 0 0
E
1
1
1 I
5 | E I E j E
3 0 , 0 j~ 2
^^-"-l-'i-l
_i I
0
6 0 T o ] 1
220 7 1 33
E
E
0
E
Q
0
1
E
0
n
[
0
0
2
23
— Includes some larger plants
V
Baseline no of direct dischargers after BPT aerated lagoon closures
E - Exempt
-------
Table VII-27 summarizes plant closures by industry group. In determining
the probable total number of closures, it was recognized that not all
plants will be able to install aerated lagoons. Site problems, climate,
land availability and other factors may require the use of activated sludge
systems. EPA estimates that approximately ten percent of the plants may
be forced to use activated sludge systems. To reflect this possibility,
closures were based on the number of plants impacted where aerated lagoons
were used plus ten percent of the number of plants impacted as the result
of the use of activated sludge systems.
VII-54
-------
Table VII-27. Estimated plant closures, industry groups, direct dischargers, BPT and BAT guidelines
Industry Group
SIC Code Plant Category
2032
2033
2035
2037
2034
20992
Total
- Canned Specialties
- Canned fruits & vegetables
- Pickles, dressings and
sauces
- Frozen fruits and
vegetables
- Dehydrated fruits and
vegetables
- Food preparations - chips
, all categories 2
Estimated total
plants
1974
203
959
495
129
160
256
,202
1977
212
825
440
1TO
171
230
1,988
number
Est.
No. Dir. Di
Aerated lagoon
1983
236
709
405
no
177
199
1,836
BPT
0
1
2
4
0
0
7
Incr. BAT
0
0
0
1
0
0
1
BPT + BAT
0
1
2
5
0
0
8
scharge Plant Closures
Activated sludqe
BPT
1
1
0
1
0
0
3
Incr. BAT
1
1
0
0
0
0
2
BPT + BAT
2
2
0
1
0
0
5
I
en
en
-------
Year
1974 1977 1983
1. Total number, baseline plants 2,202 1,988 1,861
2. Number of direct dischargers 331 275 220
3. Percent direct dischargers 15.0% 13.8% 11.8%
4. Plant closures - aerated lagoons - 7 1
5. Percent closures of direct dis-
chargers, aerated lagoons - 2.5% 0.5%
6. Plant closures - activated sludge 3 2
7. Percent closures of direct dis-
chargers, activated sludge - 1.1% 0.9%
6. New Source Performance Standards
New Source Performance Standards apply to any source for which construction
starts after the publication of the proposed regulations for the Standards.
New Source Performance Standards are based on an analysis of how the level
of effluent may be reduced by changing the production process itself as
well as through effluent treatment technology.
As specified by the Effluent Guidelines Division, EPA, the effluent limitation
for new sources is the same as that specified for the best available technol-
ogy economically achievable (1983 BAT) level. !_/ It is assumed that this
limitation is achievable in newly-constructed plants on the basis of presently-
available technology. It is proposed that land disposal remains the most
desirable disposal method and that land availability requirements for treat-
ment can be considered in site selection for a new plant.
It is not anticipated that New Source Performance Standards will have an
effect on entry of new firms into the industry. This conclusion is based
on the following factors:
1. NSPS regulations are, for this industry, identical to BAT (1983)
regulations.
2. New plant construction in the industry is. expected to be limited
to larger plants—over 10,000 tons.
— Draft Development Document for Effluent Limitations Guidelines New
Performance Standards for the Canned and Preserved Fruits and Vegetables
Industry Point Source Category, prepared by SCS Engineers for EPA.
VII-56
-------
3. New plants, when built, should be able to incorporate into
their design in-plant operating systems which will minimize
effluents and could also engineer effluent abatement systems
specifically tailored to the plant and its site. The result
should be minimum effluent volume and maximum effluent treat-
ment efficiency which should produce lower-than-average
effluent control costs.
4. The impact analysis for BAT standards showed only one plant
closed (a small freezer) where aerated lagoons were the pro-
posed abatement system and only BAT two closures with activated
sludge systems (one medium-sized canned specialties plant
and one medium-size canning plant). Since it is anticipated
that NSPS guidelines would constitute a deterrent to new plant'
construction.
7. Production Losses
Estimated production losses due to projected closures are shown for BPT
level closures, BAT closures incremental over BPT and for BPT plus BAT.
Table VII-28 shows production losses assuming effluent control require-
ments can be met by aerated lagoons and Table VII-29 shows losses if
activated sludge systems are employed. All losses are shown in terms
of tons of raw product processed.
In general, since most closures are in the extra-small and small plant
sizes, the production impact as related to total industry production
is also relatively small. As shown in Table VII-28, for the total
industry, annual production losses, assuming aerated lagoon treatment
systems, totaled approximately 47,500 tons, raw product basis for BPT
and for incremental BAT an additional 10,000 tons for a total loss in
production BPT + BAT of 57,500 tons raw product. However, in relation to
total industry volume, this represented a loss of only 0.19 percent.
If activated sludge systems were used, (Table VII-29), industry shutdowns
would be more numerous (because of the higher cost of these systems) and
production losses would be correspondingly greater. Under BPT with
activated sludge systems, production losses would approximate 25,000
tons and incremental BAT losses would be 60,000 tons for a total loss in
production of 85,000 tons equal to 0.3 percent of total industry processing
volume.
VII-57
-------
fable VII-28. Production lost due no slant closures, industry groups, aerated lagoon systems
—
S'~
L. •- * — ' C—
2053
2035
2037
2C34
10392
, , _ - --.,___
Industry Group
- Canned Specialties
- Canned fruits and vegetaoles
- pick";es, dressings and .sauces
- Frozen fruits and vegetables
- Dehydrated fruits, vegetables and
soup mixes
- Food preparations - chips
Pri
BPT
0
5.5
16.0
26.0
0
0
jc-jc L ' or. \ ost - t
incr. 3AT
0
0
0
10.0
0
0
"a// ions
(>'-•- i n r. -*-
u\J i. -r Drt i
-} __' _
3 ;
0
. 5.5 '
'16.0
36.0
0
0
,> or
BPT
/ :" }
( "I
• 0
0.04
0.40
0.80
0
0
tctal crccuc:
Incr. 3r. i
( c ]
\"i
0
0
0
0.30
0
0
' '- 1 1 ~J -' ^
E?T -r 5 AT
, - \
0
.04
.40
1.10
0
0
Total Industry
47.5
10.0
57.5
0.16
0.03
0.19
03
-------
Table VII-29. Production lost due to plant closures, i-ncfustry groups, activated sludge systems
en
UD
SIC
2032
2033
2035
2037
2034
1C992
Industry Group
- Canned Specialties
- Canned fruits and
- Pickles, dressings
- Frozen fruits and
- Dehydrated fruits,
soup nixes
- Food preparations
Total Tndn?tt*v
vegetables
and- sauces
vegetables
vegetables and
- chips
3Pi
7.0
10.0
0
8.0
0
-0
25.0
p i~/-i H ; p "!~ ~i *Tt ; [™i C "f
r J ^ i^ j **. '„ I w > - i o o l
T r> r y* Rii '
(000
40.0
20.0
0
0
0
0
60.0
; -. raw tons
S?T +
tons)
47.
30.
0
8.
0
0
85.
BAT
0
0
0
0
% of
B?T
( !&)
0.25
0.07
0
6.25
0
0
0.09
to-;l rrc-i
Incr. EA>T
('/;)
1.42
0.13
0
0
D
0
0.21
;c"icn lost
Dr'l - O-vl
t'/;)
1.67
0.20
0
0.25
0
0.30
-------
D. Employment Effects
1. Employment Trends
Total employment in the canned, frozen and preserved fruits and vegetables
industry rose gradually from 1958 through 1967 and declined slightly to 1972.
Table VI1-30 shows employment by SIC Code for those industries covered by
this study. The data exclude employment in apple and citrus processing
industries, not included in this study.
Employment in all industry groups except canned fruits and vegetables in-
creased during the 1958-1972 period. Frozen fruits and vegetables and food
preparations -- chips showed the greatest relative and absolute gains in-
employment. Canned specialties and dehydrated fruits and vegetables had
moderate increases and employment in the pickles, dressings and sauces in-
dustry remained relatively steady.
2. Employment - Sales Relationship, by Plant Size
There are significant differences between employment and sales relation-
ships among different sizes of plants in the fruit and vegetable processing
industry (Table VII-31). Ten percent of the total number of plants fall in-
to the extra large category and account for 39 percent of the total industry
employment and 49 percent of sales. At the opposite extreme, 45 percent of
the total number of plants are classified as extra small and account for
only 7 percent of total employment and 4 percent of total sales. These
extra-small plants averaged only 13 employees per plant vs. 345 for the
extra-large category. Sales per employee also varied significantly, from
a low of $24,800 per employee for the extra small plants to a high of
$59,000 per employee for the extra large plants.
3. Employment and Payroll Impacts
The closure of fruit and vegetable processing plants, due to effluent con-
trol requirements, will result in a net decrease in employment and pay-
rolls in this industry. Although there will be some new jobs created as
remaining plants expand, the greater efficiency of larger plants, as
illustrated by Table VII-31, in terms of sales per employee will mean that
the reemployment rate would be less than 50 percent of the jobs lost by
plant closures. In addition, due to the lack of mobility of this type of
labor, these job losses would be localized and would have more severe
impacts on local communities where reemployment opportunities would be
limited (see Section D-4 and E of this report).
VII-60
-------
Table VII-30. Employment in the canned, frozen and preserved fruit and
vegetable processing industry (excluding citrus and apples)
1958-1972 I/
SIC
Code
2032
2033
2034
2035
2037
20992
Total
Total employment (000)
Industry group
Canned specialties
Canned fruits & vegetables
Dehydrated fruits & vegetables
Pickles, dressings & sauces
Frozen fruits & vegetables
Food preparations - chips
1972
29.1
83.0
11.2
20.8
17.0
27.2
188.3
1967
27.2
94.4
10.4
19.8
14.7
25.2
191.7
1963
25.2
96.6
8.6
19.0
13.0
24.0
186.4
1958
24.2
102.2
7.2
19.5
10.4
17.6
181.1
\J Source: Census of Manufactures, U.S. Department of Commerce.
VII-61
-------
Table VII-31 . Employment-sales relationships, fruit and vegetable processing industry,
by size of plant
cr>
no
Plant size
Extra-small
Small
Medium
Large
Extra large
Number
Number
990
497
297
204
214
of plants
% of total
(%)
45
23
13
9
10
Employees
per plant
13
49
117
206
345
Employment
% of industry
total employment
(%)
7
13
19
22
39
Value
Sales per
employee
($000)
24,800
32,900
40,200
48,900
59,000
of sales
% of industry
total sales
(%)
4
9
16
22
49
-------
a. Jobs and Payrolls Lost - As was indicated in the Production Effects
Section (Section c), the impact of proposed effluent controls was calcu-
lated for two alternative treatment systems, aerated lagoons--the low-cost
system and activated sludge--the high cost system. As a result, the job
and payroll impacts differ, being less severe if the aerated lagoon system
is used vs. the impact where activated soudge is employed. The employment
and payroll impacts by industry group, are shown in Tables VI I -32 and
VII-33. In summary, the results for the entire industry are:
System Treatment level Jobs lost Payrolls lost-
- - - -'
Aerated lagoon BPT 996 $ 7,728
BAT incremental 1,112 8,647
BPT + BAT 2,108 16,375
Activated sludge BPT 3,022 23,171
BAT incremental 5,463 42,767
BPT + BAT 8,488 65,948
— Based on 1974 wage rates.
