U.S. Dairy Industry at a Crossroad:

Biotechnology and Policy Choices

May 1991

OTA-F-470

NTIS order #PB91-198085
Recommended Citation:

U.S. Congress, Office of Technology Assessment, U.S. Dairy Industry at a Crossroad:

Biotechnology and Policy Choices--Special Report, OTA-F-470 (Washington, DC: U.S.

Government Printing Office, May 1991).

For sale by the Superintendent of Documents

U.S. Government Printing Office, Washington, DC 20402-9325

(order form can be found in the back of this report)
Foreword

In the 1990s the U.S. dairy industry will experience a technological revolution that will place the

industry at a crossroad. This industry will be the first to experience the biotechnology era in American

agriculture. New animal health, reproduction, and food processing technologies are being developed.

Advanced scientific techniques will be used to produce transgenic animals. These technologies can be

used to increase milk production, improve the efficiency of food processing, develop new milk products,

increase herd quality, and improve animal health.

Many of the new technologies may create some controversy. But in the early 1990s, the most

pervasive and controversial technology will be bovine somatotropin (bST) produced through

recombinant DNA technology. Research has shown that the annual gain in milk output per cow from bST

would take 10 to 20 years to achieve using current breeding methods. The technology is presently under

review by the Food and Drug Administration. Public concerns have been raised about recombinantly

derived bST that include the safety to humans of dairy products produced from bST-supplemented cows,

the safety of the technology to the animal, and the economic consequences for many dairy farm operators

in this country. Some States have placed a moratorium on the use of this technology, even if approved

by FDA, and some large retail food chains have refused to sell milk and dairy products from bST test

herds even though FDA has approved their sale.

Congress requested the Office of Technology Assessment to examine the emerging technologies

that will potentially be available to the dairy industry in the 1990s. This Report analyzes these

technologies with special attention to bST. The analysis includes an assessment of bST, a discussion of

other emerging technologies in this decade, and an economic and policy analysis of the impact that these

technologies, including bST, will have on the dairy industry.

The report concludes that, based on today’s research findings, bST poses no additional risk to

consumers and does not produce adverse health effects to cows. However, if approved by FDA, bST will

accelerate trends that already put additional economic stress on dairy farm operators in many areas of the

country. Other new technologies that may become available during the decade may also have similar

impacts as bST and raise similar issues. The industry in the decade of the 1990s will be at a crossroad

with important decisions concerning new technologies and public policies.

This report was requested as part of a larger study examining emerging agricultural technologies and

related issues for the 1990s. The study was requested by the Senate Committee on Agriculture, Nutrition,

and Forestry, the House Committee on Government Operations, and the House Committee on

Agriculture. The first report issued from this study was Agricultural Research and Technology Transfer

Policies for the 1990s. Two remaining reports are in progress. Findings from this report are relevant to

specific legislation regarding dairy policy that was debated for the 1990 Farm Bill. The information

contained in this report was made available to Congress for that debate.

OTA appreciates the support this effort received from the contributions of many individuals. In

particular, we are grateful to workshop participants, contractors, reviewers, and informal advisers who

provided invaluable assistance in analyzing the issues on this subject. OTA, however, remains solely

responsible for the contents of this report.

~ f ~

a’iL# ‘ >

JOHN H. GIBBONS

~ Directo r
OTA Project Staff--U.S. Dairy Industry at a Crossroad

Roger C. Herdman, Assistant Director, OTA

Health and Life Sciences Division

Walter E. Parham, Program Manager

Food and Renewable Resources Program

Michael J. Phillips, Project Director

Marie Walsh, Analyst

Kathy Hudson, Analyst 1

Susan Wintsch, Editor

Administrative Staff

N. Ellis Lewis, Office Administrator

Nellie Hammond, Administrative Secretary

Carolyn M. Swann, P.C. Specialist

Consultants/Contractors

Dale E. Bauman, Cornell University

William Hansel, Louisiana State University

Susan K. Harlander, University of Minnesota

Ronald D. Knutson, Texas A&M University

J. Thomas McGuckin, New Mexico State University

Bennie I. Osburn, University of California, Davis

Derrell S. Peel, Oklahoma State University

James W. Richardson, Texas A&M University

IFrom September through December 1990

iv
Contents

Page

Chapter I: Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. .. .. .. .. .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Chapter 2: Overview of the Dairy Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Chapter 3: An Emerging Technology: bovine Somatotropin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Chapter 4: Emerging Technologies in the Dairy Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

Chapter 5: Economic and Policy Impacts of Emerging Technologies on the U.S. Dairy Industry . . . . . . . 73

AppendixA: A National and Regional Analysis of the Adoption of bovine Somatotropin . . . . . . . . . . . . . 89

Appendix B: Detailed National and Regional Impacts of bovine Somatotropin

and Other Emerging Technologies Under Alternative Dairy Policies . . . . . . . . . . . . . . . . . . . . 93

Appendix C: Detailed Farm Level Impacts of bovine Somatotropin and Other

Emerging Technologies Under Alternative Policy and Demand Scenarios . . . . . . . . . . . . . . . 102

Appendix D: Workshop Participants and Reviewers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
Chapter 1

Summary
Contents

Page

AN EMERGING TECHNOLOGY: BOVINE SOMATOTROPIN (bST) . . . . . . . . . . . . . . 3

Production Response . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Food Safety Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Effect on Milk and Meat Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Effects on Bovine Reproductive Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Effect on Bovine Health and Stress... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Commercial Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Product Labeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

OTHER EMERGING TECHNOLOGIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

ECONOMIC AND POLICY IMPACTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Dairy Industry Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Technology Adoption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

National Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Farm Level Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Science Policy and Emerging Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Figure

Figure Page

l-1. Projected Impact of a 10-Percent Permanent Demand Reduction on U.S.

Government Milk Purchases Under Alternative Dairy Policies, 1990-98 . . . . . . . . . . 10

Tables

Table Page

l-1. Level of Milk Production, With and Without bST, Under Alternative Policy

Scenarios, 1990-98 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

l-2. Level of CCC Purchases, With and Without bST, Under Alternative Policy

Scenarios, 1990-98, Milk Equivalent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

l-3. Impacts of bST Adoption on the Economic Viability of Moderate-Size

Representative Farms, Assuming No Change in Demand for Milk Due to bST,

Trigger Price Policy, by Region, 1989-98. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

l-4. Impacts of bST Adoption on the Economic Viability of Large Representative

Farms, Assuming No Change in Demand for Milk Due to bST,

Trigger Price Policy, by Region, 1989-98 . . . . . . . . . . . . . . . . . . . . . . . . . . . ,.... . . . 11

l-5. Impacts of bSTAdoption on the Economic Viability of Representative Large

(125-Cow) Upper Midwest Farms Under Alternative Dairy Policies, Assuming

No Change in Demand for Milk, 1989-98 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

l-6. Impacts of bST Adoption on the Economic Viability of Moderate-Size

Representative Farms, Assuming Small Decrease in Demand for Milk

Due to bST, Trigger Price Policy, by Region, 1989-98 . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Chapter 1

Summary

The dairy industry will lead U.S. agriculture into

the biotechnology era of the 1990s, and also will feel

the first profound impacts of emerging technologies.

Recombinant DNA techniques, cell culture and

antibody methods are but a few of the new biotechnology techniques that will produce technologies that will sustain or accelerate the historical

2-percent annual increase in milk output per cow.

Whereas farmers once had no choice but to

pasture bulls with cows and let nature run its course,

artificial insemination has provided a means of

controlled breeding since about 1950. In the near

future, farmers will potentially exercise even more

control over herd reproduction and genetics and over

the health and milk-producing potential of their

animals, For example, embryos produced by in vitro

fertilization (of ova from selected females with

sexed sperm) and placed at predetermined times into

the uteri of estrous-cycled animals can result in

higher conception rates than are now obtained by

artificial insemination. This will accelerate genetic

gains. Monoclinal antibodies used as diagnostic

agents will greatly reduce the cost, time, and labor

required to maintain animal health. Bovine somatotropin produced with recombinant DNA technologies has the potential to greatly enhance milk

production per cow.

The emerging biotechnologies will require considerable management expertise on the part of

farmers. Information technologies will be powerful

aids to farm operators. Expert systems, for example,

make onfarm consulting accessible via a microcomputer and can aid farmers with decisions regarding

management and new technology adoption.

Many biotechnologies will be controversial, most

notably bovine somatotropin (bST). Although bST

can boost milk yield per cow significantly---doing in

1 year what it would take 10 to 20 years to achieve

with current reproductive technologies, concerns

have been raised about its safety for humans and

animals and about the economic consequences of its

use for the industry. In response to these concerns,

two States placed a moratorium on the use of bST if

approved by the Food and Drug Administration

(FDA); up to four States are seriously considering

laws that would require milk and dairy products

produced from bST-supplemented cows to be so

labeled. Major retail food chains have curtailed sales

of milk and dairy products from bST test herds even

though FDA has approved their sale.

In addition, issues concerning science policy have

been raised in conjunction with biotechnology—

including bST. These issues include the social needs

being met by these new technologies, the appropriateness of public sector investment in their development, and lack of information about benefits and

risks of a new technology prior to commercialization. This report analyzes the major questions

concerning the use and safety of bST, examines

other technologies that will affect the dairy industry

in this decade, and evaluates the economic and

policy implications of these issues.

AN EMERGING TECHNOLOGY:

BOVINE SOMATOTROPIN (bST)

Some 50 years ago, research showed increased

growth rates in rats injected with a crude pituitary

extract. Later it was discovered that the extract,

which contains a protein hormone called somatotropin, also affects lactation, and research with

lactating cows ensued. Prior to the 1980s, progress

was slow in bST research because: 1) the availability

of bST was restricted to that which could be

extracted from pituitary glands of slaughtered animals, limiting studies to a few cows and short

timeframes; and 2) the mechanism of action for bST

was thought to be acutely stimulated use of body fat

reserves: scientists believed it would only work in

fat cows with a low milk yield. No studies used high

milk-producing cows because it was assumed that

acute mobilization of body fat reserves would cause

ketosisl and other adverse health effects.

In the late 1970s, new research showed that the

physiological basis for more efficient milk production in genetically superior cows was better use of

absorbed nutrients. Scientists recognized the need

for new concepts regarding nutrient regulation in

1A me~bolic disorder which occurs when production of ketones exceeds the ability of the body to use tiem. OCCUrS in dairy cows when he ne~

for glucose exceeds the production of glucose.

–3–
4 ● U. S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

animals. Recent work has demonstrated that somatotropin exerts key control over nutrient use. When

administered exogenously, bST markedly improves

productive efficiency in lactating cows. In the last

decade, as the important role of somatotropin has

been established, bST produced by recombinant

DNA technology has replaced pituitary-derived bST

in research with cows. Since that time, the quantity

and scope of the research with bST has increased

exponentially.

Production Response

The impact of bST on milk production will vary

according to quality of management on individual

farms, but a reasonable expectation is that successful

adopters would experience, on average, a 12-percent

boost in production. However, the increase in output

per cow tends to be absolute (in number of pounds)

rather than proportional to normal production. Thus,

approximately the same increase in pounds of milk

produced might be expected (in comparably managed herds) from all cows producing 12,000 to

20,000 pounds of milk per year. Supplementation

with bST not only results in an immediate increase

in milk yield, it also reduces the normal decline in

milk yield during the lactation period.

Because bST is rapidly cleared from the bloodstream and is not stored in the body, exogenous bST

is needed every day to sustain the increase in milk

yield. This requires daily injections or use of a

prolonged release formulation of bST. Several

prolonged release formulations have been developed

and are administered by subcutaneous injection at

intervals ranging from 2 or 4 weeks.

Obtaining a milk response to bST does not require

special diets or unusual feed ingredients. Substantial

milk responses have been observed on diets ranging

from pasture to the more typical forage/concentrate

diets used in the United States. However, voluntary

intake of feed increases in bST-supplemented dairy

cows. This increase in voluntary intake occurs after

a few weeks of bST supplementation and persists

throughout the interval of bST use. It has been

consistently observed across a wide range of diets.

Poor management results in a near zero response

from bST supplement. Facets that contribute to the

quality of management (and milk response to bST)

include the herd health program, milking practices,

nutrition program, and environmental conditions.

Food Safety Considerations

Somatotropin is produced by the anterior pituitary

gland and is transported by the blood to various body

organs where it has certain biological effects. If

somatotropin is given orally it is broken down to its

constituent amino acids in the digestive process just

like any other dietary protein. Thus, somatotropin

must be injected to be biologically active.

Somatotropin is species-limited, and the biological effects of somatotropin from one species on

others varies. In order to have any biological effect,

a protein hormone first must bind to a specific

cell-surface receptor. Studies have shown conclusively that due to its unique three-dimensional

shape, bST does not elicit any of its normal

biological actions in humans even if injected.

Recombinantly derived bST products may differ

slightly from the bST produced by the pituitary

gland because in the manufacturing process a few

extra amino acids can become attached at the end of

the bST molecule. The number of extra amino acids

varies from one to eight depending on the particular

manufacturing process. Some manufacturing processes produce no additional amino acids. The

additional amino acids that may be produced do not

change the three-dimensional shape of the active

part of the molecule and, hence, do not alter the

biological activity of bST in dairy cows or the lack

of activity of bST in humans.

Some biological actions of somatotropin in cows

may be mediated by insulin-like growth factor 1

(IGF-1). This protein hormone, a member of the

somatomedian family, normally occurs in trace

levels in milk and also in human saliva. Administration of bST to dairy cows augments IGF-1 in milk,

but the levels are still within the range typically

observed in early lactation of untreated cows.

Similar to results with bST, studies with laboratory

animal models have demonstrated that IGF-1 has no

biological activity if administered orally. The importance of increased amounts of IGF-I in milk from

bST-treated animals is uncertain. However, the

amount of IGF-I ingested in 1 liter of milk approximates the amount of IGF-I in saliva swallowed daily

by adults.
Chapter I--Summary ● 5

Effect on Milk and Meat Composition

The overall composition of milk (fat, protein, and

lactose content) and meat is not substantially altered

by bST supplementation. There can be minor

changes, primarily in fat content of milk during the

first few weeks of bST supplementation as the cow’s

metabolism and voluntary feed intake adjust. However, these changes are temporary and within the

standard variation that occurs naturally during a

lactation cycle. The meat derived from treated cows

has a lower fat content but is otherwise identical.

In manufacturing characteristics, milk from bSTsupplemented cows does not differ from the milk of

untreated cows. Characteristics that have been

evaluated include freezing point, pH, alcohol stability, thermal properties, susceptibility to oxidation,

and sensory characteristics, including flavor. Similarly, no differences were observed in cheesemaking

properties, including starter culture growth, coagulation, and acidification or in the yield, composition,

or sensory properties of various cheeses.

Effects on Bovine Reproductive Performance

Of special interest are bST effects on reproductive

variables such as conception rate (services per

conception), pregnancy rate (proportion of cows

becoming pregnant), and days open (days from

parturition to conception). As expected, cows administered bST show decreased pregnancy rates and

increased days open; these changes are associated

with increases in milk yield and occur regardless of

whether or not the high milk yields are achieved

using bST. The management of the reproduction

cycle may need to be adjusted to account for these

physiological changes. Conception rate is unchanged

by bST supplementation.

Effect on Bovine Health and Stress

Catastrophic effects such as the incidence of

ketosis (underproduction of glucose), fatty liver,

crippling lameness, milk fever (feverish disorder

following parturition), mastitis (inflammation of the

udder), sickness, suffering, and death have been

postulated to occur with bST. However, no such

effects have been observed with bST-supplementation of dairy cows in any scientifically valid

published studies, nor have subtler health effects

been in evidence. From the hundreds of investigations with bST, no study reported the lower milk

yield and decreased productive efficiency likely to

be associated with increased sickness and suffering.

Relevant studies include short- and long-term research and both chronic and acute toxicity studies. In

acute toxicity studies, dairy cows were given 30,000

mg of bST over a 2-week period, an amount of bST

approximately equaling what would be administered

in four lactation cycles.

Reduced resistance to infections has not been

found to occur in bST supplemented dairy cows

although such an effect has also been postulated.

Indeed, basic biological studies have demonstrated

that rather than reducing resistance to infection,

somatotropin plays a key role in several aspects of

maintaining immune competence.

Animal stress is more difficult to evaluate than

disease, but several indices exist that demonstrate no

stress effects due to bST supplementation. Dairy

cows would be expected to produce less milk and to

be less efficient if they are stressed. Several hundred

studies utilizing bST demonstrate increased milk

yield and productive efficiency. Studies have also

clearly demonstrated that bST has no effect on the

energy expended (as heat) for maintenance or for

efficiency of milk synthesis.

Commercial Introduction

The FDA must approve bST before it can be sold

legally in the United States. Each company seeking

FDA approval to market bST must demonstrate that

its product is effective (does what the company

claims) and safe. The safety evaluation involves

three areas:

1. safety of the animal-food products for humans,

2. safety of the bST-supplement to the target

animals, and

3. safety of using bST in the environment.

In addition, FDA requires that each company prove

that its manufacturing process can produce bST to

consistent and acceptable quality standards.

FDA has determined that sufficient scientific

information exists to indicate that the milk and meat

from bST-supplemented cows is safe for human

consumption, and has allowed for these animal

products to be marketed from the test herds during

the remainder of the investigational period.

In addition to the United States, many countries

are reviewing bST for commercial use. In all

countries where bST studies are being conducted,
6 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

the appropriate regulatory agencies have completed

the human safety evaluations and without exception,

have found it safe for human consumption.

Product Labeling

Some States are considering requiring all food

products derived from the milk of bST-supplemented cows to be labeled as such in the marketplace. The basis for labeling seems to relate to a

concern about the safety of the products for human

consumption. At least two considerations need to be

addressed.

First, is the scientific merit or basis for labeling.

If there is a valid safety concern, then the food

should not be marketed for human consumption.

Labeling is not the appropriate method for handling

a food safety concern. If the regulatory system to

evaluate food safety is inadequate, then the system

should be changed. Labeling does not excuse the

inadequacy.

The second consideration is verification. An

effective labeling program requires development

and adoption of appropriate regulations and the

establishment and funding of a system for implementation and verification. In the case of bST, no

known test or technology exist that could be used to

distinguish milk from bST-supplemented cows from

milk from non-treated cows. Indeed, no change in

milk composition as a result of bST supplementation

was found in FDA human safety evaluations.

OTHER EMERGING

TECHNOLOGIES

There are a number of emerging technologies that

will have a significant influence on the dairy

industry in the 1990s in addition to bST. Advances

in animal reproduction, animal health, and food

processing are occurring, and many of the new

technologies being developed use highly sophisticated and complex biotechnology methods. By

comparison, the biotechnology methods used to

produce bST are rather rudimentary; potentially

some of these new technologies could make bST

obsolete.

Animal reproduction technologies are advancing

rapidly. Researchers have significantly improved

their understanding of egg development in the ovary,

how to stimulate the release of numerous eggs at

once, and how to enhance the development and

fertilization of eggs outside of the cow. Embryos can

be frozen for later use. Both embryos and sperm can

be sexed. It is possible to create multiple copies of

an embryo, each of which can be transplanted into a

cow whose reproductive cycle has been adjusted to

be able to accept the embryo and carry it to term.

These new technologies make it possible to improve

herd quality more rapidly than can be achieved using

traditional breeding methods.

It is possible to create transgenic cattle,2 however,

the techniques currently used are inefficient and

require the use of thousands of eggs to produce one

transgenic animal. These inefficiencies make it too

expensive to produce and market transgenic livestock commercially. However, scientific breakthroughs are leading to the development of technologies that will improve the efficiency of transgenic

animal production and substantially lower the cost

of doing so. Transgenic livestock may become

commercially available in small numbers by the end

of the decade.

BST potentially could be supplanted by the

development of transgenic cattle. Dairy cows can be

developed to produce higher levels of bST so that

daily injections or timed release formulations are no

longer needed. Alternatively, genes that code for

chemicals that suppress bST production can be

altered in the cow such that a cow’s normal bST

production will increase.

New biotechnology products are also being developed to improve animal health. Products include new

vaccines and diagnostic kits, as well as compounds

that enhance an animal’s ability to fight disease.

Not only are new biotechnology products being

developed for use in livestock production, but they

are also being developed for use in food processing.

New products will improve the production of milk

products such as cheese and yogurt. They can also be

used to detect milk contaminants.

Effective use of these new technologies will place

a premium on management skills. New information

technologies are being developed to aid farm management. These new technologies can incorporate

2Anim~5 whose her~it~ DNA hm been augmented by the addition of DNA from a source other than parental germplasm using recombinant DNA

techniques.
Chapter 1--Summary ● 7

individual farm data, with pertinent information

from national databases, into computer programs

that will aid farmers in the decisionmaking process.

These new technologies are in various stages of

development. Some, such as embryo transfer, recombinant DNA vaccines, and information technologies are already available commercially or will be

soon. Other technologies, such as transgenic cattle

and advanced reproductive technologies, will not be

available until the end of the decade. The collective

effect these emerging technologies, including bST,

will have on the economic and policy environment

of the 1990s is examined next.

ECONOMIC AND POLICY

IMPACTS

Dairy Industry Trends

Before discussing the economic and policy impacts that emerging technologies discussed above

have on the dairy industry, it is important to consider

the major economic trends already at work within

the industry. Milk output per cow has been increasing at a very steady rate for many years. Output per

cow has grown more rapidly than milk consumption

per capita, resulting in a gradual trend toward

reduced cow numbers.

Changes in output per cow vary regionally. The

Pacific region’s output per cow has been about 30

percent higher than the national average and 50

percent higher than that of the lowest producing

region. Climatic conditions contribute to some of

these differences, but the main factors seem to be

related to progressiveness, philosophy, and quality

of management demonstrated by different dairy

farmers. These factors directly impact technology

adoption and the size of dairy farms. Generally,

larger dairy farms experience lower production

costs. The Pacific Coast and Florida lead the Nation

with herd sizes in the 500- to 1,500-cow range. The

traditional milk producing regions of the Upper

Midwest and Northeast are typically in the 50- to

150-cow range.

There is a corresponding variation in regional

profits. The Pacific and Southeast regions realized

favorable returns in 1988 ($1.05 per cwt and $1.94

per cwt. respectively) whereas the Upper Midwest

and Corn Belt regions had negative returns (–$0.62

per cwt and –$0. 18 per cwt, respectively). Returns in

the early months of 1991, however, are less favorable in all regions. Farm milk prices have declined

significantly from January through March and are

expected to fall by 15 to 20 percent for the year

compared to 1990. Dairy farms in the traditional

milk producing regions are expected to lose considerable equity under these conditions. Pacific and

Southeast farms, although still profitable, are expected to operate much closer to their respective

break-even points.

These differences have led to shifts in production

patterns. The largest increases in milk production

have been in the Pacific region where marketing

have risen by nearly 40 percent. The traditional

Upper Midwest and Northeast regions have each

increased milk production about 5 percent. These

traditional regions produce about half of the Nation’s milk supply and will continue to be a major

force in the dairy industry. But if the Upper Midwest

and Northeast regions are to maintain their roles as

the “dairy States,” major changes in scale of

operation, progressiveness in technology adoption,

philosophy, and quality of management and perhaps

dairy policy may be required.

Technology Adoption

When emerging technologies, such

come available commercially it is not

as bST, beknown with

any degree of certainty how many dairy farmers will

use them or when. Farmers have been surveyed to

project expected adoption levels once bST becomes

available. Results indicate relatively rapid adoption—

50-percent adoption within the frost year and at least

80-percent within 3 years.

However, these surveys may not be accurate

indicators of prospective adoption. Many of the bST

surveys were conducted prior to the availability of

widespread information on bST. Most other dairy

technologies, moreover, have not been adopted

rapidly. Artificial insemination technology is used

only by 70 percent of dairy farms despite being

available for some 40 years. Dairy Herd Improvement technology, available for 50 years, is used by

only 45 percent of farmers.

OTA’s statistical analysis of historical rates of

technology adoption by dairy farmers provides

another basis for predicting bST adoption. The

analysis found:
8 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

. A slower rate of adoption than suggested by

producer surveys of farmers on probable bST

use (17 percent or less the first year).

. Regional variations in rates of technology

adoption in the dairy industry. Based on this,

bST adoption after 5 years is forecast to be 40

percent in the Pacific region, where technology

adoption is most rapid, and 25 percent in the

Corn Belt. This and other traditional milk

production regions tend to be slower to adopt

new technologies.

National Impacts

The interactions of technology adoption, dairy

policy, and consumer reaction and their effects on

future milk supply prices and returns to dairy

farmers were captured using LIVESIM, a regional

and national computer simulation model.3 The

policy options analyzed included a fixed price

support, a price-support trigger, and a quota program. In all policy scenarios, the government

purchases at least 3 billion pounds of milk annually

to satisfy food-program needs (i.e.. school lunch

programs).

Fixed Price Support

This scenario frees price at the 1989 level of

$10.6O per cwt. This serves as a useful bench mark

for comparing other policy options. In this case, the

government purchases excess milk, at the support

price, in order to clear the market. Without bST, milk

production would increase from the present level of

144 billion pounds to 152 billion in 1995. With bST,

production would increase an additional 4 to 5

billion pounds over the period (see table l-l);

government purchases would rise as high as 7 and 9

billion pounds in any one year, and overall would

increase by 3 to 6 billion pounds over the minimum

purchases of 3 billion pounds for food programs (see

table 1-2).

Trigger Price Policy

This option triggers a price-support reduction

each time the level of government purchases rises

above 5 billion pounds annually. This scenario is

similar to the producer-assessment option in the

1990 farm bill because the assessment will effectively trigger reductions in producer returns through

milk price declines. Without bST, a single pricesupport reduction is triggered to a level of $10.10 per

cwt in 1991. With bST, two price-support reductions

are triggered in 1991 and another in 1993 to a level

of $9.60 per cwt. These price reductions moderate

production increases to keep government purchases

near the 3-billion-pound minimum.

Quota Policy

A quota policy is another method to manage

excess production. It establishes a level of milk

production for each farm and provides effective

disincentives to the farmer if production exceeds the

quota. This might be accomplished by a two-tiered

pricing system or some other mechanism that

provides disincentives for producing over quota

levels.

In the analysis, the quota policy was designed to

maintain government purchases at or near the

minimum government use target of 3 billion pounds.

The quota was adjusted downward any year government expenditures exceeded 3 billion pounds. The

results show that the quota avoids the high level of

government purchases that result under the fixed

price-support scenario (see table 1-2).

Demand Reduction

While claims that consuming milk and milk

products from cows supplemented with bST or other

new technologies could adversely affect human

health have not been substantiated, a range of food

safety and other considerations will affect consumer

purchases. Policy needs to be designed considering

the full range of potential consumer response;

accordingly two scenarios of reduced milk consumption were analyzed.

Small Demand Reduction-In this scenario,

per-capita demand decreases by 10 percent in 1991,

5 percent in 1992 (i.e., demand increases from 1991

to 1992), and 2.5 percent annually thereafter. Government purchases total 21.2 billion pounds in the

first year (1991), 9.7 billion in 1992, and 8.4 billion

in 1993. The support trigger decreases the pricesupport level to 9.10 per cwt in 1994. Even though

government purchases are high for 3 years, the

trigger mechanism seems to accommodate a temporary demand reduction.