4. Possibility of Reemployment in New or Surviving Plants
There would be little likelihood that new plants would be built in the same
area to replace small or obsolete plants which closed. Small fruit and
vegetable processors face disadvantages due to economies of scale in both
processing and waste treatment. As a result, it is doubtful that these
plants would be replaced. As was indicated earlier, although there is
"reserve or surge" capacity in the fruit and vegetable processing industry,
there is little "excess" capacity. It is presumed that capacity lost throuc
closing small plants would be regained by expanding surviving plants. Whilf
such expansion would create additional employment opportunities, it is not
expected that this would offer realistic opportunities to those who have
lost their jobs due to plant closures. Due to the fact that many jobs in
the fruit and vegetable processing industry are part-time or seasonal and
demand relatively unskilled labor, this type of labor is not highly mobile.
VII-63
-------
Table VII-32. Employment losses due to plant closures, industry groups, aerated lagoon systems
<;--
2 03
2C3
202
203
2?3
ir~
. — . — . —
Industry Group
2 - Canned Specialties
3 - Canned fruits and vegetables
5 - Pickles, dressings and sauces
7 - Frozen fruits and vegetables
4 _ Dehydrated fruits, vegetables and
soup nixes
52 - Food preoarations - chips
Total
— — — -
BPT
0
117
/ 234
196
0
0'
547
Jobs lo
Incr. BAF
(000
0
0
0
49
0
0
49
>st
BPT + BAT
tons)
0
117
234
245
0
0
596
BPT
($000)
0
908
1,816
1,521
0
0
$4,245
Payrolls lost
Incr. BAT
($000)
0
0
0
380
0
0
380
V
BPi + BAl
($000)
0
908
1,816
1,901
0
0
$4,625
I/
Based on 1974 wage rates.
I
cr>
-------
Table VII-33. Employment losses due to plant closures, industry groups, activated sludge systems
SIC
2032 -
2033 -
2035 -
2037 -
2034 -
10992 -
Industry Group
Canned Specialties
Canned fruits and
Pickles, dressings
Frozen fruits and
Dehydrated fruits,
soup mixes
Food preparations
Total
vegetables
and sauces
_
vegetables
vegetables and
- chips
BPT
49
117
• o
49
0
0
215
Jobs lost
Incr. BAT
_ ( nnn to
117
117
0
0
0
0 -
234
BPT +. BAT
nc^
nb )
166
234
0
49
0
0
449
BPT
f snnn }
380
908
0
380
0
0
1,668
Payrolls lost
Incr. BAT
( soorn
908
908
0
0
0
0
1,816
I/
BPT + BAT
f iPGO )
1,288
1,816
0
380
0
0
3,484
— Based on 1974 wage rates.
cr>
en
-------
E. Community Impacts
Fruit and vegetable processing plants are located throughout the United
States and, except for dehydrators which are concentrated in the West,
these plants are distributed relatively uniformily throughout all major
Census regions. A relatively high percentage (above two-thirds) are
located in or near small towns of less than 5,000 population. In these
situations, the closure of a processing plant can have a major economic
impact on the local community and on farmers in the surrounding area.
A study made by Development Planning and Research Associates, Inc. in 1973
explored the local economic and employment impacts of fruit and vegetable
processing plant closures resulting from increased water pollution abate-
ment standards I/. The results of this study are indicative of the types
of community impacts which may be associated with fruit and vegetable
processing plant closures.
Community and area economic impacts resulting from processing plant
closures will depend not only on the number of plant closures and directly
associated unemployment within a given community or area, but also on
other factors sjjch as area economic base, prevailing economic conditions,
area economic dependency on the fruit and vegetable processing industry
and other economic characteristics of the area. The most severe community
impacts may not occur in those communities with the most olant closures,
but will be related also to the size of the community, the economic base
and alternative employment opportunities for employees of the closed
plant. For example, a small community which had established a fruit and
vegetable processing plant through the issuance of municipal revenue bonds,
would be hard hit if that plant were to close. Repayment of the bonded
obligations would become difficult, reemployment opportunities for workers
would be small and the cancellation of production contracts with farmers
in the surrounding area would reduce agricultural incomes important to the
local economy. In addition, in these situations, capital availability to
finance construction of effluent control systems will present more difficult
problems.
All areas have small plants; however, the greatest relative concentrations
of small plants are found in New England, the-Atlantic Coast, the South
Central and the Intermountain States (Figures VII-1 and VII-2). It is
these same areas where farm incomes are lowest, unemployment and under-
employment is greatest and alternative employment opportunities may be
lacking. Included in these regions are many of the economically "depressed"
areas in the United States. A further fact which aggravates the local
II Local Economic and Employment Impacts of Fruit and Vegetable Processing
Plant Closures Resulting from Increased Water Pollution Abatement
Standards, DPRA Report No. P-106, April, 1973, Economic Development
Administration, U.S. Department of Commerce Contract 2-36744.
VII-66
-------
Figure VII-1.
Major regions with above U.S. average percentage of "small"
canning and freezing plants, (plus other states with
more than 5 "small" plants and above average percentage
of small plants),. 1970.
Figure VII-2. States with above U.S. average percentage of "small"
canning and freezing plants, 1970.
VII-67
-------
community impacts of plant closures is that most of the jobs in the fruit
and vegetable processing industry require relatively unskilled and part time
employees. For these types of workers, job mobility is low and alternative
employment opportunities are scarce. Since these people will tend to
remain in the local community, the multiplier effects are real and result
in a reduction of the economic base and, equally serious, increase in the
number of people on welfare.
Information developed by the National Canners Association in 1973 pertaining
to some 400+ small fruit and vegetable canning plants, resulted in the
following "profile" for such plants:
a. Employees -- 63 full-time, 72 part-time
b. Local payrolls -- $700,000 annually
c. Farmer-growers affected - 33
d. Community income generated — $1.4 to 2.1 million
e. 50 percent of such plants in or near towns of less than 2,500
population
f. 75 percent of such plants in or near towns of less than 5,000
population.
As illustrated by these data, the loss of such a plant would have a
major impact on these small communities.
£. Bal_ance- o f-Payment s I mpa c ts
It is not anticipated that the imposition of effluent guidelines on the
fruit and vegetable processing industry would have a significant impact
on exports of U.S. processed fruits and vegetables included in this study.
Small processors, who would be most highly impacted, are not an important
factor in the export trade. The principal exports included are canned
peaches, fruit cocktail, pineapple and tomato products, most of which are
packed by large packers located mainly in California (except pineapple).
The impact on the export of thes-e products is expected to be relatively
smal1.
However, the imposition of effluent guidelines could serve to stimulate
the impact of such products as mushrooms, strawberries, blueberries and
tomato paste, where imports already constitute an important part of the
total supply. This conclusion is reinforced by the fact that both the
canned mushroom and frozen strawberry - cane berry seaments of the pro-
cessing industry are heavily impacted. Plants in these two segments tend
to be small and established sources of impacts exist. In 1972, imports of
canned mushrooms (mainly from Taiwan) were equivalent to 28.7 percent of
the U.S. pack.
Certain U.S. canners are currently swinging strongly toward Taiwan as
their major source of canned mushrooms and if satisfactory trade relation-
ships are established with the People's Republic of China, this country
would represent; a major additional source of canned mushrooms. The U.S.
mushroom cannor already is experiencing less-than-satisfactory returns and
VII-68
-------
increased competition from foreign, low-cost sources could represent a
severe blow to the U.S. industry. In 1974, the declared value of mushroom
imports was $60 million, up 38 percent from 1973 which was the highest
previous level of imports.
In the same year (1972), imports of frozen strawberries (from Mexico) were
equal to 50.6 percent of the U.S. pack and frozen blueberry imports (from
Canada) were equal to 32.8 percent of the U.S. pack. Since 1972, imports
of frozen strawberries from Mexico have risen from 85.2 million pounds to
117.1 million pounds, a gain of 37 percent. Although there has not been a
comparable increase in imports of tomato products (mainly bulk paste), due
in part to light packs in Mediterranean countries, imports of tomato paste
and tomatoes total over 250 million pounds and U.S. tomato processors are
apprehensive that imports of paste may increase substantially if U.S.
processing costs are increased as a result of pollution control costs.
It appears probable that certain segments of the fruit and vegetable
processing industry, particularly canned mushrooms and frozen strawberries,
may be faced by increased imports as their costs rise due to pollution con-
trol requirements. Both of these industries currently are at the lower
end of the profitability scale, imports of both of these commodities are
increasing rapidly and large and established, low-cost foreign production
exists and can be increased. Under these conditions, any further U.S. cost
disadvantage would tend to encourage imports. The tomato situation is
somewhat different. We are both a substantial importer and an exporter of
tomato products. Much of our imports comes in as bulk paste, from Italy,
Spain and Portugal -- relatively low-cost producing areas. Any further
cost disadvantage experience by U.S. producers as a result of effluent
control requirements would tend to encourage increased imports of tomato
paste.
VII-69
-------
VIII. LIMITS OF THE ANALYSIS
A. General Accuracy
The data and other information used in this study were drawn from
published governmental reports, industry trade associations and from ex-
tensive contacts with individual fruit and vegetable processing firms.
Information on status of effluent controls in place in the industry,
recommended effluent treatment systems and costs were furnished by EPA.
Every effort was made to verify the data and other information used.
The data and analyses were reviewed by EPA and by specially-constituted
committees of the major related trade associations (see page 1-4) and
comments of both groups were considered in finalizing the analysis.
Financial information on the fruit and vegetable processing industry is
not available in published form, particularly for individual plants or
firms. Although directories of both canning and freezing plants exist,
no data for individual planes are available on volume of pack of specific
products. It v.-.s necessary to develop basic data on financial character-
istics of plants, on product mix and volume of pack and other related in-
formation, by direct contacts in this industry. Seven industry trade
associations (see page 1-4} cooperated in this effort by surveying their
members in an attempt to develop information required for the analysis.
Returns from this survey were received from 17+ percent of all firms in-
cluded in these associations. More than 330 responses were received.
Fruit and vegetable processors generally process a mix of products and
product forms. The processing and product comb:nnLions vary to the point
where each p"i&nt could almost be considered unique. There is also a sub-
stantial range in plant sizes which also vary by commodity and the com-
binations of products processed. Virtually no published information is
available on this structure of plants by size and by products processed.
As a result, it was again necessary to develop most of this information
from industry sources and from detailed analyses of privately-published
industry directories.
The complex nature of this industry makes generalization difficult. How-
ever, the same complexity and the lack of detailed data made it necessary
to develop "representative" plants (or model plants) which could be
analyzed in sufficient detail to permit an evaluation of the economic im-
pacts of proposed effluent guidelines on this industry. It should be em-
phasized that these plants were designed to be "representative" of major
plant configurations which exist in the industry and were selected to pro-
vide a cross-section of commodities, combinations, processes and plant
VIII-1
-------
sizes which realistically exist in the industry. They are not statistical
"averages'1 or representations from which precise extrapolations can be made.