Large Demand Reduction-The second demand

scenario assumes a permanent 1 O-percent annual

3A major focus of tie ~~ysis is on tie use of bST because of its effect on productivity and commercial availability ~ tie eaf~Y 1990s.
Chapter I--Summary . 9

Table l-l—Level of Milk Production, With and Without bST, Under Alternative Policy Scenarios, 1990-98

(billions of pounds)

Fixed support Trigger Quota

Year With bSTa Without bST With bSTa Without bST With bSTa Without bST

1990 . . . . . . . . . . . . . . . . . 144

1991 . . . . . . . . . . . . . . . . . 146

1992 . . . . . . . . . . . . . . . . . 146

1993 . . . . . . . . . . . . . . . . . 153

1994 . . . . . . . . . . . . . . . . . 153

1995 . . . . . . . . . . . . . . . . . 156

1996 . . . . . . . . . . . . . . . . . 157

1997 . . . . . . . . . . . . . . . . . 160

1998 . . . . . . . . . . . . . . . . . 161

144

144

143

150

149

152

153

155

157

144

146

146

153

152

156

155

159

159

144

144

143

150

148

152

153

155

157

144

146

145

148

150

152

155

157

160

144

144

144

146

148

150

153

155

157

abSTisassumed tobecommercially availablein 1991.

SOURCE: Office ofTechnology Assessmen~ 1991.

Table 1-2—Level of Government Purchases, With and Without bST, Under Alternative Policy Scenarios,

1990-98, Milk Equivalent (billions of pounds)

Fixed support Trigger Quota

With bSTa Without bST With bSTa Without bST With bSTa Without bST

1990 . . . . . . . . . . . . . . . . . 3.0

1991 . . . . . . . . . . . . . . . . . 7.3

1992 . . . . . . . . . . . . . . . . . 4.3

1993 . . . . . . . . . . . . . . . . . 9.0

1994 . . . . . . . . . . . . . . . . . 6.0

1995 . . . . . . . . . . . . . . . . . 7.0

1996 . . . . . . . . . . . . . . . . . 4.8

1997 . . . . . . . . . . . . . . . . . 5.3

1998 . . . . . . . . . . . . . . . . . 3.6

3.0

5.3

3.0

5.7

3.0

3.0

3.0

3.0

3.0

3.0

7.3

3.0

6.8

3.0

3.0

3.0

3.0

3.0

3.0

5.3

3.0

3.8

3.0

3.0

3.0

3.0

3.0

3.0

7.3

3.5

3.4

3.1

3.0

3.0

3.0

3.0

3.0

5.3

3.0

3.0

3.0

3.0

3.0

3.0

3.0

abST is assumed to be commercially available in 1991.

SOURCE: Office of Technology Assessment, 1991.

reduction in per-capita consumption. The trigger

mechanism does not easily adjust the industry under

this scenario. The support price must be lowered to

$7.60 in 1997 to bring government purchases below

4 billion pounds (see figure l-l). Such a low support

price would make it difficult (impossible) for even

the best managed dairy farms to avoid economic

losses. A quota program or termination program (a

one-time government buy-out of dairy herds) would

be needed to bring government purchases back to the

3-billion-pound minimum. However, as this study

shows, termination programs do not result in permanent reductions in supply. Quota programs can

effectively reduce supply over a period of time. But

with either program, approximately 1 million cows

would need to be slaughtered causing beef prices to

decline by 4 to 6 percent.

Conclusions

A mechanism such as the trigger price policy or

producer assessments, which allow producer returns

to decline as government purchases increase, could

effectively adjust supply without excessively large

inventory accumulations. However, if sharp reductions in demand accompany the introduction of bST,

production quotas may be required. A quota policy,

however, has some potentially harmful effects,

including:

. higher production costs,

. elimination of dynamic adjustment within the

industry,

. negative impact on beef cattle prices,

. difficulty of discontinuing, once initiated, and

. the capitalization of benefits into the quota.

Farm Level Impacts

The effects of emerging technology, dairy policies, and consumer demand can be more easily

visualized by analyzing the impacts on representative dairy farms. The farm-level impacts of the three

policy scenarios-fixed price support, trigger, and

quota---over a 10-year period were analyzed using

FLIPSIM, a farm level simulation model.
IO ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Figure l-l—Projected Impact of a 10-Percent

Permanent Demand Reduction on U.S. Government

Milk Purchases Under Alternative Dairy Policies,

1990-98

30 ;::::: :

~ 2 4 7

c ‘“

.—o m. . . . . . . . . . . . . . :

~ 18 -

al U-J

Q

x

=

o ~ ~ ; ; ~ ~ :

90 91 92 93 94 95 96 97 98

Year

— Trigger Price Fixed Support

-

- Dairy Termination Quot a

SOURCE: Office of Technology Assessment, 1991.

Adoption Incentives

Once bST becomes available, strong incentives

will exist to adopt the technology. Payoffs from bST

adoption are substantial, regardless of region (see

table 1-3). Nonadopters of bST will have more

problems surviving and will be more likely to exit

the industry. Likewise, dairy farmers located in

States that have a moratorium on adoption will be

placed at a substantial disadvantage relative to those

in States where a moratorium does not exist.

Regional Competitiveness

Several reasons for regional shifts in milk production patterns can be seen in tables 1-3 and 1-4. Upper

Midwest farms have problems realizing sufficient

earnings to achieve a reasonable return on equity,

compete, and survive. While Northeast farms perform better, they too were found to be at a

disadvantage relative to Pacific and Southeast farms.

In all regions, adoption of bST increases the

potential to survive, especially for larger farms.

Policy Impacts

The fixed price-support policy, with its higher

earnings, increases the probability of farm survival

and the chances of earning a 5-percent return on

initial equity (see table 1-5). While Upper Midwest

dairies are able to maintain cash flow, net worth

continues to erode on the 125-cow Upper Midwest

dairy due to the relatively high investments in fixed

assets (buildings, equipment, etc.).

From the producer standpoint, the quota program

does not perform as well as the trigger price or freed

price-support programs. This is because the quota

price objective is the same as the fixed price support

($10.60) and because restrictions on output curb

expansion and raise production costs. To maintain

dairy farm income under a quota system, the price

objective must be sufficiently high to offset the

effects of lower production—and this will result in

higher prices to consumers.

The economic payoff from bST adoption is about

the same for a trigger price policy and a freed

price-support policy. However, all the representative

farms experienced at least a 20- to 40-percent

decrease in economic payoff under a quota compared to the trigger price policy. Adoption of bST

would be slowed by imposing a quota as opposed to

the trigger price policy.

Even with reduced demand, strong incentives

would exist f-or all farms in all regions to adopt bST.

With the continuation of the current trigger policy,

a 52-cow Upper Midwest dairy’s probability of

survival declines under a small decrease in demand,

but is relatively enhanced by adopting bST (see table

1-6). The same is true for the larger dairies. If a major

decrease in demand occurs, small and large dairy

farms in the Upper Midwest will be most vulnerable.

Increased Pressure on Traditional Farms

A major controversy concerning bST is that it will

force many dairy farms out of the industry, especially in traditional milk-producing regions. BST

alone, however, will not force these traditional farms

out of existence. As discussed earlier, the trend

toward fewer total cows and larger farms has been

underway for many decades. This trend is a result of

the combination of emerging technology, industry

economics, and policy. The trend will no doubt

accelerate in the 1990s as the result of the combination of bST and other cost-reducing technologies

and a more market-oriented dairy policy. As has

been the case for years, such changes inherently puts

increased pressure on traditional dairy farms. These

pressures are not new, although they are accentuated

by technological change.

If policymakers decide to change or at least slow

this trend toward fewer but larger farms, changes in

policy will be needed. First, to reduce the magnitude
Table l-3—impacts of bST Adoption on the Economic Viability of Moderate-Size Representative Farms, Assuming No Change

in Demand for Milk Due to bST, Trigger Price Policy, by Region, 1989-98 (in percent)

52-cow 52-cow 350-COW 200-COW

Upper Midwest Northeast Southwest Southeast

Non- bST Non- bST Non- bST Non- bST

Measure of impact adopter adopter adopter adopter adopter adopter adopter adopter

Probability of survivala . . . . . . . . . . . . . . . . . . . . . . 58% 74% 10070 100% —950/0 97% 100% 100%

Probability of earning 5-percent return

on equity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 74 100 100 95 97 100 100

Probability of increasing equityb . . . . . . . . . . . . . . . 0 0 3 3 60 79 13 24

Present value of ending net worth as percent

of beginning net worthc 

. . . . . . . . . . . . . . . . . . . . 16 29 72 77 109 128 76 89

%hance that the individual farm will remain solvent through 1998, i.e., maintain more than a 10-percent equity in the farm.

bchance that the individual farm wilt increase its net worth in real 1989 dollars through 1998.

cPresent value of ending net worth divided by initial net worth indicates whether the farm increased (decreased) net worth in real dollars.

SOURCE: Office of Technology Assessment, 1991.

Table l-4—impacts of bST Adoption on the Economic Viability of Large Representative Farms, Assuming No Change in Demand for Milk

Due to bST, Trigger Price Policy, by Region, 1989-98 (in percent)

125-cow 200-COW 1 ,500-cow 1 ,500-COW

Upper Midwest Northeast Pacific Southeast

Non- bST Non- bST Non- bST Non- bST

Measure of impact adopter adopter adopter adopter adopter adopter adopter adopter

Probability of survivala . . . . . . . . . . . . . . . . . . . . 9570 99% 100% 100?40 10070 100?40 100% 1 00%

Probability of earning 5-percent return

on equity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 95 99 100 100 100 100 100

Probability of increasing equityb . . . . . . . . . . . . . . . 8 12 43 53 100 100 88 99

Present value of ending net worth as percent

of beginning net worthc 

. . . . . . . . . . . . . . . . . . . . 57 69 92 102 195 214 129 147

Whance that the individual farm will remain solvent through 1998, i.e., maintain more than a 10-percent equity in the farm.

bchance that the individual farm will increase its net worth in real 1989 dollars through 1998.

cPresent value of ending net worth divided by initial net worth indicates whether the farm increased (decreased) net worth in real dollars.

SOURCE: Office of Technology Assessment. 1991.
12 . U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Table l-5—impacts of bST Adoption on the Economic Viability of Representative Large (1 25-cow)

Upper Midwest Farms Under Alternative Dairy Policies, Assuming No Change

in Demand for Milk, 1989-98 (in percent)

Trigger price Fixed price support Quota

Non- bST Non- bST Non- bST

Measure of impact adopter adopter adopter adopter adopter adopter

Probability of survivala. . . . . . . . . . . . . . . . . 95% 99% 99% 100% 85% 920/.

Probability y of earning 5-percent

return on equity . . . . . . . . . . . . . . . . . . . . 90 95 95 98 67 78

Probability of increasing equityb

. . . . . . . . . . 8 12 11 18 2 3

Present value of ending net worth as

percent of beginning net worthc . . . . . . . . 57 69 67 78 37 46

%hance that the individual farm will remain solvent through 1998, i.e., maintain more than a 10-percent equity in the farm.

bchance that the individual farm will increase its net worth in real 1989 dollars through 1998.

cPresent value of ending net worth divided by initial net worth indicates whether the farm increased (decreased) net worth in real dollars.

SOURCE: Office of Technology Assessment, 1991.

of adjustment the rate of technology adoption by

traditional farms would need to be increased. This

would require additional expenditures on public

research and extension with the specific goal of

enhancing the survivability of these farms. During

times of rapid technological change, research and

technology adoption strategies for traditional farms

need to be developed and implemented by USDA,

land-grant universities, and dairy cooperatives if

these farms are to survive.

Second, dairy policy may need to change back to

a fixed price-support policy. As seen in the previous

analysis, a fixed support policy enhances the traditional farm’s probability of survival compared to

other policies. It is, however, significantly more

costly to the government than current policy.

It is possible to at least slow the trend toward

fewer total cows and larger dairy farms. However,

such change may be costly. As noted, to keep less

progressive traditional farms in the industry will

require increased expenditures for research and

extension to improve technology adoption and

increased funds to support the price of milk at a level

that will allow these farms to compete. Policymakers

will need to weigh the benefits of traditional farms

with these costs in determining the policy path to

follow in the 1990s. This is particularly the case for

dairy farms outside the areas with a comparative

advantage in dairying where a large share of feed

supplies are purchased.

Science Policy and Emerging Technology

The controversy surrounding biotechnology—

including bST—raises questions concerning what

social needs are being met by these technologies and

the appropriateness of public sector investment in

their development. The questions raised point to the

need for broadbased, ex ante information concerning

new technologies. Presently, little information about

new technologies is available prior to commercialization. There is no institution within the agricultural

science policy community that develops information

on the benefits and risks of any technology ex ante.

There also is no formal structure that provides input

to decisionmakers from all affected parties (farmers,

marketers, researchers, consumers, etc.). Thus there

is no comprehensive information about the benefits

and risks of a new technology prior to commercialization and, therefore, no inclusive criteria to

determine how public research resources should be

allocated.

The development of an institutional framework to

provide and act on such information is needed. Had

such an institution been in existence a decade ago, it

is possible that the bST controversy could have been

avoided or minimized. Consideration of the costs

and benefits of new technologies and input from a

wider range of clientele could lead decisionmakers

to consciously choose a different allocation of public

sector research funding than that which occurs in the

absence of such information.

Clearly, all benefits and risks of new technology

development cannot be determined a priori, and

overcentralization of research decisionmaking raises

legitimate concerns. Care must be taken in establishing such an institution. However, a broad based

discussion of issues involving all relevant users of

new technologies can point to potential problems,

determin e further research needs, and provide information about the relative social benefits to be gained
Table l-6—impacts of bST Adoption on the Economic Viability of Moderate-Size Representative Farms, Assuming Small Decrease in

Demand for Milk Due to bST, Trigger Price Policy, by Region, 1989-98 (in percent)

52-cow 52-cow 350-COW 200-cow

Upper Midwest Northeast Southwest Southeast

Non- bST Non- bST Non- bST Non- bST

Measure of impact adopter adopter adopter adopter adopter adopter adopter adopter

Probability of survivala . . . . . . . . . . . . . . . . . . . . . . 40% 480/0 1009!0 1009!0 88% 94% 99% 100%

Probability of earning 5-percent return

on equity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 48 100 99 88 94 89 94

Probability of increasing equityb . . . . . . . . . . . . . . . 0 0 1 2 35 51 4 9

Present value of ending net worth as percent

of beginning net worthc . . . . . . . . . . . . . . . . . . . . 3 10 65 70 79 99 58 71

Whance that the individual farm will remain solvent through 1998, i.e., maintain more than a 10-percent equity in the farm.

bchance that the individual farm will increase its net worth in real 1989 dollars through 1998.

cPresent value of ending net worth divided by initial net worth indicates whether the farm increased (decreased) net worth in real dollars.