A total of 15 basic model plants of various sizes, representing 21 com-
modities were synthesized to form a total of 53 detailed, representative
plant models to provide a base for analyses of the complex of plant types
and sizes which comprise this industry. The most feasible method for
segmenting this complex industry for the purpose of generalizing from
specific model plants, was by processing function, e.g. blanch, pit, peel,
brine, reprocess and nonbasic processors. The most prevalent industry
plant types (canning, freezing and dehydrating) and commodities per plant
(single and multiple) are represented by the models. It is recognized that
this segmentation procedure constitutes a limiting assumption; but, it is
believed that it does permit a consideration of these plant types in more
detail than would be possible by extrapolating from industry averages.
However, the lack of detailed data on all types and sizes of plants and
the complexity of this industry do limit the reliability of this study.
In general, it must be recognized that there are severe limitations in the
availability and detail of information required For the analysis on a corn-
modi ty-by-coinmodity basis. Published data, at the individual commodity
level, do not exist for individual or "representative" plants in terms of
financial characteristics and volume end type of pack. The use of aggregate
data do not permit the necessary detail of analysis. However, it is believed
that the data developed by this project are representative "A the situation
which actually exists in the fruit and vegetable processing industry and
permit a more realistic analysis that would be possible through the use of
published aggregate data.
Specifications of the contract require: the Contractor to use effluent con-
trol costs provided by FPA. The Effluent Guidelines Division, EPA, to-
gether with its technical contractor., provided proposed effluent control
systems, investment costs and annual operating costL ddcptcd to the types
and sizes of "representative" model plants used in this analysis. Costs
for three systems, aerated lagoons, spray irrigation and activated sludge,
were provided. In addition, the Effluent Guidelines Division provided
estimates of the percentage of plants in the industry which were "direct
dischargers" and within this group, estimates were provided of the degree
to which these plants had effluent control systems in place. The estimates
of percentage of direct dischargers were made by EPA for each of the
/'representative" model plants specified. However, the estimates of the
degree to which plants (all plant types and sizes) had effluent controls in
place (zero, minimum, moderate and acceptable) were not available except
on an industry-wide basis, The estimates for incremental investment and
operating costs for those plants with in-place controls were also fur-
nished by EPA.
VIII-2
-------
B. Possible Range of Error
Estimated ranges of error for data used in this analysis are as follows:
Error range (%)
1. Number and type of plants +_ 5
2. Distribution of plants by size " +_ 10
3. Price data for products and raw
materials .+_ 5
4. Sunk investment costs +_ 15
5. Plant operating costs j^ 15
6. Effluent control costs -f 10
7. Expected price changes +_ 5
8. Estimated plant closures +_ 15
C. Critical Assumptions
In an analysis of an industry as complex as the fruit and vegetable cannin-
freezing and preserving industry, it is inevitable that simplifying as^'tnp
tions must be made to bring the problem into a framework of analysis con-
sistent with the constraints of time, budget and data availability. The
major critical assumptions used in this analysis are as follows:
1. Types and sizes of "representative" plants are realistic
in terms of plants actually existing in the industry.
2. Size distribution, in terms of number of plants in each
size group, as used in the analysis was based primarily
on results of the surveys by industry trade associations
together with data on concentration ratios from the Bureau
of the Census to reduce the survey bias toward larger plants.
3. The product mix used for multi-product plants is typical
of plants in the industry and was based primarily on trade
association survey results and industry sources.
VIII-3
-------
4. Financial data were developed primarily from returns
from surveys of firms conducted for this project by
industry trade associations. It is assumed that these
data are representative of costs and returns existing in
the industry and that they represent actual rates of
utilization of plant and equipment.
5. Levels of profitability of plants, as used in the financial
analysis of canning and freezing, were based on 80 percent
of 1973 profitability. This assumption reflects historical
profitability data as reported by the analysis done for the
National Canners Association by the Touche-Ross accounting
firm. Profitability levels of all canning and freezing
plants were adjusted to conform to this general profitabi.l ity
relationship. This adjustment recognizes the fact that 1973
was, for the canning and freezing industry, a year of better-
than-average profitability. Examination of historical re-
turns data supports the 80 percent adjustment factor.
6. It was assumed that the economic impacts of effluent controls
on those commodities not included in the detailed analysis
of "representative" plants could be evaluated in general
terms through associating them with those "representative"
or model plants for which detailed analyses were made.
This association was based primarily on unit processes,
that is the types of processes involved (blanching, peeling,
pitting, etc.) in the production of the canned, frozen or
preserved products. It is recognized that this is a limiting
assumption, but the complexity of this industry and the very
large number of products and product combinations made such
generalization necessary. This assumption is especially
critical in the case of "specialty" foods since most of
these are reprocessors and start with partially processed
products (e.g. puree, paste, etc.) and often combine these
fruit or vegetable products with starches, cheese, sugars
and other materials.
7. In deriving "baseline" numbers of plants for 1977 and 1983,
it was assumed that trends in plant numbers, by 4-digit SIC
codes, as indicated by the Census of Manufactures, would
continue and that, with the exception of potato chips, the
principal decreases in plant numbers would be in the small
and extra-small plant size categories. Concentration ratios
showing size groups were not available beyond 1967, but were
applied to 1972 total plant numbers.
8. It was assumed that numbers of employees, by plant type and
size, would be consistent with employment, data shown by the
Census of Manufactures, by 4-digit SIC codes. Since data
from the 1972 Census were not yet available, it was necessary
to base this employment on data reported for the 1967 Census
adjusted to the total number of employees, shown in 1972. It
is recognized that these data are old, but they represent the
only data on this factor available at this time.
VIII-4
-------
9. Effluent control costs and control status estimates were
supplied by the Effluent Guidelines Division, EPA. It is
assumed that these data are realistic in terms of:
a. Applicability of effluent treatment systems
recommended.
b. Investment and annual operating costs for
systems.
c. Percentage of total number of plants which are
direct dischargers for each industry segment
and for the industry in general.
d. Percentage of direct dischargers having specified
(zero, minimum, moderate, acceptable) effluent
treatment systems in place. This estimate was
only given for the total industry and without fur-
ther breakdown by plant type or size, variations
among plant types and sizes undoubtedly exist.
e. The incremental costs which would be incurred by
plants having minimum (85 percent of costs) and
moderate (50 percent of costs) treatment systems
in place, are representative of actual incremental
costs which will be encountered.
D. Remaining Questions
A major Question, not addressed by this stut,y, is concerned with the
economic impact of effluent guidelines on those fruit and vegetable
canning, freezing and preserving plants discharging through municipal
waste treatment systems, in total or in part. It was estimated, by
EPA Effluent Guidelines, that 55 percent of the plants in this industry
are discharging through municipal systems. The remaining 30 percent are
"zero discharge" plants utilizing spray irrigation or gravity flow irri-
gation systems. It is known that for some segments, e.g. canned soups,
the importance of municipal systems is near 100 percent. Much the same
situation appears to exist for most other specialty food processors.
Municipal sewage charges and other costs related to such sewage services
are reported to be rising rapidly. The economic impacts of these in-
creasing sewage charges on connected fruit and vegetable processing
plants has not been determined. Such determination is needed to com-
plete the evaluation of proposed effluent controls on the fruit and
vegetable canning, freezing and preserving industry.
VIII-5
-------
2. The use of the model plant approach necessarily raises questions
as to the "representativeness" of the model plants used and in par-
ticular, the process of generalizing "by association" from the spe-
cific model plants analyzed to plants processing other commodities
or combinations of commodities. The complexity of the fruit and
vegetable canning, freezing and preserving industry, including a
wide variety of specialty food processors, together with limitations
on time and budget for this study, made detailed analyses of all
industry segments impracticable.
3. Another fundamental question which remains unanswered stems from the
fact that this analysis was concerned only with the impacts of proposed
effluent guidelines. It is recognized that there are other regulatory
EPA programs in air and noise control, pesticide regulatory programs,
OSHA, FDA, energy controls, inflation, consumer protection and various
State controls, either existing or emerging which will influence the
operations and profitability of plants studied. The analysis does not
consider the full impact of this aggregate of regulations, particularly
as they may affect the future of the fruit and vegetable industry.
Although it is impossible to quantify the aggregate impacts of all
these regulatory programs, it is evident that the combination of pro-
grams imposes additional burdens on management in keeping up with
regulations, filing reports, replying to surveys and other similar
administrative requirements, constitutes a significant degression from
the major function of these firms -- processing food for human con-
sumption.
VIII-6
-------
APPENDIX A
Industry Questionnaire
-------
Return By
October 14, 1974
To: American Frozen Food Institute
c/o Touche Ross & Co.
1776K Street NW
Washington D.C. 20006
Environmental
Economics
urvey
bythe AMERICAN FROZEN FOOD INSTITUTE
St.*«fiJli3HtallkAdii4^BBi guidelines for the food processing industry pursuant to the Federal Water Pollu-
tion Control Act Amendments of 1972 (Sections 304(b) and 306 of the Act). One of the factors required to be
considered by EPA in setting these guidelines is the economic impact which would result. Because these con-
trols will have substantial effects on the food industry, it is in the interest of food processing companies that the
economic analysis of the impact of proposed controls be based on accurate, up-to-date data which can be
obtained only from company records.
PROCEDURES
The completed survey forms will be analyzed by an independent
research organization, Development Planning and Research Associ-
ates, Inc. (DPRA), under contract to EPA. The tabulated and analyzed data will be presented to
EPA and the American Frozen Food Institute (AFFI) in summarized form so that individual plant
data will not be disclosed but the current economic picture of the industry will emerge.
The survey form should be filled out and returnee
without identifying the company or plant involved
In replying to the -survey, the Company does so on the express condition that the indi
vidual company and plant data supplied herein will remain confidential and will be
used solely for the purpose of determining the economic impact of proposed wates
pollution controls on the industry.
CONFIDENTIALITY
INSTRUCTIONS: Complete a survey form FOR EACH PLANT. Respond to all questions if possible. Where specific accounting figures do
not seem to fit or if allocations of costs are on a different basis, make your own estimates. Estimates by you are far better than estimates by
outsiders. For specific questions you may have, call:
FRANCIS G. WILLIAMS - Phone 202/296-4080
American Frozen Food Institute
NOTE - Regardless of the nuirber uf qvi'-"ons von are able to answer, please return the questionnaire.
o
PLANT DESCRIPTION - 1973
A. Location: Please check the box for the region in which this plant is located (DO NOT MARK THE STATE)
D North Atlantic ME, NH, VT, MA, Rl, CT, NY, PA, NJ
D South Atlantic WV, VA, MD, DE, NC, SC, GA, FL
D North Central ND, SD, NB, KS, MN, I A, MO, Wl, IL, IN, OH, Ml
DSouth Central NM, OK, TX, AR, LA, KY, TN, MS, AL
G Nolhwest WA, OR, ID, NV. M T, WY, UT, CO, AK
[H Southwest AZ, CA, HI,
B. Size: Total Tons Raw Product Processed at this Plant in 1 973
C. Type: nCanningonly L3 Freezing only D Canning and Freezing D Drying, Dehydrating, Freeze-Drying OOther
D. Ownership: Company owning this Plant: ClOperates I Plant only DOperates more than 1 Plant
E. Seasonality: During which months is this plant in operation for first-processing* of major commodities:
(mon ths)
During which months is this plant in operation to perform other processing activities, e.g., repacking, which partially contributes
to sales in the off-season:
(months)
Approximately vvhat percent of the total sales generated from this plant is attributable to off-season activities: .