SOURCE: Office of Technology Assessment, 1991.
14 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

by investments in competing technologies. The

seeds of such a framework can be found in the first

report of this series, Agricultural Research and

Technology Transfer Policies for the 1990s. Congress has subsequently taken the first step by

authorizing an Agricultural Science and Technology

Review Board in the 1990 farm bill that will begin

to develop ex ante information on selected technologies. It is a beginning, but much more work will be

needed in the future.

CONCLUSIONS

Emerging technologies, such as bST, industry

economics, and public policy will play critical roles

in shaping the U.S. dairy industry in the decade of

the 90s, Advances in health, reproduction, and

information technology all will affect the industry.

The most dramatic impact will be due to bST.

Claims have been made that bST is unsafe in

consumer food products, an unsafe technology for

cows, and a technology that will economically

destroy many traditional farms. This report concludes just the opposite. It is a technology that, based

on today’s research findings, poses no additional

risk to consumers, one that does not produce adverse

health effects to cows, and one that alone will not

economically disadvantage the traditional farm operator. Emerging technologies (including bST),

industry economics, and current dairy policy will

merely accelerate an existing trend-the pressure on

traditional farms to grow or exit the industry.

Changes in: rate of technology adoption, research

and extension policy, and perhaps dairy policy may

be required to reverse this trend.

A national dairy policy that provides a mechanism

for allowing producer returns to decline as government purchases increase, such as the trigger pricesupport policy or producer assessments as provided

for in the 1990 farm bill, could effectively adjust

supply without excessively large inventory accumulations. However, if demand for dairy products

declines sharply with the introduction of bST,

supply-management programs such as production

quotas or termination programs may be required,

Termination programs are costly and do not effectively reduce supply over a period of time. Production quotas can effectively control supply. However,

they also freeze regional production shifts and

(because the quota has an economic value) make it

more costly for new entrants into the industry.

Because of costs and rigidities associated with quota

programs, consideration might be given to observing

government purchases over a 2-year, as opposed to

a l-year, period before implementing such a program. This would permit a more accurate assessment

of whether the demand reduction is temporary or

permanent.

The introduction of bST has caused considerable

controversy. Little, if any, information was available

early in its development to foresee the biological,

economic, social, and political impacts of its potential adoption. Lack of such information establishes

a clear need to consider the benefits and risks of new

technology more seriously and to use that information in allocation of public sector research funds. An

institutional framework needs to be developed to

provide this information and involve all the relevant

users of new technology.
Chapter 2

Overview of the Dairy Industry
Contents

Page

FORCES DRIVING THE INDUSTRY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Technological Change +... . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . .. . . . . . . . . . . . . . . . . . 17

Economies of Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18

Costs of production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18

Dairy Receipts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Net Income . . . . . . . . . . . . . .. .. +. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Regional Production Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Demand Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

MAJOR DAIRY POLICY ISSUES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ,.,. 23

Butterfat Surplus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ,. . . . . . . . . . . . ● . . . . . . . . 23

Milk Price Support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Price Instability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Milk Production Controls . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Federal Milk Marketing Orders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Basic Formula Price . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...,*. 28

Emerging Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

CHAPTER 2 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . 29

Figures

Figure Page

2-1. Annual Milk Outputter COW, 1965-89 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

2-2. Average Number of Milk Cows on Farms and Total Milk Production, 1980-89 . . . 17

2-3. USDA Farm Production Regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

2-4. Milk Outputter Cow by Region, 1989 . . . . . . . . . . .,...,. . . . . . . . . . . . . . . . . . . . . . . 19

2-5. Milk Production Costs Related to Herd Size, for 10 States, 1985 . . . . . . . . . . . . . . . . 20

2-6. Regional Differences in Costs of Producing Milk, 1988 . . . . . . . . . . . . . . . . . . . . . . . . 21

2-7. Regional Differences in Receipts From Dairy Farm Sales, 1988, ....,..,..,,.. 22

2-8. Regional Differences in Net Income (profit), 1988 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

2-9. Change in Milk Production by Region, 1980-89 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24

2-10. Share of Milk Production by Region, 1989 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .,. 25

2-11. Change in Share of Milk Production by Region, 1980-89 .. .. .. .. .. ... .,. ....,. 26

2-12+ Actual and Projected Consumption of Lowfat Milk, 1950-93 . . . . . . . . . . . . . . . . . . . 27

2-13. Market Share of Lowfat Milk as a Percent of Total Fluid Milk Consumption ...,. 27

2-14. Actual and Projected Consumption of American Cheese, 1950-93 . . . . . . . . . . . . . . . 27

2-15. Actual and Projected Consumption of Other Cheese . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

2-16. Uncommitted Government Dairy Product Inventories, 1985-90 . . . . . . . . . . . . . . . . . . 28

2-17. Minnesota-Wisconsin (M-W) Price and Milk Price-Support Level,

January 1987 to April 1990 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . 28
Chapter 2

Overview of the Dairy Industry

The dairy industry is large, dynamic, and driven

by a number of forces. Dairy products account for

about 13 percent of total cash receipts from all farm

commodities. In 1989, cash receipts from dairy

products totaled $19.3 billion; only cattle and calves

brought greater returns. Although milk is produced

and processed in every State, two-thirds of the total

1989 milk supply was produced in 10 States (l). At

least half of the total 1989 U.S. milk production

came from Wisconsin, California, New York, Minnesota, and Pennsylvania.

A central feature of the dairy industry is the

relatively constant 1.5 to 2.0 percent annual increase

in output per cow (see figure 2-l). Exceptions have

occurred only after major weather disruptions (leading to sharp increases in feed prices in the early

1970s and in 1989) and with changes in government

policy (namely, the 1983-84 milk diversion program). This chapter describes the supply, demand,

and regulatory forces driving the industry and the

resulting policy issues for the 1990s.

FORCES DRIVING THE

INDUSTRY

Technological Change

Increases in milk output per cow have not come

automatically; they reflect the continuous adoption

by farmers of artificial insemination, Dairy Herd

Improvement Association (DHIA) recordkeeping,

Figure 2-l—Annual Milk Output Per Cow, 1965-89

15,000

11,250

3

$

g 7,500 —

3,750

0

1965 1970 1975 1980

l-l

1985 1989

Year

SOURCE: U.S. Department of Agriculture, Economic Research Service,

Dairy Situation and Outlook Report, various years, 1965-1990.

three-times-a-day milking, automated feeding, forage testing, and other technologies that periodically

enter the market as products of public- and privatesector research and development. Productivity has

also risen because of constant improvement in the

quality of management, which in turn partially

reflects improved packaging of technology to increase output per cow.

With milk consumption per capita growing less

rapidly than output per cow, there has been a gradual

national trend toward reduced cow numbers (see

figure 2-2). This trend was interrupted in the early

1980s by government policy that supported the price

of milk at 80 percent of parity in the face of declining

feed prices.

The U.S. Department of Agriculture (USDA), in

reporting production statistics, divides the United

States into 10 farm-production regions (see figure

2-3). Changes in output per cow have not been

uniform nationally (see figure 2-4). For example,

USDA’s Pacific region had a milk output per cow of

18,389 pounds in 1988, whereas the U.S. average

was 29 percent lower (14,213 pounds). The Pacific

region’s output per cow is 51 percent higher than

that of the Appalachian region. While climatic

conditions contribute to some of these differences,

the main factors seem to be progressiveness, philosophy, and quality of management—factors that also

are believed most directly to impact the adoption of

Figure 2-2—Average Number of Milk Cows on Farms

and Total-Milk Production, 1980-89

,., .

,, .,,.

. . .

.’

“.

10 ~ 1 0 0

1965 1970 1975 1980 1985 1989

Year

— Milk cows ... , Milk production

SOURCE: U.S. Department of Agriculture, Economic Research Service,

Dairy Situation and Outlook Report, various years, 1965-1990.

–17–
18 ● (U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Figure 2-3—USDA Farm Production Regions

r )

WA

- -

r

MN

1 .

““ liiii’1

PA

n

● Pacific Region

includes Alaska and Ha

K - M ( -

Southern Plains

SOURCE: U.S. Department of Agriculture, Economic Research Service, 1990.

technologies. These factors in turn are related to the

availability of extension education services, consultants, and the infrastructure of input and technology

suppliers. Success in technology adoption will be

one of the major factors determining future milk

production patterns. Other major factors impacting

these patterns include dairy policies, environmental

policies, water availability, population pressures,

climate, and resource availability.

Economies of Size

Larger dairy farms, as a general rule, experience

lower per-unit production costs. Studies currently in

progress suggest that in traditional milk production

regions, such as the Upper Midwest and the Northeast, economies of size (reduced per-unit production

costs associated with increased farm size) have led

to the establishment of several larger size dairy

operations. And current research suggests that these

dairy operations have the potential to realize even

larger economies of size.

ind q

Statek

Southeast LA

FL

Regional differences in dairy herd size are associated with different economies of size (see figure

2-5). The Pacific coast and Florida lead the Nation

with herd sizes typically in the 500- to 1,500-cow

range and enjoy the lowest production costs per unit

output. In traditional milk production regions of the

Upper Midwest and Northeast, dairies are typically

in the 50-to 150-cow range, and production costs are

relatively high.

Costs of Production

Substantial regional differences in costs of producing milk reflect regional differences in output per

cow as well as in herd sizel (see figure 2-6). The

Economic Research Service/USDA has estimated

the cash costs and total economic costs of production

since 1974. Cash costs depend primarily on the share

l~e USDA cost of production I@OnS & not include the same States as the production regions indicated in figure 2-3. With minor exceptions, tie

Upper Midwest cost of production region is equivalent to the Lake States production region.
Chapter 2----Overview of the Dairy Industry ● 19

Figure 2-4—Milk Output Per Cow by Region, 1989

20,000

15,000

5,000

0

LS NE

Key: LS - Lake States

NE - Northeast

PA - Pacific

SOURCE: U.S. Department of Agriculture,

of inputs purchased and milk

PA MT SP NP SE DL CB AP us

Region

MT - Mountain SE - Southeast AP - Appalachian

SP - Southern Plains DL - Delta States US - United States

NP - Northern Plains CB - Corn Belt (national average)

Economic Research Service, 1990.

output per cow.2 For moderate cash cost of $9.07 per cwt. Regions that

example, in the Southeast, where dairies purchase grow much of their feed have the lowest cash costs.

most of their feed inputs (about 50 percent of

production costs) and where average output per cow The level of cash costs is significant from a policy

is low (12,604 pounds, see figure 2-4), the cash cost perspective. Farmers who are not covering cash

averaged $11.63 per hundredweight (cwt) (see fig- costs have strong economic incentives to shut down

ure 2-6). Dairies in the Pacific region also purchase their operations. They are either building debt or

a high percentage of their inputs but have the highest eroding equity on virtually a daily basis. Not

output per cow (17,527 pounds), thus yielding a surprisingly, farmers in high-cash-cost regions likely

Wash costs reflect the minimum break-even prices needed to produce in the short run. Subtracting cash costs from the gross value of production leaves

net cash available before replacement of depreciable assets. It excludes income taxes and principal payments.
20 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Figure 2-5—Milk Production Costs Related to

Herd Size, for 10 States, 1985

20

18 \\

17

16 I FL

WA /

\

ID

o 200 400 600 800 1,0001,2001,400

Herd size (adult cows)

SOURCE: Office of Technology Assessment, 1991.

are the first to complain about milk prices being too

low.

Total economic costs include all fixed and cash

costs of production.3 Fixed costs are highest in

regions that grow a large percentage of their feed,

have substantial investments in housing and feed

storage (silos), and/or are expanding rapidly (meaning high depreciation costs). Thus, while the Upper

Midwest and Northeast regions have among the

lowest cash costs, they have relatively high total

economic costs due to their large housing and

feed-storage investments.

Total economic costs are meaningful from a

policy perspective because they influence the longrun economic viability of a region. If these as well

as cash costs are not offset by high milk prices,

farmers will have no incentive to invest. This is the

case in the Upper Midwest and Corn Belt regions

where the dairy industry is in relative economic

stagnation and even decline.

Dairy Receipts

Dairies obtain most of their receipts from milk

(about 90 percent) and from the sale of cows (no

more than 10 percent). The price of milk is

determined nationally and regionally by the interaction of government policy, consumer demand, and

the supply of milk. Government dairy programs

include the Federal and State milk marketing order

programs and the Federal dairy price support program.

The milk marketing order programs regulate the

price of milk eligible for fluid consumption: processors are required to pay minimum class prices based

on how the milk is used. The lowest prices are for

Class III uses (milk used to manufacture butter,

cheese, and nonfat dry milk). Milk used for soft

products (ice cream and yogurt) receives a slightly

higher Class II minimum price, and milk used for

fluid consumption receives a substantially higher

Class I minimum price. Dairy producers receive the

average (blend) of the three class prices weighted by

the share of milk used in each class. Class II and III

minimum prices are fixed at the average of the

market prices paid by manufacturers in Wisconsin

and Minnesota. Class I prices are determined by th e

Minnesota-Wisconsin prices plus a differential that

increases with increasing distance from Eau Claire,

WI. Thus, Federal milk marketing order Class I

(fluid use) prices increase from the Upper Midwest

to the South and East.

The Federal Government purchases cheese, butter, and nonfat dry milk in quantities sufficient to

maintain market price at a minimum level, established by the Federal price support program. Reductions in the price of milk may occur for several

reasons: because the government lowers the price

support, because the share of milk used for fluid

purposes in a marketing order declines (due to an

increase in supply or a fall in demand), or because

premiums over minimum order prices (based on

supply and demand conditions) paid by processors

decline.

This combination of government-administered

and market-determined price relationships is important because it has a marked impact on the regional

distribution of milk receipts (see figure 2-7). Receipts are highest in the Southeast (14.87 per cwt)

and lowest on the Pacific coast (11.13 per cwt). The

Upper Midwest has slightly higher milk receipts

($11 .92 per cwt) than the Pacific region.