(percent)
' inithil processing of raw products a^ contrasted \<,ith repai.k or combination blends of pre-processed components.
-------
1 !
2
3
4
PRODUCTION BY COMMODITY - 1973
a. *Mame of commodity packed
Major stvle
b "Tons of raw product processed
c. *Maximum rated capacity raw
product tons per hour _ _ ___ __ _
d. Hours of operation in 1973 _ __ __ _
e. Range of hours of operation
in last five years _ _ __ _
f. Percent of finished product:
Canned _ _ __ _
Frozen _ _ __ _
Dried _ _ _ __ __
g. Percent of pack in:
June _ _ __ _
July _ _ __ _
August _ _ __ _
September _ _ ___ _ _
October _ _ __ _
November - May _ _ _ _ _ _
h. Volume of finished product in
24/303 cases, pounds or other units _ _ __ __
Specify units _ _ __ _
i. VVastewater generated per ton
of raw product processed
Process - gal. /ton _ _ __ _
Cooling - gal ./ton _ _ __ _
"For items a, b and c, report first-processing of raw products only. If more than one style is major, show each style as a major commodity i:
PROFITABI LITY — 1973 and RANGES* Please calculate as accurately as possible your profit (or loss) as a percent of
other commodities, and for your plant as a whole for 1973. Also, indicate yout high and low profit ranges as
between 1969 and 1973. Use the following formula for calculation:/ profjt before tax ($) \
V Sale7($) ) 10° = Percent Profit <
1973 _ _ __ _
Other:
High _ __ _ __ _
Year _ _ __ _
Low _ _ _ __ _
Year _ _ __
"Coirplete first line for all items in 1973. Indicate high and low ranges for 1969— 1973 period, by commodity only. For example, Tomatot
High. 6.4%, 1972; and low: (-1.396), 1969.
OPTIONAL QUESTIONS - ANSWERS TO QUESTIONS 4 AND 5 ARE DESIRED FOR IN-DEPTH ANAL
SALES - 1973 3 WAS ANSWERED
Annual sales by commodity,
F. O. B. factory prices _ _ __ _
COSTS — 1973 Show 1973 commodity costs broken down into variable and fixed expenses as shown below. If indirect or fixed expens
factory totals (far right column). Expenses shown should include effluent treatment costs.
Direct or Variable Expenses
- Raw product
- Direct labor
- Other direct ,
— Total direct
Indirect or Fixed Expense
— Depreciation
— Interest
- All other factory indirect
or overhead
— Allocated general overhead,
mciuding selling and ad-
ministrative - ,
-------
All Others
Plant Total
(ave.)
(ave.)
our major commodities, all
of sales for each major commodity
T6 profit.
T OPTIONAL IF QUESTION
allocated by commodity, show
PLANT INVESTMENT - 1973
Plant Total
A. Book value of fixed assets at this location:
Land
Buildings
Equipment
Other
B. Estimate current replacement value of all fixed assets
C. Annual depreciation __
D. What was the average annual amount of capital investment
(Exclude major plant expansions) for this plant during the
past 5 years ___
EFFLUENT CHARACTERISTICS
AND DISCHARGE DATA - 1973
A. Most plants have several types of liquid waste discharges. What is the final disposition
of wastewaters from this plant?
Wastewater Type Land Municipal Discharge to Total
Disposal System Watercourse
Process
Cooling
Sanitary
* 100%
= 100%
= 100%
For your process and cooling wastewaters, check the types of on-site treatment, if any,
that are performed prior to final discharge from the plant site:
Type of Treatment
Screening
Lagoon
Aerated lagoon
Activated sludge
Trickling filter
Chemical precipitation
Other (specify):
Process
Wastewater
D
D
D
D
D
D
D
D
Cooling
Wastewater
D
D
D
n
D
n
n
n
B. In terms of pounds per ton of raw products processed, what is the average daily 6005
and TSS content of the untreated process wastewater and the final plant discharge
(effluent) during the peak processing season*
BOD5
TSS
Before on-site treatment
After on-site treatment
TSS
- Biological oxygen demand - 5 days
= Total suspended solids
C. Land availability at this location
1. Total land owned or leased
(acres)
Market Value
($/acre)
1. Of the above acreage:
• Amount now used for waste treatment
• Additional amount available for such use
3. Additional land "available" for water treatment
within about a 1-mile radius of plant site
Market Value or Cost
(acres)
(acres)
(acres)
($/acre)
-------
OTHER REGULATORY IMPACTS AND COSTS
Feaerai, state or local regulations already established or under development may have an economic impact on this plant's operation.
Identify to the extent possible the nature of these additional regulations and anticipated costs of compliance.
A State or local water quality regulations. From 1 973 to 1 977 (projected) are there either state or local water effluent regulations which will affect
operating costs of this plant? DlMo D Yes If yes, explain (include BOD$ and TSS guidelines if possible.)
Est.rr.ate total combined investment and operating costs for next 5 years: Investment requirement
Annual operating cost
(projected)
(projected)
B. Other related cost impacts: Describe other environmental controls (e.g. air, odoi, thermal, solid waste) or other factors (e.g. OSHA, FDA, etc)
which have resulted in significant cost impacts.
Estimate total combined m\estment and operating costs for next 5 years: Investment requirement
Annual operating cost
C. For plants on munic'pal svstems:
1. What are \ our use" charges' Last year
Current vear
Pioiected*
(1973 season)
(1974 season)
(1977 season)
(projected)
(projected)
"i incliidts pa'y back requirements)
2. Docs the r^unicioa! featment facility that this plant discharges into currently meet EPA's secondary treatment requirements?
U \ es Ljno. If no, when is upgrading of this municipal facility expected?
(year)
COMMENTS
Please supply any other data or comments that you feel may be helpful in evaluating the
economic impact of possible effluent limitation guidelines on food processing plants.
(Attach additional sheets if necessary)
-------
APPENDIX B
Supplemental Tables
-------
KEY VALUES OF IMPACT ANALYSIS:
REQUIRED PRICE INCREASE, AFTER TAX INCOM,F, RETURN ON SALES C INVESTED CAPITAL, CASH FLOW, AND PRESENT VALUES
UNDER VARIOUS IMPCSITICN OF BPT AND HAT CONTROL LEVELS
FOR CO^N CANNING PLANTS — 1973
1.
2.
3 .
4.
5.
6.
PDICE INCREASE
REQUIRED
AFT-R 'AX INCOME
a'TcR TAX = "iJRN TS
SALE?
AFTER TAX RF'URN ON
INVESTED CAPITAL
EST. CASH FLPH GN I N-
v-lSTHO CAPITAL (41000)
NET PFESE.VT VALUES
! $1000)
5500
18000
5500
13000
5500
13000
5500
13000
5500
IB 000
5iOO
13000
BASE
8
29
LI?
1.2
1.8%
2.5
85
66
122
NCNE IN
RRT
3.9%
2.2
-11
1
-1.5?
0.0
-2.2%
0.1
21
74
-71
-124
PLACE
RAT
5.5%
3.0
-24
-24
-3.33
-1.0
-4.5%
-I . 7
13
61
-129
-214
15? IN
RPT
3.2%
1.9
-8
6
-i.oi
0.3
0.5
23
77
-48
-87
PLACE
4.6%
2.5
-19
-13
-2.6%
-C.6
-3.7%
-1.0
16
67.
-97
-164
50% IN
1.7*
1.1
0
18
-0.0%
0.7
-0.1%
1.4
27
82
5
-1
PLACE
2.5%
1.5
-7
8
-0.9%
0.3
-1.4%
0.6
23
73
-23
-46
NONE If
12.8%
5.4
-59
-73
-8.0%
-3.1
-4.6
-4
39
-443
>J PLACE
13.8%
6.0
-73
-98
-9.8%
-4.1
-10.3%
-5.9
-12
25
-510
-650
15% IN
PPT
4.4
-49
-56
-6.6%
-2.3
-7.7%
-3. 7
2
48
-353
— '-37
PLACE
12.0^
5.2
-60
-77
-8.1%
-3.2
-9.0%
-4.8
-5
37
-411
-519
50% IN
RPT
4.9%
2.9
-25
-15
-3.3%
-0.6
-4.4%
-1.1
15
69
-165
-207
PLACE
5.7?
3.3
-31
-27
-4.2%
-1.1
-5.5%
-1.9
11
63
-194
-252
-------
KEY VALUES OF IMPACT ANALYSIS:
REQUIRED PRICE INCPEASF, AFTER TAX INCOME, RETURN CfJ SALES t INVESTED CAPITAL, CASH FLOW, AND PRESENT VALUES
UNDER VARIOUS IMPOSITION OF B"T AND BAT CONTROL LEVELS
FOR MUSHROOM CANNING PLANTS — 1973
PRICE INCREASE
REQUI&CP
2- AFTER TAX I
(S1000)
A-TER TAX PETURN QN
SALES
AFTER TAX PETURN ON
INVESTED CAPITAL
EST. CAS!1 FLOW ON IN-
VESTED CAPITAL (11000)
6. NET PRESENT VALUES
{
[£MS_
200
1 500
2rOO
5 COO
200
IbOO
2500
5000
200
1 500
2500
5CCC
200
1500
2500
5000
200
1 500
2500
5000
200
15CC
2 500
50 30
BASE
£AS.E_
2
21
34
64
0.7?
1.0
• 1.0
0.9
0. 3?
0.6
0.6
0. 7
44
264
428
607
152
709
1156
1267
NONE II
*£!_
7.9%
1.3
' 0.9
0.5
- 17
3
20
48
-6.1?
0.2
0.6
0.7
-2.7?
0.1
0.4
0.5
30
252
420
599
48
585
1016
1101
M PLACE
12.4?
1.8
1.2
0.7
-33
-15
3
34
-12.07;
. -0.7
0.1
0.5
-5.3?
-0.4
0. 1
0.4
15
237
408
5 SI
-11
530
954
10<"2
15? If
BP.T
6.7%
1.1
0.7
0.4
-14
6
22
51
-5.0J
0.3
0.6
0. 7
-2.3?
0.2
0.4
0.5
' 32
254
421
600
63
6 1) 3
1037
1126
>J PLACE
10.3?
1.5
1.0
0.6
-28
-9
9
39
-10.1?
-0,4
0.3
C.6
-4.5?
-0.3
0.2
0.^
20
242
412
593
17
557
'5S4
1059
50? IK
npr
4.C%
0.6
0.4
0.3
-7
13
27
56
-2.5?
0.6
0.8
0.8
-1.2?
0.4
0. 5
0.6
37
258
424
603
1GC
647
IOB6
1184
! PLACE
5.7?
0.9
0.6
0.4
-15
5
21
49
-5.5?
0.2
0.6
0.7
-2.5?
0.2
0.4
0.5
30
253
420
599
77
620
i cr-s
1144
NONE II
29. 7T
3. 7
2.3
1.3
-61
-42
-20
22
-21.8?
-2. 0
-0.6
0.3
-3.7?
-1 .2
-0.4
0.2
-3
218
392
587
-270
343
776
8^5
^ PLACE
32.8?
4.3
2.7
1. 5
-77
-61
-42
3
-27.7?
-2.9
-1.2
0.0
-10.8?
-1 .8
-0. 3
0.0
-17
202
375
572
-343
283
715
76o
15? I!