Net Income

Profits vary regionally with receipts and costs.

The combination of high costs and low prices in the

Upper Midwest in 1988 led to a negative cash

income (–$0. 11 per cwt) and an even lower return to

management (–$0.62 per cwt) (see figure 2-8).4 The

sTot~ economic costs do not include a return to management.

Wash income is the difference betvveen gross value of production and cash expenses and capital replacement.
Chapter 2-----Overview of the Dairy Industry ● 21

Figure 2-6—Regional Differences in Costs of Producing Milk, 1988

UM NE PA SP SE CB AP

= Cas h = Total economi c

Key: UM - Upper Midwest PA - Pacific CB - Corn Belt

NE - Northeast SP - South Plains AP - Appalachia

SE - Southeast

SOURCE: U.S. Department of Agriculture, Economic Research Service, Economic Indicators of the Farm Sector, 1989.

Corn Belt also experienced a loss in returns to

management (of $0.27 per cwt). The highest return

regions were the Southeast and Appalachia. Despite

high costs, the Southeast realized higher returns due

to favorable treatment under the Federal milk

marketing order system. The Pacific region realized

a favorable return despite having the lowest receipts.

This reflects the overall efficiency of relatively

industrialized production on the west coast.

The income situation improved for dairy farms in

the traditional milk producing regions in 1989 and

1990 when farm milk prices increased. These farms

experienced positive returns in those years. However, in the early months of 1991 prices declined

significantly and are expected to fall by 15 to 20

percent for the year compared to 1990. Dairy farms

in the traditional milk producing regions are expected to lose equity under these conditions. Farms

in the nontraditional areas, such as the Pacific

region, are expected to operate much closer to their

break-even point.

Regional Production Changes

Sustained regional differences in profit lead to

shifts in the geography of production. The largest

increases in milk production have been in the West

and Southwest, where marketing have risen by

nearly 40 percent since 1980 (see figure 2-9). Milk

production in the traditional dairy areas of the Lake

States and Northeast has increased by 6.5 and 4.0

percent, respectively. The Corn Belt, which consistently has had the lowest net returns, experienced a

production increase of only 4.9 percent.

However, no region is homogeneous. During the

1980s, for example, centers of rapidly increasing

production developed within regions (i.e., central

Texas and southern Georgia). In the late 1980s,

persistent production declines occurred in Minne-
22 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Figure 2-7—RegionaI Differences in Receipts From Dairy Farm Sales, 1988

16.14

Paoific South Plains Appalachian Upper Midwest Corn Belt Southeast Northeast

Region

m cows = Tota l

SOURCE: U.S. Department of Agriculture, Economic Research Service, Dairy Situation and Outlook Report, 1989.

sota—traditionally one of the largest dairy States,

Because of the higher cost conditions associated

with smaller dairies (see figure 2-5), and low profits

(see figure 2-8), significant sections of the Lake

States may have lost its comparative advantage to

other regions. Questions arise as to whether traditional Federal order pricing institutions, which rely

on Minnesota and Wisconsin as the base point for

pricing milk (the M-W price), are appropriate in

today’s milk industry. The answers to these questions are complex and merit further study and debate

(2, 3).

While the national share of milk production in the

Lake States and the Northeast has declined by at

least 2 percent since 1980, these two regions still

produced almost half of the Nation’s milk supply in

1989 (see figures 2-10 and 2-1 1). If these regions are

to maintain their role as “dairy States, ” major

changes in scale of operation, levels of technology

adoption, support for dairy research and extension,

and, perhaps, dairy policy may be required.

Demand Changes

Changes in demand may be as important as

changes in supply in determining the future course

of the dairy industry. Shifts in population toward the

West and South have favored increased milk production in these regions.

There have also been major changes in demand

for individual dairy products, such as sharply

reduced butter consumption, increased lowfat (2.0

percent butterfat or less) milk consumption (see

figures 2-12 and 2-13), and increased cheese consumption. The shifts from whole milk to lowfat milk

and the rapidly rising cheese consumption have been

particularly dramatic. The trend away from consuming whole milk likely reflects increasing consumer

concerns about calories, fat, and cholesterol consumption.

Cheese is overwhelmingly the bright spot in terms

of dairy product demand. While American-style

cheeses (predominantly cheddar) have experienced

substantial growth (see figure 2-14), the demand for
Chapter 2-Overview of the Dairy Industry ● 23

Figure 2-8—Regional Differences in Net Income (profit), 1988

3

2

g ,

&

o

-1

.

Upper ’Midwest Northeast Pacific South Plains Southeast

I

Corn ‘Belt Appalachian

~ Cas h m Managemen t

SOURCE: U.S. Department of Agriculture, Economic Research Service, Dairy Situation and Ouf/ook Report, 1989.

other cheeses (predominantly Italian-style) has grown

even more rapidly and consistently (see figure 2-15).

Italian-style cheese demand is largely a result of the

rapidly growing convenience and fast food (pizza)

market. Therefore, cheeses have capitalized on

consumer trends toward microwave convenience

and eating out. Other dairy products have not benefited as much from these changing market trends.

MAJOR DAIRY POLICY ISSUES

The milk industry may well be the most highly

regulated of any in the United States. A complex

system of health, food safety, and labeling regulations exist at the Federal, State, and local levels.

These regulations reflect the perishability of the

products, which are ideal media for the growth of

microorganisms; the potential for their adulteration;

the potential for drugs and/or chemical residues

related to milk production processes; and the potential for variations in the nutritional value of products.

Over time, more stringent water quality standards

. . . . . . . ,.,. . .

have been placed on dames, affecting the management of animal wastes and runoff. In some instances,

air pollution regulations have also been imposed.

Overlying the EPA- and FDA-oriented regulations is

an extensive set of Federal and State milk-pricing

regulations. These include a network of Federal milk

marketing orders, State milk marketing orders, and

the milk price-support programs discussed earlier.

The following section summarizes some of the

major issues of dairy policy and how policy considerations and regulatory mechanisms may interact to

shape the industry’s future.

Butterfat Surplus

Nutrition- and diet-conscious consumers increasingly have shunned higher butterfat products. (Increased consumption of premium ice cream is one of

the few exceptions to this trend.) As a result of

declining demand, a butterfat surplus has developed,

although overall, milk supply and demand have been

in relative balance during the late 1980s and early
24 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Figure 2-9—Change in Milk Production by Region, 1980-89

LS NE PA MT SP NP SE DL CB AP US

Region

Key: LS - Lake States MT - Mountain

NE - Northeast SP - Southern Plains

PA - Pacific NP - Northern Plains

SOURCE: U.S. Department of Agriculture, Economic Research Service, 1990.

1990. Commodity Credit Corporation (CCC) pricesupport purchases of butterfat have continued even

as USDA has had to enter the commercial market to

satisfy cheese demand for its child nutrition programs. USDA has attempted to remedy the butterfat

surplus problem by consistently lowering the price

of butterfat to stimulate consumer demand while

holding the cheese price constant. This strategy has

been only partially successful. Surpluses in cheese

and nonfat dry milk (NFDM) have completely

disappeared since 1988 and butterfat surpluses

continue (see figure 2-16).

Future trends could further complicate the butterfat surplus problem. Lowfat cheeses and lowfat ice

cream are capturing a larger part of that market. Fat

substitutes are also being developed for use in ice

cream, and perhaps other dairy products. These

trends represent a two-edged sword; they could

SE - Southeast AP - Appalachian

DL - Delta States US - United States

CB - Corn Belt (national average)

result in increased total demand for dairy products,

yet further reduce butterfat demand.

Research progress in removing cholesterol from

butterfat may be the solution to the problem.

However, for reasons of diet and health, consumers

are concerned over a range of issues: total fat

consumption, calorie intake, saturated fat consumption, and cholesterol intake. Fat substitutes aggravate the butterfat problem whether or not cholesterol

is effectively removed from butterfat.

From the above analysis, it seems that the

solution to the butterfat problem may be to reduce

butterfat production. This can be partially accomplished by changing feeding practices in the short

run and by breeding for reduced butterfat in the long

run. Pricing incentives must exist for either of these

potential solutions to occur. Milk currently is priced,

to a large extent, on the basis of butterfat content.
Chapter 2----Overview of the Dairy Industry ● 25

Figure 2-10—Share of Milk Production by Region, 1989

40

30

20

10

0

27.4

LS NE PA MT SP NP SE DL CB AP

Region

Key: LS - Lake States MT - Mountain

NE - Northeast SP - Southern Plains

PA - Pacific NP - Northern Plains

SOURCE: U.S. Department of Agriculture, Economic Research Service, 1990.

Shifts to pricing on the basis of protein or nonfat

solids are possible and practiced in some markets.

Industry initiatives and USDA leadership are required to obtain widespread adoption of such

innovative pricing alternatives.

Milk Price Support

Related to the butterfat issue is the mechanism for

adjusting the milk price-support level. From 1949

through 1981, the milk price-support level was set as

a percent of parity (a price that will give a farmer the

same purchasing power he/she had in abase period).

Generally, the Secretary of Agriculture was given a

discretionary range of 75 to 90 percent of parity

within which to set the milk price-support level. In

1981, a trigger mechanism relating changes in the

price support to the level of government purchases

was adopted. Under the 1985 farm bill, the milk

price support was raised in $0.50 per cwt increments

SE - Southeast AP - Appalachian

DL - Delta States US - United States

CB - Corn Belt (national average)

when CCC purchases of dairy products were projected for the following year to be less than 2.5

billion pounds and decreased at the same rate when

such purchases were projected to be greater than 5.0

billion pounds. The pounds were measured on a

butterfat-milk-equivalent basis. The butterfat basis

became an issue when CCC cheese and dry milk

purchases ended in 1989, and as butterfat purchases

increased.

The 1990 farm bill dairy policy provisions froze

the price support at $ 10.10 per cwt through 1995. For

deficit reduction purposes, it assesses $0.05 per cwt

for all milk produced in 1991 and $0.1125 in

1992-1995. This assessment is refunded on proof

that the farmer’s milk production was not increased

over the previous year. The Secretary is required to

prepare a report with recommendations to Congress

on how it plans to limit growth of CCC purchases of

dairy products by August 31, 1991 with exclusions
26 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

5

I

-2.5

Key:

Figure 2-1 l—Change in Share of Milk Production by Region, 1980-89

4.1

LS NE PA MT SP NP SE DL CB AP

Region

LS - Lake States MT - Mountain SE - Southeast AP - Appalachian

NE - Northeast SP - Southern Plains DL - Delta States US - United States

PA - Pacific NP - Northern Plains CB - Corn Belt (national average)

SOURCE: U.S. Department of Agriculture, Economic Research Service, 1990.

of cow slaughter and price-support reduction options. If Congress fails to enact dairy legislation by

1992 and CCC purchases are expected to exceed 7

billion pounds, an assessment covering the full cost

of the CCC purchases over 7 billion pounds is

authorized.

As a result of these decisions, the following policy

issues are pending as the industry enters the 1990s:

the potential for effective demand expansion

programs-the 1990 farm bill authorizes a

processor-funded demand expansion check-off

if approved by referendum,

the potential for developing effective temporary supply and/or management systems that do

not lead to industry inefficiencies and rigidity

in production patterns,

what to do about declining demand for butter

and the accumulation of butter stocks, and

how much discretion the Secretary of Agriculture should have in determining the provisions

of dairy policy.

Price Instability

As the price-support level has declined, the price

of milk and manufactured dairy products has become more variable. This instability is the result of

the interaction of an inelastic supply and demand for

milk. With lower price supports, instability is

particularly evident in autumn when milk supplies

are often relatively short. For example, in 1989, the

Minnesota-Wisconsin (M-W) price rose from a low

of $11.20 per cwt in May to $15.10 in December. It

then fell back to $12.20 in March 1990 (see figure

2-17). By September 1990, the M-W was approaching the milk price-support level of $10.10 per cwt.

From an industry perspective, one of the benefits

of dairy policy has been the stability provided by the

price support and Federal order program. Current

predictions regarding M-W prices are widely variable. While some argue that the milk price support

will once again determine the price of milk under the

1990 farm bill, others suggest that significant

segments of the milk industry cannot survive such

low prices. Planning for the future has become

exceedingly difficult for producers, processors, USDA,

and Congress.
Chapter 2-Overview of the Dairy Industry ● 27

Figure 2-12—Actual and Projected Consumption of

Lowfat Milk, 1950-93

Figure 2-1 3—Market Share of Lowfat MiIk as a Percent

of Total Fluid Milk Consumption

60 m l

40, . ~ : : : :m

,,! ,.

: , . ”

,.

.

L

,.”

.“ :

I

45

15

0 ~ ~ ~ ~ : : : :

1950 1955 1960 1965 1970 1975 1980 1985 19901993

Year o

-- Projected — Actual 1970 1975 1980 1985 ‘1 990

Year

SOURCE: U.S. Department of Agriculture, Economic Research Service,

Dairy Situation and Outlook Report, various years, 1970-1991.

Figure 2-15—Actual and Projected Consumption of

SOURCE: Reginald Adamus and Emerson Babb, “Projections of U.S.

Dairy Product Consumption, 1989 -1993,” Food and Resource

Economics Department, University of Florida, 1990.

Figure 2-14—Actual and Projected Consumption of

American Cheese, 1950-93 -

Other Cheese

3.0

2.5 –r

I I I I I I I 1

1950 1955 1960 1965 1970 1975 1980 1985 19901993 1950 1955 1960 1965 1970 1975 1980 1985 19901993

Year

-

- Projected — Actual

SOURCE: Reginald Adamus and Emerson Babb, “Projections of U.S.

Dairy Product Consumption, 1989 -1993,” Food and Resource

Economics Department, University of Florida, 1990.

Year

--- Projected — Actual

SOURCE: Reginald Adamus and Emerson Babb, “Projections of U.S.

Dairy Product Consumption, 1989 -1993,” Food and Resource

Economics Department, University of Florida, 1990.