RPT
21.3%
3.1
2.0
1. I
-51
-32
-10
29
-18.4%
-1.5
-0.?
0.4
-7.5?
-0.9
-0.2
0.3
5
226
400
590
— \ H H
398
833
908
V PLACE
23.8?
3.6
2.3
1.3
-65
-48
-28
15
-23.4?
-2.3
-0.8
0.2
-9.4%
-1.4
-0.5
0.2
-7
213
385
501
-253
35).
781
841
50? II
__££!_
9.2*
1.9
1.2
0.6
-29
-7
12
43
-10.4?
-0.3
0.4
0.6
-4.5?
-0.2
0.2
0.5
21
245
416
597
-25
526
966
1056
V PLACE
11.62
2.1
1.3
0.8
-37
-17
et
36
-13.3?
-0.8
0.1
0.5
-5.7?
-0.5
0.!
0.4
14
237
409
593
_ AO
499
9 ; 5
1016
-------
KEY VALUES OF IMPACT ANALYSIS:
REQUIRED PRICE INCREASE, AFTER TAX INCOKE:» R5TORN CN SALES S INVESTED CAPITAL, CASH FLOW, AND PRESET VALUES
UNDER VARIOLS IMPOSITICN CF HPT AND BAT CONTROL LEVELS
FOR PICKLE CANNING PLANTS — 1973
K_S Y y._A_L_U_£
2. AFTER TAX INCOME
($1000 )
AFTER TAX 5ETURN ON
SALES
R TAX RETURN CN
INVESTED CAPITAL
EST. CASH FLOW ON IN-
VESTED CAPITAL f £1000)
6. NET PRESENT VALUES
($1000)
TH NS
1500
6000
loooo
1500
6000
10COO
15CC
60^0
10000
1 500
6000
10000
1SOO
6000
10000
1500
6000
10000
BASE
14
59
108
1.6?
1 .4
1.5
3.5?
3.5
4. 1
27
H4
191
15
10
77
fi_2._E
NONE IN PLACE
2.3?
0.9
0.7
-4
86
1 .0
-0.9?
2.3
3. 1
13
104
179'
-131
-175
-155
2. 8?
I .4
1.1
-24
25
66
-2.6?
0.6
0.9
-5.2?
1.4
.?. 3
-3
170
-212
-274
152 IN
-SEI-
2.9?
0.3
0.6
-1
43
89
-0- 1?
1.0
1.3
-0.1?
2.5
3.3
16
105
181
-1C7
-] 47
-120
1_A_S
PLACE
2.9*
1.2
0.9
-17
30
72
0.7
1 .0
-3.8?
1 .7
2.6
. . 2
S8
173
-171
-221
5 0 0 N
50? IN
_££!_
1.5?
0.5
0.3
6
50
97
0.6?
1.2
1.4
1.3?
2.9
3.6
21 '
109
1S5
-51
-83
-39
PLACE
2.4?
0.7
0.5
-3
42
87
-0.3?
1.0
1.2
-0.6?
2.4
3.2
14
104
181
-89
-99
NONE' IN
10.3?
2.2
1.9
. -54
5
46
-6.0?
0. 1
0.7
-10.0? -
0.3
1.6
-22
85
160
-543
-431
-549
i £_T I
PLACE
11.47
2.7
2 .2
-74
-24
26
-8.2?
-0.6
0.4
-13.1*
-1.3
0.9
-38
63
151
-636
-521
-667
-Y,_AjL_E
15? IN
8.9?
1.9
1 .6
-43
16
56
-4.8?
0.4
0.8
-8.3?
0.9
1.9
-14
92
165
-448
-365
-455
PLACE
9.9?
2.3
1.9
-60
-5
39
-6.6?
-0.1
0.6
-11.1?
-0.3
1.3
-28
77
157
-527
-442
-556
_]i_.Q_£_J
50? IN
4.3S
1. 1
0.9
-18
34
77
-2.0?
0.8
1.1
-3.8?
2.0
2.8
5
102
176
-229
-211
-236
PLACE
1.3
1.1
-28
27
67
-3.12
0.6
l.C
-5.7*
1.5
2.4
-4
98
171
-274
-256
-2'?
-------
RFOUIRSO PRICF INCREASE,
KEY y_A._L_U_£
1. PRICE IMC?,FASE
SECURED
2. AFTER TAX INCOME
($1000)
3. AFTER TAX R=TU3\ ON
SAtfS
4. AFT El TAX PET'JR\' ON
INVrSTEO CAPITAL
5. EST. CASH FLOW CA1 IN-
VESTED CAPITAL ($1000)
6. NET PRESENT VALUES
($1000)
KE^ VALUES
-------
KEY VALUFS OF IMPACT ANALYSIS:
REQUIRED PRICE INCREASE, AFTER TAX INCOME, RrTURN CN SALES £ INVESTED CAPITAL, CASH FLOW, AND PRESENT VALUES
VDcR VARIOUS IMPOSITION' 0^ PPT AND PAT CONTROL LEVELS
FCR TOMATO CANNING PLANTS — 1973
i. PRICE INCRE
REQUIRED
2. A^TER TAX I.NCCVE
($1000)
AFTER TAX RETURN ON
SALES
••-. APTER TAX RETURN ON
INVESTED CAPITAL
5. EST. CASH FLOW CN IN-
VESTED CAPITAL ($1000)
5. NET PRESET VALUES
($1000)
TQ£i.S_
1500
4500
25CCO
150000
1500
4 5 CO
25000
150000
1500
4500
25000
150000
1 500
4500
25000
150000
1~500
4500
25COO
150000
1 500
4500
25000
1500CO
•BASE
£ Ajx£_
11
24
101
755
4.0%
2,9
2. 8
4,7
4.5%
'5.0
3.4
9.1
31
60
266
1140
165
244
365
5466
NONE IN
fJ£T
4.3%
2.1
0.8
.0.5
3
14
£3
722
1.2%
1.8
2.5
4.5
' 1.2%
2.8
2.9
6.5
27
56
264
1134
1C8
163
724
5083
PLACE
rjAI
<. .8%
3.3
1.6
1.0
-/.
4
71
667
-1.3%
0.5
2.0
4.2
'-1.2%
0.7 .
2. 3
7.5
24
51
. 262
1130
76
116
602
4692
15% IN
RPT
3.7%
l.fl
0.7
0.4
5
16
90
727
1.7%
2.0
2.5
4.5
1.7%
3.2
3.0
fa. 6
28
57
• 264
1135
117
175
745
5140
PLACE
£AT
5.6?
2.3
1.3
C.9
-1
7
75
680
-0.3%
0.9
2.1
4.3
-0.3%
1.3
2.4
7.8
25
53
263
1131
91
136
641
48r^
50% IN
APT
2.2%
1.1
C.4
0.3
7
20
95
739
2.6%
2.4
2.7
4.6
2.8%
4.1
3.2
8. 8
29
59
265
1137
136
204
795
5774
PLACE
BAZ
3.2%
1.7
0.8
0.5
i
15
86
711
1.5%
1.8
2.4
4.4
1.5%
2.9
2.8
8.3
28
56
264
1135
122
ISO
73?
5079
NONE IN
_££!_
15. er,
6.6
2.6
1.6
-26
-13
61
642
-9.35
-1.6
1 .7
4.0
-6.8%
-2.1
1.9
7.1
12
43
261
1127
-101
-9
'•35
4249
PLACE
2AI
17.5%
7.8
3.3
2.1
-34
-26
44
586
-12.2%
-3,2
1.2
3.7
-8.4%
-4.0
1,3
6.3
7
35
259
1122
-136
-56
312
3858
15% IN
P, C1 T
12.5%
5.6
2.2
1.4
-20
-6
67
659
-7.1%
-0.7
1.9
4. 1
-5.5%
-1.0
2.1
7.4
15
47
262
1129
-58
29
499
4432
PLACE
_£AI_
14.7%
6.6
2.8
1.8
-26
-17
52
612
-9.6%
-2.1
1.5
3.8
-7.0%
-2.8
1.6
6.7
11
40
260
1125
-87
-11
395
4100
501 IN
_££!_
9.3%
3.3
1.3
0.8
-6
8
81
698
-2.0%
1.0
2.3
4.4
-1.8%
1.5
2.6
8.1
23
54
263
1133
43
117
650
4858
PLACE
_££!_
10.6?
3.9
1 .6
1.1
-!0
3
72
671
-3.5%
0.3
2.0
4.2
-3. OS
0.5
2.3
7.6
21
51
263
1131
26
94
5B9
4662
-------
PRICE INCREASE, AFTER TAX INCOME? RFTURN ON SALES £*?NVESTEO CAPITAL, CASH FLOW, AND PRESENT VALUES
VARIOUS IMPOSITION OF PPT ANO PAT CONTROL LEVELS
FOR CORN-PEA CANNING PLANTS — 1973
___ K_£._Y. ___ y_
1. 3R1CE INCREASE
R E CU I R E n
ft-TER TAX INCOME
t tlOOO)
3. A'TER TAX F5TURN ON
SALFS
4. APTER TAX RETURN ON
INVESTED CAPITAL
5. EST. CASH FLOW ON IN-
VESTED CAPITAL ($1000)
6. NET PRESENT VALUES
($1000)
M<-
3000
1 2 ' 1 C 0
37000
1 2 0 0 C 0
?000
12 COO
37000
12JOOO
3000
12COO
37000
120000
30CO
12000
? 7COO
120'.'01
TOOO
12000
37^00
120000
3 0 ~ 0
12000
370CO
120000
BASE
28
102
301
966
4.5%
3. 7
3. 5
3.5
6.8%
0.9
7. 8
8.4
57
197
1416
258
777
1 7QO
5461
NONE IN
3.0%
1 .5
1 .0
0.7
20
63
265
878
3.1%
3.0
3.1
3.2
4.3%
0.7
6.6
7.4
54 .
191
469
i 6 i
583
1400
4521
PLACE
4.3*
2.0
1.3
0.9
10
73
246
837
1.6%
2 .6
2.9
3.0
2.2% •
0.6
5. 9
6.9
' 48
188
4-65
1371
1 -1 f\
513
12 ',3
4235
15* IN
_2nl_
2.6%
1.3
0.8
0.6
21
86
271
891
3.3?;
3.1
3.2
3.2
4.7%
0.7
6.7
7.6
55
' 192
471
1386
181
612
1458
4662
PLACE
_££!_
3.6%
1.7
1. I
0.8
14
77
254
856
2.2%
2.3
3.0
3.1
2.9%
0.7
6.2
7.1
50
189
468
1378
149
553
1346
4419
50? IN
£PT
1.5%
0.7
0. 5
0.4
24
93
283
922
3. 8%
3.4
3.3
3.3 •
5.5%
0. 8
7.2
7.9
56
194
475
1398
? I 2
680
4991
PLACE
fiAI
2. IT,
1.0
o.e
0.5
21
87
274
901
3.3*
3.2
3.2
3.3
4.7%
0.8
6.8
7.7
54
193
473
1394
1
-------
KEY VALUES OF IMPACT ANALYSIS:
REQUIRED PRICE INCREASE, AFTER TAX INCOME, RETURN CN SALES G INVESTED CAPITAL, CASH FLOW, AND PRESENT VALUES
UNDER VARIOUS IMPOSITION OF BPT AND BAT CONTROL LEVELS
FOR CCRN-PEA-G8-CARPOT CANNING PLANTS — 1973
1. PSICE INCRFAS5
°ECUIB ED
2. AFTER TAX INCOME
(S1000)
AFTER TAX RETURN CN
SALES
4. AFTER TAX RETURN ON
INVESTED CAPITAL
5. EST. CASH FLOW CN'• I IN-
VESTED CAPITAL (*1000)
6. r: = T PRESENT VALUES
($1000)
TONS _
100CO
25COO
50000
10000
25000
50 COO
10CCO
25000
50000
10COO
25000
50000
10000
25-QOO
•50CCO
10000
25000
STOCO
BASE r
^L5i"
71
171
333
3.0%
2.3
2.8
6.2%
6.4
6.8
141
371
633 '
456
1253
2033
>
-------
KEY VALUES OF IMPACT ANALYSIS:
REQUIRED PRICE INCREASE,' AFTER TAX INCOME, RETURN CM SALES C INVESTED CAPITAL, CASH FLOW, AND PR"SCNT VALUES
UNDER VARIOUS IMPOSITION OF BPT AND BAT CONTROL LEVELS " "
FOR CCRf;-?E A-GB-CARPOT FREEZING PLANTS — 1973
1_A_G_£_C_N..
1. "'ICE INCREASE
RECUIR ?n
2- APTER TAX INCOME
(tiooo)
AFTER TAX RETURN ON
SALES
AFTER TAX RETURN ON
INVESTED CAPITAL
EST. CASH FLCW ON IN- -
VESTED CAPITAL (S10CO)
\!i: I P^t ${•*!! VALUbS
(<1000)
. T C N S
5000
10000
IS 000
25000
50COC
5COC
10000
13^00
25000
50000
5000
10000
13COO
25COO _
50000 '
5000
10000
18000
25000
50000
5COO
10COO
1BCOO
25000
53000
SOOt;
10000
1RCOO
25000
50000
BASE
£.A.S£_
41
76
107
147
286
4.3?
4.0
3.0
3. 7
3.6
5. or
5.5
6. 0
: 6.0
6.6
87
148
757
307
586
3fO
612
997
1167
2291
NONE IN
_fiPT_
3.6?
2.7
, 2.6
2.4
1.9
26
53
74
105
- " 228 _.
2.7?
2.8
2.6
2.7 '
2.9
2.9?
3.6
3.3
4.0
4.9 .
61
139
244
290
. 553
208
370
641
723
1564
PLACE
MI
5-4?
3-9
3.9
3.5
2.8
9
36
48
73
177
1.0?
1.9
1.7
1.8
2.2
1.0?
2.3
2.-^
2.6
3.6
72
1?3
237
231
533
126
259
474
bll
123-*
15? IN
£P 1
3.1?
2.3
2.2
2.0
1.7
28
56
79
111
236
3.0?
3.C
2.8
2. • n
3.0
3.2?
3.9
4.1
4.2
5.2
82
140
246
293
558
232
406
694
7P9
1673
PLACE
££T
4.6?
3.3
3.3
3.0 •
2.4
15
42
57
04
193
1.6?
2.2
2.0
2.1
2.5
1.7?
2.7
2.8
3.0
. 4.0
76
1?6
240
2P5
5^5
163
312
553
609
1392
50? IN
yp I
l.S?
1 .4
1.3
1.2
1.0
33
64
90
126
257
3.5?
3.4
3.2
3.2
3.3
3.9?
4.5
4.9
4.9
5.8
84
143
250
29fi
569
2S9
491
319
945
1927
1 PLACE
— £AI_
2.7?
2.0
1.9
1.8
1 .4
27
56
78
110
232
2.8?
3.0
2.7
2.8
2.9 .
3.0?
3.8
4.1
4.2
5.0
81
141
247
294
562
248
4?'>
735
839
1762
NONE IN
fi£LI
9. 3?
6.5
6.2
5.5
4.3
-15
19
27
48
132
-1.6?
1.0
1.0
1.2
1.7
-1.5T
1.2
1.3
1.6
2.6
60
130
232
277
541
-70
?.(.•
169
•141
680
! PLACE
BAJ.
11.6?
7.8
7.4
6. 6
5.2
-40
-8
-9
14
81
-4.3?
-0.4
-0.3
0.4
1 .0
-3.7?
-0.5
-0.4
0.4
1.5
43
114
214
266
527
-152
-?5
2
-71
350
15? IIS
RPT
fl.3?
5.6
5.2
4.7
3.7
-3
28
39
63
155
-0.3?
1.5
1.4
1.6
2. 0
-0.3?
1.7
1.9
2.2
3.1
68
133
236
282
548
-4
114
2^3
294
922
. V J 1
1 PLACE
RA.T
9.9?
6.6
6.3
5.6
4.4
-24
10
17
35
112
-2.6?
0.5
0.6
0.9
1.4
-2.3?
0.6
0.8
1.2
2.2
53
125
229
274
536
-74
20
151
114
6M
Tlml y 1-. L?
50? IN
_££!_
4.9?
3.3
3.1
2.7
2.2
20
48
67
97
209
2.1*
2.5
2.4
2.5
2.7
2.1?
3.2
3.4
3.6
4.4
SO
139
245
292
564
150
31"
533
654
1485
L
PLACE
_££!_
5.TT
3.7
3.3
10
39
55
ei
184
1.1%
2.1
1.9
2.1
2.3
1. I?
2.5
2.7
2.9
3.8
75
136
24-1
257
557
1C9
264
499
54°
1321
-------
K5Y VALUES CF IMPACT ANALYSIS:
REQUIRED PRICE INCREASE, AFTER TAX INCOME, .RETURN ON SALES 5 INVESTED CAPITAL, CASH FLOW, AND PRESENT VALUES
UNDER VARIOUS IMPCSITICN OF P.PT AND BAT CONTROL LEVELS
FOR BRCC-CLFL-LB-SPIN FREEZING PLANTS — 1973
1, PRICE INCREASE
REO'JIPFD
AFTER TAX INCOME
f S1000)
3. AFTER TAX PETURN CN
SALES
AFTER TAX RETURN OH
INVESTED CAPITAL
5ST. CASH FLCW CN IN-
VESTED CAPITAL (S1000)
6. NFT PRESENT VALUES
CS1000)
.XQ&'.5._
8000
25000
40000
8COC
25000
40 CCO
8000
25000
40000
3000
25000
40000
8000
25000
40COO
8000
25000
40000
BASE
EASE-
57
222
695
1.4%
1.8
3.4
3.3%
5.0
10.3
' 148
387
911
176
1C8
4907
NONE If
RPJ
1.2%
0.7
.0.6
25
. 182
641
0.9%
1.4
3.2
1.9%
4.0
9.2
127
368
8c5
-50
-314
4338
M PLACE
E-^1
1.9?
1.2
0.9
8
133
589
0.2%
1.1
2.9
0.4%
2.9
. 8.2
122
^49
857
-1 89
-582
•4031
15* IN
. ££*
1.0%
0.6
0.5
38
188
649
0.9%
1.5
3.2
2.1?
4.1
9.3
139
371
889
-16
-251
4423
1 PLACE
£ AT
1.6%
1.0
C.8
18
150
605
C.4%
1.2
3.0
1 .0%
3.2
8.5
. 129
354
S65
-135
-47d
4162
50% IN
JRPJ
0.6%
0.4
0.3
46
202
668
1.1%
1 .6
3.3
2.6%
4. 5
9. 7
142
377
898
63
-103
4622
PLACE
£AT_
1.0%
0.6
0.5
34
180
642
0.8%
1.4
3.2
1.9?
3.9
9.2
137
368
884
-7
-237
4469
NONE II
RPT
2.8%
1.7
1.4
-4
122
560
-0.1?
1.0
2. 8
-0.2%
2.5
7.7
118
341
846
-359
-902
3523
^J PLACE
_SAI_
3.5?
2.1
1.8
-48
73
507
-1.2%
0.6
2.5
-2.4%
1.6
6.8
86
322
818
--493
-1170
3217
15% IN
_SP.!_
2.4%
1.4
1.2
9
137
580
0. 2%
1.1
2.9
0.5S
2.9
8.1
126
348
855
-279
-751
3731
[ PlACc
RAT
3.0%
1.8
1.5
-26
100
535
-0.7%
0.8
2.7
-1.3%
2.0
7.3
102
332
832
-397
-978
3470
50% IN
rtp T
1.4%
0.8
0.7
31
172
627
0.8%
1. ^
3.1
1.7?
3.7
8.9
137
364
878
-92
-397
4215
i PLACE
B A T
1.8%
1.1
0.9
19
150
6C1
0.5%
1.2
3.0
1 .0%
3.2
8.5
132
355
865
-161
-531
4062
-------
KEY VALUES OF'IMPACT ANALYSIS:
RFCT'iRED PRICE INCREASE, AFTER TAX INCOME, RETURN CN SALES E INVESTED CAPITAL, CASH FLOW, AND PRESENT VALUES
UNDER VARIOUS IMPOSITION Of BPT AND BAT CONTROL LEVELS
FCR TO'ATO-ORY BEAN CANNING PLANTS — 1973
A._C._J_l_y._A_I_.E_n S-L-1L.P G £
< _£_ Y. i_ A_.L_LLJ
P?TCL" INC'EA
AFTER TAX INCOME
C$1000)
3. AFTER TAX RETURN ON
SALES
TAX RETURN ON
INVESTED CAPITAL
E?~. CASH FLOW ON IN-
-di-tTTAt r t i nf^rii
^ " r * !*•»*_ * •»• X w w f
VALUES
$1000)
_IGKS_
2COO
7000
20000
70000
125COO
2CCO
7000
20000
70000
125000
2000
7000
2 TOCO
70000
123000
7-000
7000
200QO
70000
125000
2000
70 CO
20000
70000
125000
2000
70CO
20000
70000
I 2 r' 010
BASE
22
58
158
360
633
3.3?
2.6
2.5 .
2.1
2.2
7.0?
5.5
5.2
3.9
3.9
35
102
276
723
1207
123
775
7 4 4
1559
2609
NONE IN
3.9?
1.5
'0.9
0.7
0.5
5
40
134
312
568
C.7?
1.8
2.1
1.8
2.0
' 1.4?
3.6
4.3
3.3
3.4
23
C3
263
709
1189
-2-
m
4fc *
1028
1872
ii n J —
PLACE
_MI_
5.7%
2. o
1. 5
1.1
0.9
-15
23
108
256
488
-2.2?
1.0
1.7
1.5 '
1.7
-3.91?
1.9
3.3
2.6
2.9
8
87
261
6^8
1174
-87
8
3CH
647
1"<26
_O 1 U_V
15? IN
_B£I_
3.2?
1.3
0.7
0.6
0.5
8
42
138
319
578
1.1?
1.9
2.2
1.9
2.C
2.2*
3.8
4.4
'3.4
3.5
25
94
270
711
1191
19
1 38
522
11C8
19H3
J* ii i.
PLACE
_££!_
5.5?
2.2
1.2
1.0
C.3
-9
28
115
271
510
-1.3%
1.3
1.8
1.6'
1.8
-2.2?
2.4
3.6
2.8
3.0
13
89
264
701
1179
-51
48
373
7S3
1518
I _ .W — 1* LA
50% IN
_2£I_
l.S?
0.3
0.4
0.3
0.3
14
48
146
336
601
2.0%
2.2
2.3
2.0
2. I
4.1%
4.4
4.8
3.6 .