Milk Production Controls

During the 1980s, a dairy diversion program and

a dairy termination (buyout) program were implemented as means of reducing milk production—in

addition, the price-support level was lowered from a

high of $13.10 per cwt to $10.10 per cwt. The

termination program was considerably more effective than the diversion program but also more

controversial because of its negative impact on the

price of beef.

The combination of the termination program and

lower price supports has brought milk production

into relative balance with consumption. With this

accomplished, attention has turned to the potential

need for production controls should surpluses once

again accumulate. This could happen if milk supply

increases sharply due to rapid adoption of a new

technology, and/or if demand falls due to negative

consumer reaction to the same technology. After

passage of the 1990 farm bill, options for production

controls (or inventory management) would appear to

include:

utilization of a combination assessment and

production control system;

implementation of some type of quota system;

and

in concert with either assessments and/or quotas, an aggressive program to expand domestic

and foreign demand.

●

●

●

292-860 O - 91 - 2
28 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Figure 2-16—Uncommitted Government Dairy

Product Inventories, 1985-90

1,200

1,000

g

800

200

}-Q- -. .

-------

0 1i i - i”” ‘I

I

1985 1986 1987 1988 1989 1990

— Butter . . . . Cheese ---- Non-fat dry milk

SOURCE: U.S. Department of Agriculture, Economic Research Service,

Dairy Situation and Out/ook Report, various issues, 1985-1991.

Federal Milk Marketing Orderss

Historically, decisions regarding Federal milk

marketing orders have been left largely to the

Secretary of Agriculture. However, the 1985 farm

bill increased Class I milk prices, emphasizing

markets distant from the Upper Midwest. In 1988,

the General Accounting Office (GAO) published a

study indicating that Federal orders tended to favor

regions to the South and East at the expense of

producers in the Upper Midwest. The GAO report

recommended a gradual but progressive succession

of steps to reduce the level of regulation in Federal

orders.

In light of these developments, the Secretary of

Agriculture has initiated a series of national hearings, which were to be completed by the end of 1990.

The 1990 farm bill mandates decisions on Federal

orders by 1992. Major issues identified for the

hearings include:

●

●

●

●

●

the level of class prices for milk,

the number of classes and products included,

the geographic structure of prices including the

potential for multiple basing points,

the need for uniformity in order provisions, and

the appropriate basis for new Federal order

class prices (as opposed to the MinnesotaWisconsin series).

Figure 2-17—Minnesota-Wisconsin (M-W) Price and

Milk Price-Support Level, January 1987 to April 1990

20

zv

&

15

10

5

0

\ i i i ‘I i

1/87 6187 1/88 6188 1/89 6/89 1/90 4/

Month/year

— M-W . . . Price support

SOURCE: U.S. Department of Agriculture, Economic Research Service,

Dairy Situation and Outlook Report, various issues, 1988-1991.

Basic Formula Price

Since the 1960s, the Minnesota-Wisconsin price

series has served as the basic formula price used to

move or change the level of all Federal order milk

prices. The M-W price has also served as the guide

for determining if the milk price support objective

set by Congress or the Secretary of Agriculture has

been realized.

The M-W price series is the average price paid for

Grade B milk (which can only be used for processing

dairy products such as cheese and butter) by

Minnesota and Wisconsin processing plants. However, the volume of Grade B milk produced in

Minnesota and Wisconsin has declined to where the

M-W price series may not reliably reflect the forces

of supply and demand for this milk

In 1989, the GAO concluded that alternatives to

the M-W price series should be evaluated and

implemented. It recommended two options:

. a product formula based on the market prices

for butter, NFDM, and/or cheese; and

. a competitive price for Grade A and Grade B

milk.

5A ~e~ation issued by tie Secre[q of Agl-icul~e Specifying minimum prices and conditions under which mi~ can be bought and sold within a

specified geographic area.
Chapter 2---Overview of the Dairy Industry ● 29

Emerging Technology

The dairy industry will be among the first to adopt

many of the newly emerging technologies from the

biotechnology era. Considerable controversy surrounds the potential use of these technologies. This

is especially true of bovine somatotropin (bST), now

undergoing review by the Food and Drug Administration (FDA). Concerns about food safety, animal

safety, the manufacturing process to produce the

technology, and the economic impacts on the dairy

industry have all coalesced to make bST the focus of

a controversy of unprecedented magnitude in the

dairy industry.

A number of actions have already been taken to

slow or stop the use of bovine somatotropin. Two

States have declared a moratorium on the use of the

technology if approved by FDA. Four States have

enacted or are considering enacting labeling requirements on dairy products produced from bSTsupplemented milk. And consumer groups have

successfully pressured some large retail food stores

not to market dairy products produced with this

technology.

The next chapter provides information and an

analysis of the issues relevant to this technology.

Subsequent chapters discuss other major emerging

technologies that should become available in this

decade for the dairy industry.

1.

2.

3.

CHAPTER 2 REFERENCES

U.S. Department of Agriculture, Dairy: Background

for 1990 Farm Legislation, Economic Research Service, staff paper AGES9020 (Washington, DC: 1990).

U.S. General Accounting Office, Milk Marketing

Orders: Options for Change, GAO/RCED-88-9 (Washington, DC: March 1988).

U.S. General Accounting Office, Milk Pricing: New

Method for Setting Farm Milk Prices Needs To Be

Developed, GAO/RCED-90-8 (Washington, DC: November 1989).
Chapter 3

An emerging Technology:

bovine somatotropin
Contents

Page

STATE OF THE ART . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

PRODUCTION RESPONSE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

NUTRIENT REQUIREMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

BOVINE REPRODUCTIVE PERFORMANCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

MILK AND MEAT COMPOSITION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

MECHANISMS OF ACTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

BOVINE HEALTH AND STRESS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

ONFARM ENVIRONMENTAL POLLUTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ...43

INSTITUTIONAL INVOLVEMENT IN bST RESEARCH . . . . . . . . . . .. .. ... ... ......43

TIMING OF COMMERCIAL INTRODUCTION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

PRODUCT LABELING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..45

CHAPTER PREFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

Figures

Figure Page

3-1. Effect of Quality of Management on Milk Response of Dairy Cows Receiving

bovine Somatotropin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. ,... 35

3-2. Temporal Pattern of Milk Yield, Net Energy Intake, and Net Energy Balance

During a Lactation Cycle in Dairy Cows.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

3-3. Efficiency Gains by Reduction in the Proportion of Nutrients

Used for Maintenance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Tables

Table Page

3-1. Impact of bovine Somatotropin on Animal Numbers, Feed Requirements, and

Waste Production of Dairy Cows to Achieve 1988 U.S. Milk Production . . . . . . . . . . 35

3-2. Effect of bovine Somatotropin on Specific Tissues and Physiological Processes

in Lactating COWS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

3-3. Comparison of Theoretical Gains in Milk Yield Per Cow for

. . . . . . . ,.

Different Dairy Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Chapter 3

An Emerging Technology: bovine Somatotropin

The U.S. dairy industry has a rich history of

technological advances underpinningg steady and

significant increases in the efficiency and economic

returns of milk production. Progress in biotechnology and information technology will carry this trend

into the 1990s. Through the application of biotechnology, farmers will be able to manipulate to an

unprecedented degree herd reproduction, genetics,

and the physiological variables that affect their

animals’ productive efficiency.

Genetically superior (more productive) animals

are distinguished by their regulation of nutrients;

new concepts of how this occurs have recently been

established (6,10,1 1). Potentially one of the most

significant of the new biotechnologies is bovine

somatotropin (bST). Recent work has demonstrated

that somatotropin exerts a key control over nutrient

use. When administered exogenously, it markedly

improves the productive efficiency (milk per unit of

feed) in lactating cows. It does so by coordinating

the metabolism of body tissues such that more

nutrients are used for milk synthesis.

However, a number of questions involving human

safety, animal safety, economic concerns, and ethics

surround bST. Lay articles focusing on human and

animal safety issues of bST imply that little research

has been done. In fact, the scientific literature on bST

contains at least 1,000 studies involving some

10,000 dairy cows.l This chapter provides an

overview of bST technology and the concerns

surrounding it. It assesses the validity of these

concerns based on current

on dairy industry trends.

STATE OF

scientific knowledge and

THE ART

Somatotropin, a hormone, was discovered about

50 years ago. Initial investigations showed that

when rats were injected with a crude pituitary

extract, growth rate was increased (only later did

scientists discover that milk yield of lactating

animals increased as well). This extract factor was

called somatotropin from the Greek derivation

meaning “tissue growth. ” Based on this derivation,

somatotropin is sometimes referred to as growth

hormone or GH.

Somatotropin is produced by the anterior pituitary

gland, a small gland located at the base of the brain.

Like any hormone, it is transported in the bloodstream to the various body organs where it exerts its

biological effects. In effect, it acts as a chemical link

between different cells and organs of the body. The

term “hormone” has taken on negative connotations in recent times, primarily due to steroid abuse

by athletes. However, the chemistry of hormones is

as diverse as their biological functions. For example,

vitamin D (with which pasteurized milk is fortified)

is a steroid hormone.

Somatotropin is also a protein, unlike steroids,

which are nonprotein hormones. Like all proteins, it

is composed of amino acids. (There are 20 different

amino acids, which combine in specific sequences to

form some 10,000 different proteins in the body.

Amino acids are analogous to letters in an alphabet,

which combine to form a diverse vocabulary of

words.) The amino acid sequence of somatotropin is

known for many species, including cattle (41,79).

Bovine somatotropin can be either 190 or 191 amino

acids long and either of two different amino acids

(leucine or valine) occupy position number 126 in

the sequence (80). Thus, four different variants of

bST are produced naturally. Typically, the pituitary

produces equal amounts of the 190 and 191 aminoacid bST. About two-thirds of the total bST produced has leucine at position 126, while the remaining one-third has the amino acid valine at position

126.

Artificially introduced somatotropin must be

injected to be biologically active. If somatotropin is

given orally, it is broken down by digestive track

enzymes to amino acids for absorption. This is true

for all dietary proteins and large protein hormones in

all species. Just as human diabetics must take insulin

injections (insulin, another protein hormone, is also

inactive if taken orally), humans deficient in somatotropin must take injections of human somatotropin

(hST). Studies have demonstrated that when fed to

rats, bST was inactive even at a daily dose (units/

IBecause of tie l~ge quanti~ of res~ch on bST, this chapter will mainly cite review articles of these studies.

–33–
34 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

body weight) equivalent to 2.3 million times what a

human would be exposed to in five 8-ounce glasses

of milk (38,67).

Somatotropin is referred to as “species limited”

in the scientific literature. This means that there are

differences in the ability of somatotropin from one

species to elicit biological effects when injected in

other species. To have a biological effect, a protein

hormone must first bind to a specific receptor

located on the cell surface. The amino acid sequence

of somatotropin gives it a unique three-dimensional

shape, which determines whether the protein will be

able to bind to tissue somatotropin receptors and

elicit a biological response.

Some 25 years ago it was discovered that certain

types of human dwarfism were due to an inadequate

pituitary production of somatotropin. Because hST

was scarce, physicians conducted an extensive series

of studies in which patients were treated with

injections of bST. These clinical studies uniformly

demonstrated that bST does not elicit any of its

normal biological actions in humans even if injected

(20,38,41,79). Somatotropin isolated from the pituitary glands of sheep, pigs, and whales was also

ineffective in humans, Biological activity in humans

is only observed if somatotropin from primates is

used.

The reason for bST’s lack of effect in humans

became clear when its amino acid sequence was

identified; the sequence of bST, which gives it its

three-dimensional shape, differs by about 35 percent

from that of hST (79). Thus, bST is not able to bind

to the somatotropin receptors of human tissues

(36,38). In contrast, ovine somatotropin and bST

differ in only one amino acid position so bST is

biologically active if given to sheep.

Recombinantly derived bST products differ slightly

from the bST produced by the pituitary gland in that

a few extra amino acids may become attached to the

end of the bST molecule in the manufacturing

process. The number of extra amino acids varies

from 1 to 8 depending on the particular manufacturing process (38). For some manufacturing processes,

no additional amino acids are produced. Some claim

that for processes that produce extra amino acids,

and the fact that recombinantly derived bST is

produced by bacterial ribosomes, it renders the

product hyperpotent to cows and dangerous to

humans (23,46,64). However, the additional few

amino acids on the end of the protein do not alter the

biological activity of bST in dairy cows or the lack

of activity of bST in humans because the threedimensional shape of the active part of the molecule

is not changed (36,79). This shape, moreover, is

determin ed by the sequence of amino acids, not by

whether or not bacterial ribosomes were used for the

synthesis.

The first bST research with lactating cows was

reported in 1937 by Russian scientists (l). With

advances in protein chemistry, somatotropin preparations gradually improved in purity and several

dozen studies have since been conducted with dairy

cows. Particularly significant were a series of studies

in the 1940s by scientists in the United Kingdom

(81) and later studies by Brumby and Hancock (13)

and Machlin (49).

Prior to the 1980s, bST research progress remained slow for two reasons. First, bST availability

was limited to what could be extracted from the

pituitary glands of slaughtered animals. Thus, only

a small number of cows could be treated for

short-term studies. Second, because bST w a s

thought to act by acutely stimulating the use of body

fat reserves, scientists believed it would work only

in fat cows with a low milk yield. Thus, only low

producing cows (generally less than 7 kilogram (kg)

milk/day) were studied. It was assumed that bST

would cause ketosis2 and adverse health effects in

high producing cows.

Scientists at the National Institute for Research in

Dairying in England, and others at Cornell University, in the late 1970s began to work on bST. Both

groups concluded that the physiological basis for

genetically superior cows (i.e., those more efficient

in milk production) was better use of absorbed

nutrients (10,12). Based on new concepts of how

animals regulate the use of nutrients (7), both groups

hypothesized that somatotropin could play a key role

in nutrient regulation and that the previously proposed mechanism of action (acutely stimulated use

of body fat) was wrong. Over the last decade these

concepts have been applied to research with somatotropin and the biology of nutrient use during

growth, pregnancy, and lactation for many species.

2A me~bolic disorder that OCCUrS when production of ketones exceeds the ability of the body to use them. Occurs in dafi cows when the need for

glucose exceeds the production of glucose.
Chapter 3--An Emerging Technology: bovine Somatotropin ● 35

SOURCE: D.E. Bauman, “Bovine Somatotropin: The Cornell Experience,”

Proceedings of the National Invitational Workshop on Bovine

Somatotropin, pp. 46-56, USDA Extension Service, Washington, DC, 1987.

Initial investigations with cows used pituitaryderived bST. After landmark breakthroughs in

biotechnology, in 1982, the Cornell scientists conducted the first study with dairy cows using recombinantly derived bST produced by Monsanto Co.

and Genetech Co. (8). Since that time the quantity

and scope of research with bST has increased

exponentially.

PRODUCTION RESPONSE

Quality of management will be the major factor

affecting the magnitude of lactation response to bST

(4,16,17,57). This concept is illustrated qualitatively

in figure 3-1. Across 45 field trial studies conducted

in the United States, Europe, and Africa a correlation

of 0.58 was observed between pretreatment group

milk yield (an indication of management quality)

and kg milk response to bST (57). A similar

relationship between management quality and gains

realized is observed for other technologies, such as

artificial insemination (AI) with semen from superior sires.

Facets that contribute to the quality of the overall

management program include the herd health program, milking practices, nutrition program, and

environmental conditions. Inadequate management

can result in a near zero response to bST supplement

(51,52,57). McCutheon et al. (51) studied bST’s

effects as the quality of herd nutritional management

varied over the course of the 26-week treatment

period. Cows were fed only pasture, and milk

responses to bST were greatest (+18 percent) in the

spring when pasture supply was adequate, declined

to zero during the summer drought, and were again

significant during the fall. As this illustrates, bovine

somatotropin is not magic. If cows are given an

inadequate amount of feed or fed a diet that is not

nutrient-balanced, the magnitude of the response to

bST will decrease accordingly (see figure 3-l).

While the milk response to bST on an individual

farm will vary according to quality of management,

a reasonable expectation is that successful adopters

would experience an average gain in productivity of

12 percent. This gain in productivity could lead to

substantial savings in dairy cattle feed nationally.

Assuming 100-percent adoption and milk production at 1988 levels (26), then decreased cow numbers

(10.7 percent) and increased productive efficiency

would translate into annual savings in dietary energy

equivalent energetically to 2.5 x 109 kg of corn grain.

Annual savings in dietary protein supplements

would be equivalent to 5.6 x 107 kg of soybean meal

(see table 3-l). These savings in feedstuffs represent

Table 3-1—impact of bST on Animal Numbers, Feed

Requirements, and Waste Production of Dairy Cows

To Achieve 1988 U.S. Milk Productiona

Variable Impact of bSTb

Animals:

Cow numbers . . . . . . . . . . . . . . . .

Milk yield per cow . . . . . . . . . . . . .

Feed: c

Energy equivalent as

corn grain . . . . . . . . . . . . . . . . . .

Protein supplement equivalent

as 44% soybean oil meal . . . . .

Waste:

Manured. . . . . . . . . . . . . . . . . . . . .

Urinee 

. . . . . . . . . . . . . . . . . . . . . .

Urinary nitrogene. . . . . . . . . . . . . .

Methanef . . . . . . . . . . . . . . . . . . . .

Decrease by 10.70/.

Increase by 12.0?4.

Decrease by 2.5 x 109 kg

Decrease by 5.6 x 107 kg

Decrease by 6 x 109 kg

Decrease by 8 x 109 L

Decrease by 8 x 107 kg

Decrease by 8 x 1010 L

aU. S. 1988 milk production values were 10.24x 10G cows, 6,460 kg milk per

cow, and 66 x 109 kg total milk production (26).

bAssumed I oo.percent adoption and that use would increase avera9e

annual milk yield per cow by 12 percent. If commercially approved,

expected impact would be less because technology rarely achieves

100-percent adoption.

cBased on nutrient requirements for dairy cows averaging 650 kg body

weight and producing milk of 3.5-percent fat content (54).

dBaSed on an average diet composition of 1.62 Meal net energy/kg, a diet

digestibility of 65 percent, and fecal dry matter of 16 percent (72).

eBased on a daily urine production of 20 L per cow with 1-percent nitrogen

in urine (72).

fAssumed that methane production represents 5 percent of gross ener9Y

intake (72).

.SOURCE: D.E. Bauman, “Bovine, Somatotropin: Review of an Emerging

Animal Technology,” commissioned background paper prepared for the Office of Technology Assessment, Washington,

DC, 1990.
36 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

maximal estimates because commercial adoption of

new technology is rarely 100 percent (see ch. 5).

Milk yield gradually increases the first few days

of bST treatment, peaking at about the sixth day

(37,56). A maximum milk response is achieved at a

bST dose (daily injection) of about 30 to 40

milligrams (mg) per day; no further increase occurs

even at doses several-fold higher. Most production

trials have used a bST dose between 10 to 50 mg per

day. Exogenous bST must be introduced every day

(by injection or via a prolonged-release formulation)

in order to maintain an augmented milk response.

This is because bST is cleared rapidly from the

bloodstream and is not stored in the body. Removal

is by protein breakdown to amino acids—a normal

body function. Several prolonged-release formulations have been developed and are administered by

subcutaneous injection at intervals ranging from 2 to

4 weeks (17).

Response to bST varies according to stage of

lactation (see figure 3-2). In general, the milk

response is small or negligible when bST is administered in early lactation (the interval immediately

postpartum, prior to peak milk yield) (4). The

biological basis for this low response relates to the

nutrition/endocrine status of the animal during this

interval. In contrast, substantial increases in milk

yield occur when bST is administered after peak

yield of milk is attained. Lactational responses to

bST have been reported for all dairy breeds examined, including North American and European

breeds as well as Murrah buffalo, and for animals of

different parity (lactation number) and genetic

potential (16,17,56).

Marked improvement in persistency of lactation

occurs in cows receiving bST (16,17,56). The

greater overall milk yield with bST supplementation

occurs in part because of an immediate increase in

milk yield, but mainly because of a reduction in the

normal decline in milk yield that occurs as lactation

progresses.

Cows treated with bST show a range of responses.

In a few instances this has been cited as evidence of

individual variation in response. However, this is

misleading. All studies with bST have shown that

the yield variations within bST-supplemented

groups is similar to that of untreated groups (5,57).

Thus, to a large extent, all cows in a herd respond to

bST in a fairly similar manner. The bST-suppleFigure 3-2—Temporal Pattern of Milk Yield, Net

Energy Intake, and Net Energy Balance During

a Lactation Cycle in Dairy Cows

Panel A-Milk yield (4% fat-corrected milk)

15 I \

35 r Panel B-Net energy intake

>

151

8 Panel C-Net energy balance

I

~z--- ~

, <

‘ .

$ 4

,/ ‘\\

u I

f

h o

-----------------

Q

-12 L

o 8 16 24 32 40

Week of lactation

Cows averaged 9,534 kg milk (21,000 Ibs) over the first 305 days

of lactation. Typically, daily milk yield peaks during the first month

after parturition (birth of the calf) and then progressively decreases through the remainder of the lactation cycle (Panel A).

The rate of this decline in daily milk yield is referred to as the

persistency of lactation. Typically, voluntary feed intake increases

gradually over the first few weeks of lactation and peaks about 6

to 10 weeks after parturition (Panel B). Dairy cows are generally

in negative energy balance during the first portion of the lactation

cycle (Panel C). During the first month of lactation for these cows,

the body reserves being utilized (i.e., net energy deficit) were

energetically equal to about one-third of the milk produced. Under

normal management conditions the daily cow is overfed (positive

energy balance) during the last third of lactation to allow for

replenishment of body energy stores needed to support the next

lactation cycle (dashed line, Panel C).

SOURCE: D.E. Bauman and W.B. Currie, “Partitioning of Nutrients During

Pregnancy and Lactation: A Review of Mechanisms Involving

Homeostasis and Homeorhesis,” J. Da”ry %“. 63:1514-1529,

1900.
Chapter 3--An Emerging Technology: bovine Somatotropin ● 37

mented cow that ‘‘appears’ to be a low responder

simply matches the low producing control cow.

NUTRIENT REQUIREMENTS

Nutrient requirement tables are unchanged for

bST-supplemented dairy cows(11, 16). The basis for

this is two-fold. First, digestibilities of dry matter,

carbon, nitrogen, and energy are not altered when

lactating cows are receiving bST. Second, bioenergetic studies have demonstrated that bST does not

alter energy expenditure for maintenance, or for the

synthesis of a unit of milk. Nutritional needs for

maintenance, milk production, pregnancy, and to

replenish body reserves over a lactation cycle for a

cow producing 10,000 kg milk per year are the same

regardless of whether she received bST or not.

No special diets or unusual feed ingredients are

needed to obtain a milk response to bST: substantial

milk responses have been observed on diets ranging

from pasture to forage concentrates.3 Overall, however, the dairy cow receiving bST has a greater total

nutrient requirement because she is producing more

milk. She has a higher productive efficiency because

a larger proportion of her total nutrient intake is used

to make milk (see figure 3-3).

Voluntary intake of feed increases in bST-supplemented dairy cows, beginning after a few weeks

of bST supplementation, and persisting throughout

the interval of bST use. This has been consistently

observed across a wide range of diets (16,17,56).

Overall, cows supplemented with bST adjust their

voluntary intake in a predictable manner related to

the extra nutrients required for the increased production of milk. The magnitude of increase in feed

intake is dependent on the response in milk yield and

the energy density of the diet (17). It is expected with

current feed costs that use of bST for dairy cows will,

on average, lead to a predictable increase in the

energy density of the diets used (increased ratio of

concentrate to forage). This is because income over

feed cost increases with level of milk production

even though the cost for higher energy ingredients is

greater. However, as noted, bST increases milk yield

even when pasture is the only dietary ingredient.

Figure 3-3-Efficiency Gains by Reduction in the

Proportion of Nutrients Used for Maintenancea

❑ Milk

❑ Maintenance

30

20

10

0

Control bST

aFor this example, the hypothetical control cow Produced 6,818 kg (15,000

lb) of milk in a’lactation-and use of bST increased milk yield by 20 percent

SOURCE: D.E. Bauman, “Biologyof Bovine Somatotropin in Dairy Cattle,”

Advanced Technologies Facing the Da”ry lndustry:bST, Cornell

Cooperative Extension Animal Science Mimeograph Series

#133 (Ithaca, NY: Cornell University, 1989), pp. 1-8.

BOVINE REPRODUCTIVE

PERFORMANCE

Of special interest are the effects of bST on

reproductive variables such as conception rate (services per conception), pregnancy rate (proportion of

cows becoming pregnant), and days open (days from

parturition to conception). Normally, variation in

reproduction variables is large. Effects of bST

supplementation are small enough that large data

sets are needed to allow definitive conclusions.

Several reviews have summarized many of the

studies on reproduction variables (28,55,59). In

general, these summaries indicate that bST suppleslJse of somatotropin for growing animals will require modification of the maintenance and growth components of the nutrient requirement tables

because of tbe shift in the type of growth (increased prote@ decreased lipid).
38 ● U.S. Dairy Industry at a crossroad: Biotechnology and Policy Choices

mentation results in a decrease in pregnancy rate but

that conception rate is not altered. For example,

Ferguson and Skidmore (28) found that pregnancy

rate (n >3,000 cows) was 89.2 percent for controls

and 81.2 percent for bST-supplemented cows (bST

dose ranged from 5 to >200 mg per day). Days open

increased a few days in bST-supplemented cows

according to most studies.

The studies that identified changes in pregnancy

rate and days open for bST-supplemented cows

followed management practices geared to achieve a

12- to 13-month calving interval. Thus, period of

breeding (commencing 50 to 60 days postpartum)

would generally have coincided with the early

period of bST supplementation when milk yield had

increased but before voluntary feed intake had

increased. It is well established that decreased

pregnancy rate and increased days open are associated with increases in milk yield (15). This is

because of the inverse relationship between level of

milk production and energy balance that typifies the

early stage of lactation. Ferguson and Skidmore

(28), for example, found the decrease in pregnancy

rate to be related to the increase in milk yield rather

than the dose of bST when they analyzed their

multistudy data by controlling for confounding

factors. Hard et al. (35) summarized a series of

studies that had a similar design and found that days

open increased by 5 days in the bST-supplemented

group; however, when data were stratified by level

of milk production, days open did not differ between

controls and bST-supplemented cows (35). Thus,

effects of high milk yield on reproductive performance are the same whether or not the high yield was

due to the use of bST

Calving interval for optimum economic return for

U.S. dairy farms will probably increase with bST

supplementation. Although conventional wisdom

has been that a 12- to 13-month calving interval

maximizes profit, many managers of high producing

dairy herds indicate that their calving interval is

longer (6). In the case of bST supplementation, not

only does milk yield increase, but persistency of

lactation is also improved. Thus, it is logical that the

calving interval for optimum economic return may

be substantially increased when bST is used. Ferry

(29) modeled the effects of a 12- and 14-month

calving interval on a herd basis and concluded that

with bST use, income over feed cost was considerably increased with a 14-month calving interval.

More extensive modeling, which included factors

such as veterinary costs and replacement values,

yielded a similar conclusion (70).

Extending the calving interval also has some

benefits from the standpoint of the physiology of the

cow. In the case of reproduction, increasing the

calving interval improves conception rate (71),

probably as a consequence of the nutritional status

of the cows as discussed earlier. In addition, the

majority of health problems and veterinary costs for

dairy cows occur during the first 45 days postpartum

(24). Thus, increasing the calving interval reduces

health problems and costs on an annual basis for a

herd and over an individual animal’s lifetime.

Optimum calving interval with bST use probably

will be different in the United States than in other

countries, particularly countries that have a seasonal

supply of feedstuffs and a beef industry largely

based on the offspring of dairy cows. Thus, the

actual calving interval that optimizes economic

return will vary according to a number of management and economic factors; still, a major determinant will be the magnitude of milk response and the

increased lactation persistency that occurs with bST

use.