3. 7
30
96
272
716
1198
62
1 9 4
614
1794
2241
PLACE
_Jiai_
3.C?
1.3
0.7
0.6
0.5
5
39
133
308
561
0.8?
1.8
2.1
1 .8
1. 9
1.5%
3. 5
4.2
3.2
3.4
24
93
269
710
1191
29
141
526
1103
1968
NONE ir>
_fi£I_
13.8?
4.6
2.6
1.8
1 .6
—43
3
93
221
430
-6.5*
0.1
1.5
1.3
1.5
-9.5?
0.2
2.8
2.2
2.5
-10
76
250
690
1164
-3fl*
-208
-33
97
458
4 PLACE
_M!_
15.5?
5.6
3.2
2. 3
2.0
-65
-29
66
164
350
-9.6?
-1.3
1.1
1.0
1.2
-13.2?
-2.2
1.9
1.6
2.0
-27
54
243
678
1150
-491
-313
-208
-290
— 33
is? ir
_S£I_
17.0?
3.9
2.2
1.5
1.3
-33
13
103
24-2
461
-4.8?
0.6
1.6
1.4
1.6
-7.5?
1.1
3.1
2.4
2.7
-3
82
254
095
1171
-293
-135
84
312
781
4 PLACE
_MJ_
13. 4t
4.8
2.7
1.9
1.7
-51
-11
80
194
393
-7.5?
-0.5
1. 3
1.1
1.4
-10.9?
-0.8
2.3
1.9
2.2
-17
67
248
685
1159
-380
-225
-65
-12
316
50? IN
_fi£I_
5.0?
2.3
1.3
0.9
0.8
-7
32
126
290
532
-1.1?
1.4
2.0
1.7
1.8
-1.9?
2.8
3.9
3.0
3.2
16
90
263
706
1186
-96
?4
356
826
1534
PLACE
_ fj A T
5.9S
2.8
1 .6
1.1
1.0
-18
23
1 12
2fi?
492
-2.7%
I .1
1.8
1.5
1.7
-4.4?
2.0
3.4
2.7
2.9
7
87
260
701
1179
-139
-19
26S
635
126C
-------
KFY VM.UES CP IMPACT ANALYSIS:
= OL!I".ED PRICE INCREASE, AFTER TAX INCOME, RF7URN GN SALES C INVESTED CAPITAL, CASH ^LCW, AND PRESENT VALUES
UNDER VARIOUS :MPCS!TICN P'" SPT AND EAT CONTROL LEVELS
FOR CHERRY-G3-PEAR-P'_'J'i CAN'MNS PLANTS — 1973
"" rCc INCREASE
SECIJI' ED
AFTER TAX INCOME
( S10TO)
A=TER TAX FFTURN ON
SALES
AfT-^ TAX PET URN ON
INVENTED CAPITAL
ES-. CASH CLCW ON IN-
V'STEO CAPITAL (S1000)
N'T ostSSFNT VALUES
(11000)
5000
10000
23COO
50CC
13100
2JOOO
5 COO
10000
20000
5TOO
10000
20COO
5000
no oo
200CO
5000
10000
20000
• BASF.
77
291
2.6%
3,6
3.6
9. 13
10. 1
i- 7
4- ,
759
1476
MCNE IN
£PI
1.5?
1.1
• 0.9
. 130
260
' 3. IX
3.2
7.0*
8.2
7.8
123
219
434
ill
• 50
11.20 •
4 2 i
PL ACE
2-3?
1 .7
1 4
112
2?. 3
2-5?
2.7
2-3
5. 3?
6.6
6.7
215
2M
428
L A i n_r
1 5 X IN
1 ~*> £
0.9
0.6
6t
1 3 1
265
3,2*
3.2
3.2
7.3?
8.5
8.0
124
435
342
581
1182
1 A <
PLACE
1.9%
1. 4
1,2
117
242
2.9
2.9
5.8%
7.1
7.0
121
431
. 275
473
1C2'»
i Q D N
50? IN
RP£
0.7S
0. 5
71
139
276
3.4%
3.4
3.4
8.0?
9. 1
3.5
125
221
433
392
655
13C3
PLACE
i. n
C.7
65
130
262
3.1?
3.2
3.2
7. 1%
8.2
7.9
124
435
594
1210
/
NONE IN
£PT
7 .6
1.9
101
222
2.02
2.5
2.7
4.02
5.8
6.3
118
211
423
88
258
751
I C. I 1
OLACF
3.2
2.3
29
83
195
1.4?
2.4
2.7%
4.5
5.3
114
207
418
8
136
565
V A T c
155 IN
3.32
2.2
I. 6
47
lOfl
233
2. 3*
2.8
4.6*
6.4
6.7
119
213
426
144
333
860
n 5 '
*LAC5
2.7
2.0
36
93
210
1.8?
2.3
2.6
3.4S
5.2
5.8
116
210
422
77
230
702
1! P G
50T IN
H£T
1.3
C.9
59
125
257
3.0
3.1
6.3%
7.5
7.7
122
217
276
509
1113
c
Pl^CE
2.:-?
i . f
1.2
C 3
i 1 6
243
2.3
5.C
5.5?
7.0
7.1
121
216
43C
236
4 4 8
102 n
-------
KEY VALUES OF I«P/CT ANALYSTS:
PRICE INCREASE, AFTER TAX INCOME, RETURN CN SALES £ INVESTED CAPITAL, CASH FLOW, AND PRESENT VALUES
I.NOER VARIOUS iMPCS!TIC'J Oc PPT AND BAT CONTROL LEVELS
FOR CHERRv-STR-j-CNBA FPEEinG PLANTS — 1973
P"IZ~ I^.CRFASE ' BOO
REQUIRED 2000
5000
A?* =3 TAX INCOME SCC
CilCCO) 2000
5CCO
iFTER TAX RETURN OM 800
SALES 2000
5000
;,---= TAX FETU3N CN 300
;>.V£S7fC CAPITAL ?COO
5000
E5.r. CASH FLCH CN IN- SCO
vV'TTED C4PITAL iS 1030 J 2000
5CCC
'4"T P-\ES'\T VALUES 600
(51000) 2000
5000
BASE
19 "
37
83
1.7%
1.4
1.2
4.4?
3.9
3.8
32
62
130
23
-41
-245
NONE IN
p, Q T
1 .3*
1.0
0.5
9
26
67
0.9%
1 .0
1,0
2.1?
2.6
3.0
26
57
123
-39
-163
-412
PL ACS
£* A T
2.1*
1,4
C.fl
I
14
53
0.1%
0.5
O.S
0.3?
1.4
2.3
22
31
1 i 8
- / £
.-2?0
' - 5 'J 0
IS? IM
i . 1 'i
c.s
0.4
I 1
27
69
l.C?
1.0
1.0
2.4S
2.6
j. 1
27
5 e
124
-29
-144
-367
PLACE
1.7?
1.2
C.7
A
15
57
C.-*
0.7
0.9
0.8%
• 1.9
2. -3
23
Ki.
120
-60
-193
-462
50? IN
p a-"-
0. 7?
0.5
0.3
14
31
75
1.3*
1.2
1. 1
3.2*
3.2
3.4
29
60
126
_ c
-102
-328
PLACE
(7 f\ T
l.C?
0.7
0.4
10
27
68
0.9?
1,0
1 ,0
2.2"
2.7
3.C
27
58
124
-22
-131
-372
NONE IN
4,4^
2.2
1.3
-19
--4
43
-1,6?
-0.2
0.6
-3.52
-0.4
1.8
11
41
116
.-25'-
-3 40
-659
PLACE
4. 6?
2 . ~
1.6
-29
-22
29
-2.7%
-0.8
0 .4
-5.1?
-2.0
1.2
5
28
111
-2 = T
-'•42
-747
155E IN
3.^
2.3
1.1
-13
4
49
-1.2?
0.2
0.7
-2.4%
0.4
2.1
15
46
llfl
-207
-329
-597
PLACE
4.2?
2.6
1.3
-21
-10
37
-2. OS
-0.4
0.5
-3.9%
-0.9
1.5
9
36
114
-244
-378
-b72
50% IN
"PI
2.5*
1.3
0.7
2
21
63
0.2*
0.8
0.9
0.4?
2.0
2.3
24
56
123
-99
-211
-452
PLACE"
_£!!_
l.f
0.8
— 3
14
56
-0.3S
C.5
0.3
-0, 5?
i .4
2 .4
21
52
120
-12:
-23S
- 4 ^ t
-------
KEY VALUES OF IMPACT ANALYSIS:
PPICc IVREASEt AFTER TAX INCOME, RETURN CN SALES 5 INV-STF.R CAPITAL, CASH FLOW, AND PRESENT VALUES
UNDER VARIOUS I^POSITICN OP PPT AND B.^T CONTROL LEVELS
TCR PICKLE-TOWT-C8-OSS4 CANNING PLANTS — 1973
.A_C._I_l_y_A._I_E_IL
, __
2.
3.
4 *
5.
6 .
FKlCr INCREASE
RSQUi'EP
J5-TER TAX I.NCQME
( SI 000!
AP-E-. TAX RETURN ON
SAL6S
ArTc3 TAX =E"U"N ON
;-:V5STFO CAPITAL
E$T. CASH CLOW ON itj-
VrSTED CAPITAL t $1000)
\-T P3ESFN' VALUES
! S1000)
2000
6000
18COO
60 CCO
2COO
6000
1SOCO
600^0
2000
6000
18000
60000
2 COO
6 CCC
.1 °000
6 COCO
2000 '
6000
loTOO
60000
2000
60 JO
1 8000
60000
8.
72
202
505
1967
3.7*
3.4
3.4
3.4
.3 • I 9»
4.0
?,6
9.9
180
454
833
2507
638
165<>
3323
9689
NONE IN
RPT
' 0. s
-
0.,
£. :
187
573
1924
3.1%
3.2
3.3
3.3
2 .6%
3.6
7,2
9.6
173
446
872
2'- 8 8
-31
r- "'
\ f.
• . C5
9240
PLACE
1 * 7 *
0.8
0.4
0.2
52
1 /4
5:3
18S6
2.6?
3.0
3,2
3.2
2.27
1 .4
6.9
9.4
167
433
S^2
2472
480
1423
2933
9007
15% IN
RPT
1.0?
0.5
0,2
0. I
C
1G9
576
1930
3.2?
3.2
3.3
3.3
2.7?
3.7
7.3
9.7
• 174
4^ ;
873
2491
547
1525
3139
93C7
PLACE
AA T
1.4%
C.7
0.4
C.2
55
173
559
1898
2.8%
3.0
'3.2
3.3
2 . 3%
. 3.5
7.0
9.4
169
440
865
2477
5C4
1462
3C35
91 09
50* IN
0.0%
0.3
0. 1
0. 1
67
195
534
1945
3.4%
3.3
3.3
3.3
2.9"
3.3
7.4
9.3
177
450
877
2497
5S5
1579
3216
9465
"LACE
0. 3?
0.^
0,2
0. 1
62
1S8
574
1926
3.2%
3.2
3.3
3.3
2.6%
3.7
7.2
9.6
174
446
872
2489
559
1542
3156
9343
NONE IN
gOT
4.5?
1.8
0.8
0.4
30
152
530
1854
1.5?
2.6
3.0
3.2
1.2"
2.9
6.5
9.1
160
431
854
2456
216
1152
2672
854 R
PLACE
5.1?
2.1
0-9
0.5
21
139
510
1316
1. 1%
2.4
2.9
3.1
0 . 8%
2.6
6,2
8.9
153
423
B45
2440
166
1073
2550
8315
15% IN
3.?%
1.5
0.7
0. 4
37
160
540
1871
1.9%
2.7
3. 1
3.2
1 . 5>
3.0
6.7
9,3
163
434
85Q
2^-64
28 C
1225
2770
8719
PLACE
4.3T
l.S
0,6
0.4
29
!49
523
1839
1.5%
2.5
3.0
3.2
1.2%
2.8
6.4
9.0
157
427
850
2^-50
236
i I ',- 5
2667
8521
50? IN
_££!_
2 . 3S
0.9
0.4
0.2
51
177
562
1910
2.63
3.0
3.2
3.3
2. 13
3.4
7.0
9.5
170
443
869
24 Cl
427
1404
300C
9118
°L ACE
_P JT ^
2.52
1.0
0.5
0.2
47
171
552
1891
2-1%
2.?
? . 2
3.2
1.9%
3.3
6.9
9.4
167
439
864
2473
4C?
1367
2939
9002
-------
KEY VALUES OF IMPACT ANALYSIS:
PRICE INCREASE, AFTER TAX INCO'-^, RETURN c\ .SALES £ tWtSTFD CAPITAL, CASH FLOW, AND PRESENT VAL';FS
UN3E* VARIOUS riVTS ITICN OF RPT AW BAT CCN'TPCL LEVELS
rcR SKINFD psrrucr CANNING PLANTS — 1973
,,.,,, :. .^;ri$r
n E OU ]'- c 0
ATT?K TAX INCOME
1 $ 1 0 o 0 )
AFTER TAX "FTURN ON
SALES
_^
r
\"-'~, TAX Pr.T:j3\ C\
r.v'"STrc CAPITAL
HST. CAS^ PLCH CN IN-
V"ST = 0 CAP ITAL I HOOO)
\'?T P
316
NONE IN
JpT
4 . r?
2.2
2.4
11
57
75
2.2?
3.1
3.8
3.1?
',.5
5.1
22
127
159
fl7
4 12
5P5
PL \CE
7.5T,
3.2
3. 7
-5
^ '
:")=;
-1.0?
2 . 3
2.«
-1.3?
3. 1
3-6
19
I 1 8
ISO
03
3/1
4 o 6
is? IN PLACE
'-. . 1 ?, 6 . 1 T
1 , t- 2.7
2.1 3.1
14 1
f, :-J
7 'i fc /
2. /'? 0. 22
3.3 2.5
3 . ••? 3.1
3.8? 0.2?
4.7 3.5
5 ., 4 4 . 0
3-+ 24
128 121
161 1 r- 'i
'104 .45
•'-3'v 2k2
619 E 1 fl
50? IN
2.«
: . i
1 .2
20
66
87
3.9?
3. 6
4.3
5.6?
5. 3
6.0
39
132
166
145
504
7CC
PLACF
3.5"
1 .6
1.8
12
58
77
2.4X
3.2
3.8
3.4?
4-. 6
5.2
33
127
161
117
^59
641
NO^
I*5-?
5.2
6.. 6
-36
26
36
-7.0
1.4
1 .8
-7.5
1 .°
2.2
0
113
141
-257
156
ic. 1
IN FlACf
* 20,13:
^ . ?
7.H
-55
£>
14
": -ao.fi?
0.3
0.7
'" —11.1?
0.'»
0. 3
-It.
99
130
-350
A ^
72
15? IN
P. PT
13. 0?
4.4
5 .6
-25
33
45
-4,9?
1.8
2.3
-5.5?
?.S
2.6
8
116
146
-17C
•*• ') ~>
2^5
PLACE
14.6?:
5.3
6.7
-41
20
20
-3.1?
1.1
1.4
-S.7?
1.4
1. 7
-6
109
138
-245
145
1S4
50?: IN
7.9?
2.6
3.3
0
50
67
0.1?
2.8
3.3
O.IK
3.9
4.4
27
125
157
12
376
504
PLACF
9.~?
3- 1
3.9
-9
42
57
-1.67
2.4
2.9
-2.2?
3.2
3.7
19
120
152
-26
331
444
-------
•,r.OJ!?E:> P^ICr INCREASE,
AFTER
TAX INCO
UNDLR VARIO
K r v v -'• L U c "rflNS
•^ :c~ :\; .>;AS? • 1000
» "Q'l I "! - 0 2500
3000
1 3 T 0 C
-< icor
:. AFTE=. TAX !«;CGUE no"
mOGCJ 250C
3000
1 3 C C 0
3CCOO
APT;? TAX C'ETU"N CN 1000
SALES 2500
8CCC
13CCC
30000
a=T=» TAX ^CTIRN ON 1000
:\/=;TED CA^IT^L 2500
3000
13000
30CCO
C"7. CASU FLOW ON IN- 1000
VCSTEO CAPITAL uiooo) 2500
8CCO
• 13:00
30000
NIT PRESENT VALUES 1000
($1000) 2500
3000
1 3000
30COO
BASE
f .', " c
16
31
63
75
100
2-5^
2. 1
1. 7
1 .
-17
5
4 1
4 °.
63
-2.77;
0.3
1 . I
C. <5
f'.6
-A.3?
0.6
1. 3
: . 5
' 1.1
1 5
75
227
?< 2
275
-62
41
273
217
- 5 '-3
yrs OF IMPACT
Un'J UN SALT-S S
S(T:C'N CF HPT
C H IP 0 1 MY C F .
/A ^ £ 0 i. A
1 ",- Z I f\ P L A C E
Si-'T -'AT
3.1? 4.9%
^ . 5 2.1
C .6 C . 8
0,5 0.3
0.4 C . S
2 - 11
?1 I .1
52 44
62 52
31 68
0.3; -i.e.?
1.4 C . 7
1-4 1.2
i.2 1.0
0.7" 0.6
0.62 -2. 93
2-4 1.1
2-3 1 . V
i . ° - i . 6
1.5 1-3
31 19
87 79
234 229
301 294
385 378
22 -31
1C8 66
348 30
303 750
— u 2 S — r* ^ 0
ANALYSIS:
I MV r S 7 r C
CAPITAL, CASH
FLOW,
AM) PRESENT VALU
HS
ANG HAT CONTROL LEV=LS
PLANTS -
r:_C C £L_
502 IN
fv ^ ~
1.6%
0.9
0.4
C. 3
0.2
8
25
5 7
A ^
39
1 -2?
1.7
1 . 5
1-3
0. 8
2, r?
3.C
2 .5
2. 1
1.7
35
90
237
303
389
59
149
392
"^ V ^;
-3 'i 3
- 1973
PLACC NONH !
R .1 J ri P T
2.6^ 16.4?
1.2 5. *
0.5 2.5
0.4 2-2
0.3 i. , 2
1 -60
20 -.!6
52 lo
62 24
81 37
0.2* -9. «?
1.4 -2.5
1.4 0.5
1.2 0.5
0.7 0.3
0.3? -12.2?
2.4 -3.T
2.2 0,7
1.9 0-7
1.5 0. 7
30 -14
?6 43
233 21^
3 C 0 2 .3 4
385 366
35 -479
125 -226
3C- C 7
323 - "? 7
-3 £7 -fa 70
u .- j_
N PLACE
"AT
i • - 7 ^
6.3
2 - d
2 . ^
I . ?
•? -7
-54
^
9
2 I
-12,47
-3.7
0.1
O.'1
C. 2
-15. OT
-5. '-
0.2
0. 3
C. ,
-70
3 ?
200
2 7 3
357
-55?
-287
-4 5
-1 3C
_o ; 7
'_V A T -
15* IV
ROT
14. 2J
^. 5
2 . 1
i. . 7
1 .0
-43
-24
25
32
46
-7.8?
-1 .6
0. 7
r.6
0. 4
-10.2?
-2- 5
1.0
o. c
0.3
_5
57
222
2?7
370
-37?
-161
74
0
-7 7 3
n ^
P^ACr
R.'. T
1 5.4?
5. 1
2.4
1.9
1.2
-62
-39
16
22
33
-IQ.lt
-2.7
0.4
0.4
C.3
-12.8?
-4,0
0.6
0.7
G.6
-17
45
216
Z-'-l
363
-439
-202
30
-52
-648
1 U I £
5C? IN
^ P -
6.62
3.2
1.3
1 .0
0.6
-20
4
41
50
68
-3.22
0.3
1 .1
0,9
0.6
-4.f5l
0.4
1 .7
! .5
1,3
15
77
22a
295
sec
-140
-S
231
Jell
-548
PLf CF
D • T
7.27
3.5
i .4
T . !
C.7
-29
-4
B5
4i
61
-4.6?:
-0,3
1 .0
O.f
0.5
-6.6?
-0.4
1.5
1 .3
1.1
3
71
226
2^2
376
-172
-33
205
130
-592
-------
EPA-230/1-75-036
MIIiLIOGKACIIIC UA1 A
M i r i. r
4, I i.lc .mJ ,sul.,-..ini^Jiirn KCJ
No.
10. lJlOJCtl/ I .I'.'l / V oil. LIllll Nc
Task Order No. 17
) ]. Contrjci /(<.-. i in No.
Contract No".
68-01-1533
K'-. Type ot iU pc-ri ^ Period
Covcied
Final Report
U>. Suj>p)<.i,Kmj:y Notes
16. Ab: tracts
The economic impacts of proposed effluent guidelines on the fruit and vegetable
canning, freezing and dehydrating industry are assessed. The analysis includes
classification and description of types of firms and plants; financial profiles,
investments and operating costs, and profits for representative model plants;
evaluation of pricing mechanisms and pricing relationships and descriptions of
analytical procedures employed. The financial impact of proposed effluent treatment
technology was assessed in terms of prices, industry returns, volume of production,
employment, community impacts and international trade.- In general, the extra small en*.
small plants were most highly impacted, primarily because of economies of scale which
exist in pollution control costs. In addition, those industry segments having iower-
than-averoge returns suffered, e.g. the freezing industry and pickle processors. The
canning industry was not as highly impacted as most other segments because of a higher
jDrqiwrJy^n_j^f^arj:je^^^ plants. However, the imparts were ninim
17. Key VorJs ,in,i Dccui,;ci.t .-\m>Ms. I/a. Dcscii;no:i. (COTittnTJeO
Water pollution, economic analysis, fruits and vegetables, canning, freezing, dehy-
drating, preserving, pollution, industrial wastes, economic demand, supply, prices,
variable costs, fixed costs, fixed investment, discounted cash flow.
;'7b. Idcruifieis/'O[ cn-f.iidej TCF.TI
02 Agriculture, B-Agricultural economics
05 Behavioral and Social Sciences, C-Economics
IS.
.M. ,..,, i r
293
-------
16. Abstracts (continued)
as guidelines were not established for plants processing 2,000 tons or
less of raw products and BAT guidelines for plants in the 2,001 through
10,000 ton category were made equivalent to BPT. Under BPT guidelines
it is estimated that only 10 plants will close with an additional 3 plants
projected to close as a result of BAT guidelines. Since these closures
were in relatively small plants, production losses were negligible, less
than 0.2% of total industry production.
DATF DUE
------- |