Genetic evaluation of sires might be affected by

use of bST if an interaction between genotype and

the milk response to bST occurs, or if bST is

inappropriately used to manipulate sire proofs.

Several studies have concluded that no evidence

exists of a genotype-response interaction in bSTsupplemented cows (32). Sire evaluations involve

the comparison of the performance of a bull’s

daughters with the performance of their contemporary herdmates. A bias in sire evaluations can occur

(and has) if a farmer gives preferential treatment to

the daughters of a particular sire that he hopes to

market commercially (25). Potential for bias from

the use of bST is similar and can be handled by

properly coded records and/or use of AI-proven sires

(25,32), With proper coding of records, bST-treated

daughters could be compared only with herdmates

that had also received bST supplement. Similarly,

when the sire is evaluated with AI records, many

more daughters in a large number of herds will be

involved; thus the chance for bias is negligible.

MILK AND MEAT COMPOSITION

Gross composition of milk (fat, protein, and

lactose content) and meat has been examined inmost

bST production trials, and is not substantially altered
Chapter 3-An Emerging Technology: bovine Somatotropin ● 39

by bST supplementation (3,16,50,56,75). There can

be minor changes, primarily in fat content of milk,

during the first few weeks of bST supplementation

as the cow’s metabolism and voluntary feed intake

adjust. However, these changes are temporary and

minor when compared with variations that normally

occur over a lactation cycle. Whereas the lactose

content of milk is relatively constant, the content of

fat, and to a lesser extent protein, normally varies

widely due to many factors including genetics,

breed, stage of lactation, age, diet composition,

nutritional status, environment, and season (48).

These factors affect the fat and protein content of

milk in the same manner in bST-supplemented and

nontreated cows (3,16,56). The meat derived from

treated cows has a lower fat content but is otherwise

identical (53).

The temporary shift in milk fat that can occur

during the first few weeks of bST supplementation

relates to nutritional status (11,16,56). Cows in

negative energy balance produce milk with a higher

fat content due to a greater reliance on lipids

mobilized from body fat stores. Milk fat content is

most likely to increase when bST supplementation

is initiated in the first 100 days postpartum, when

cows are typically in a lower energy balance.

However, the negative energy balance typical of this

period (and especially of the first 8 weeks of

lactation) is far in excess of that associated with bST

supplementation.

The lipid composition affects the milk’s nutritive

value, flavor characteristics, and manufacturing

properties. Studies demonstrate that fatty acid composition and cholesterol content of milk are not

altered by bST (3). Cows that are in negative energy

balance (as occurs early in lactation) shift milk fat

composition toward longer chain, unsaturated fatty

acids whether or not they receive bST supplementation. In addition, the same fatty acid composition

changes are observed in untreated and bSTsupplemented cows as lactation progresses.

Composition of milk proteins has been examined

in at least a dozen studies because of the impact on

functional properties of milk used in the manufacturing of dairy products (3,75). These studies have

demonstrated that the content and composition of

casein (et-casein, ß-casein, k-casein) are not altered

by bST supplementation; and that casein as a percent

of true protein is either unchanged with use of bST

or shows a small numerical decrease (often nonsignificant). One short-term study reports a small

increase in ct-lactalbumin content of milk in bSTsupplemented cows but this was not observed in

long-term studies. The nonprotein nitrogen (NPN)

content of milk from bST-supplemented cows

should vary with nutritional status just as it does in

untreated cows. Some countries routinely test NPN

levels in bulk milk as a management tool for farmers

to evaluate the protein adequacy of their nutritional

program (61).

Mineral content of milk from bST-supplemented

cows has been examined in short- and long-term

studies involving large numbers of animals (3,75).

Results have uniformly demonstrated that bST does

not alter ash (total mineral content) or any nutritionally important mineral. Only one published report

exists on the vitamin content of milk, but milk from

bST-supplemented cows did not differ in content of

any vitamin (vitamin A, thiamine, riboflavin, pyridoxine, vitamin B

12, pantothenic acid, and choline)

except for biotin, which showed a slight increase

(75). The increase in biotin content of milk is too

small to be considered a benefit; biotin, a member of

the b-vitamin family, is widely distributed in plant

and animal food products and is also synthesized in

the intestine of humans.

Manufacturing characteristics of milk have been

investigated in a smaller number of studies but

results have consistently demonstrated that milk

from bST-supplemented cows does not differ from

milk of untreated cows (3,75). Characteristics studied include freezing point, pH, alcohol stability,

thermal properties, proteases, lipases, susceptibility

to oxidation, and sensory characteristics, including

flavor. Similarly, no differences were observed in

cheese-making properties, including starter culture

growth, coagulation, acidification, and syneresis, or

in the yield, composition, or sensory properties of

the various cheeses.

Minor constituents of milk include hormones

such as estrogen, progesterone, glucocorticoids,

thyroid hormones, prolactin, and growth factors.

Trace concentrations of bST also normally occur in

milk and meat but this concentration is not appreciably altered when cows receive exogenous bST

(38,53,65,75). The level of bST in milk is only a

small fraction of the blood concentration. Only when

blood levels are increased about 30-fold by a

substantial dose of bST is there a small, but

significant, increase in milk concentrations of bST
40 U.S. Dairy Industry at a crossroad: Biotechnology and Policy Choices

(65). This lack of an appreciable change in milk

concentration of bST when exogenous bST is

administered is expected, given that mammary

epithelial cells do not have receptors for somatotropin (19). Pasteurization of milk destroys 85 to

90 percent of immunoreactive bST (33).

Some part of the biological actions of somatotropin may be mediated by insulin-like growth

factor I (IGF-I). IGF-I, a protein hormone and

member of the somatomedin family, normally occurs in trace levels in milk. The concentration of

IGF-I is higher in cows’ milk (3 to 10 parts per

billion) than in human milk (1 to 3 parts per billion).

Administration of bST to dairy cows results in an

increase in the amount of IGF-I in milk (by 2 to 5

parts per billion), but the levels are still within the

range typically observed in early lactation of untreated cows (31,38,65,75). There is approximately

twice as much IGF-I in meat of treated cows (2).

Studies with laboratory animal models have

demonstrated that IGF-I, like bST, has no biological

activity if administered orally (38). It is digested into

its amino acid, di- and tripeptide constituents by gut

enzymes. Similarly, no evidence exists that fragments of IGF-I are biologically active in humans,

nor is there evidence of systemic biological effects

in humans from any IGF-I absorbed intact. The

amounts of IGF-I that might potentially be ingested

in food products from treated cows are orders of

magnitude less than those required to produce such

effects (53).

The amount of IGF-I ingested in one liter of milk

from bST treated cows approximates the amount of

IGF-I in human saliva swallowed daily by adults

(31). Young children and infants already ingest

IGF-I in regular cows’ milk. The importance of the

additional amount of IGF-I in milk from bST-treated

cows—whether it has a local effect on the esophagus, stomach, or intestine of infants-is unknown

(53). However, most infants are either breast fed or

fed commercially prepared infant formulas; the heat

treatment used in the manufacture of these formulas

inactivates approximately 90 percent of IGF-I.

MECHANISMS OF ACTION

Somatotropin regulates the use of absorbed nutrients. When milk production is increased, extra

nutrients are needed by the mammary glands to

provide the raw materials and energy to make milk.

Somatotropin coordinates the metabolism of various

body organs and tissues in a manner that supports the

increased nutrient use by the mammary glands .

These coordinated adjustments in tissue metabolism

involve all nutrient classes--carbohydrates, lipids,

proteins, and minerals (see table 3-2), and are due to

the direct action of somatotropin on tissues (e.g.,

liver and adipose). The adjustments made are

characteristic of metabolic changes needed to support lactation in all mammals (11,56,77).

Glucose metabolism illustrates the coordinated

manner in which bST alters tissue processes. Glucose is a carbohydrate used as an energy source by

many tissues and as a raw material for milk synthesis

(primarily for production of milk sugar). Nearly all

of a cow’s daily glucose requirement is made by the

liver and the mammary glands typically use about 85

percent of the total. With bST-supplementation, the

uptake of glucose by the mammary glands increases

in a manner parallel to the increases in milk

production. This increased use of glucose for milk

synthesis is accommodated by whole-body adjustments which include increase glucose production by

the liver and reduced glucose use for energy by other

body tissues. In part, these adjustments occur

because bST alters the response of tissues to acute

signals (e.g., insulin), thereby allowing a greater

allocation of glucose for milk synthesis while still

maintaining normal body functions. Without such

adjustments in metabolism, initiation of bST supplementation would cause the glucose use to exceed

that which is available, resulting in ketosis and

death. Ketosis from bST supplementation has not

been observed in the hundreds of studies performed,

even in tests where bST resulted in increased milk

production of 40 percent or more.

Lipid metabolism provides another example of

the coordination which occurs with bST supplementation. The adjustments in tissue lipid metabolism

depend on the nutritional status of the cow at the

time bST-supplementation is initiated. Normally, if

a cow’s nutrient intake is greater than her requirements, the excess nutrients are used to make body

fat. BST administration causes adipose tissue to

reduce its use of nutrients to synthesize body fat and

allows for reallocation of these nutrients to support

increased milk production. A different metabolic

adjustment occurs if the cow’s nutrient intake is

equal to or less than her requirements. In this

instance, somatotropin directs adipose tissue to

mobilize deposits of body fat so that these energy

reserves can be used to support increased milk
Chapter 3-- An Emerging Technology: bovine Somatotropin ● 41

Table 3-2—Effect of bST on Specific Tissues and

Physiological Processes in Lactating Cowsa

Process affected during first few days and

Tissue weeks of supplement

Mammary T’

‘r

T

Liver T

o

Adipose ~

J’

o

Muscle ~

Pancreas 0

Kidne y

b 

~

Intestine b T

‘r

T

Whole -J

body

T

-J

0

0

‘T

‘r

T

secretory activity and maintenance of mammary

glands

blood flow and nutrient uptake

synthesis of milk with normal composition

production of glucose

response to acute signals (e.g., insulin) that allow

for greater glucose production

mobilization of fat stores to meet needs for

increased milk production if nutrient intake is

inadequate

use of nutrients for fat storage so that they can be

used for increased milk production if nutrient intake

is adequate

response to acute signals (e.g., insulin and other

hormones that affect lipid metabolism) that allows

for synthesis and breakdown of body fat reserves to

be coordinated with changes in use and availability y

of nutrients

uptake of glucose

insulin and glucagon secretion reponse to changing

glucose levels

production of 1,25 vitamin D3

absorption of Ca, P and other minerals required for

milk

ability of 1,25 vitamin D3

to stimulate calcium binding

protein

calcium binding protein

use of glucose by some organs so more can be used

for milk synthesis

use of fat stores for energy if nutrient supply is

inadequate

use of nutrients to make body fat if nutrient supply is

adequate

insulin and glucagon clearance rates

energy expenditure for maintenance

energy expenditure consistent with increase in milk

yield (i.e., heat per unit of milk not changed)

cardiac output consistent with increases in milk yield

productive efficiency (milk per unit of energy intake)

~hanges (’?=increased, ~=decreased, a=no change, o=change) that

occur in initial period of bST supplement when metabolic adjustments

occur to match the increased use of nutrients for milk. With longer term

treatment, voluntary intake increases to match nutrient requirements.

bDemonstrat~ in nonlactating animals and consistent with observed

performance in lactating cows.

SOURCE: D.E. Bauman, “Bovine Somatotropin: Review of an Emerging

Animal Technology,” ~mmissioned background paper for the

office of Technology Assessment, Washington, DC, 1990.

production. In both situations, these adjustments

involve alterations in adipose tissue response to

acute signals (e.g., insulin and other hormones that

affect lipid metabolism) thereby allowing the use of

body fat reserves to be coordinated with changes in

the animal’s need for, and availability of nutrients.

Over time, bST teated cows gradually increase their

feed intake so that stores of body fat are replenished

during a lactation cycle. This replenishment occurs

under a wide range of dietary conditions (11,16,17).

If these adjustments in lipid metabolism did not

occur, cows would become emaciated, decrease

their milk production, and be less efficient in their

use of feed for milk production. These effects have

not been observed; cows administered bST have

demonstrated increased milk production and improved feed efficiency.

In addition to the direct metabolic effects that bST

coordinates, somatotropin indirectly affects the mammary gland via its impact on other controlling

compounds (e.g., somatomedins such as IGF-1).

Effects include increased cellular rates of milk

synthesis and improved maintenance of secretory

cells (i.e., slower rate of cell loss). The net result is

that bST-supplemented cows have higher daily milk

yields and produce higher levels of milk throughout

the lactation cycle. Over the years, selection of

higher producing dairy cows has resulted in the same

improvements. Thus, it is not surprising that cows

that produce high levels of milk have higher

circulating levels of naturally produced somatotropin

than do cows that produce low levels of milk (6).

BOVINE HEALTH AND STRESS

Catastrophic health effects have been postulated

to occur with bST supplementation of dairy cows.

Ketosis, fatty liver, and chronic wasting have all

been proposed as possible side-effects of bST use

(12,43). Crippling lameness, milk fever (a feverish

disorder following parturition), mastitis (inflammation of the udder), infertility, heat intolerance,

sickness, suffering and death are recent additions to

the list of adverse health claims (23,30,45,62,63,64).

These postulated catastrophic effects were not based

on actual data but rather on the presumption that bST

caused the mobilization of lipids from body fat

reserves and/or overtly caused stress.

Metabolic disorders, if they occurred, would most

likely manifest themselves during the first few days

of bST use. None of the above catastrophic health

effects have been observed in any of the short-term

or long-term studies with dairy cows going back to

the frost bST study in 1937. They were not observed

in chronic toxicity studies (22,55), or in acute

toxicity studies where dairy cows were given 30,000

mg of bST over a 2-week period, an amount

approximately equal to what would be administered
42 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

in four lactations (about 40 months) (78). Nor were

adverse effects observed in studies where inadequacies in the overall quality of the management

program resulted in negligible milk responses to

bST supplementation. An increase in ketones (an

indicator of subclinical ketosis) was reported in one

earlier study involving two cows given bST for 9 or

10 days (42). However, that pituitary-derived preparation was contaminated with other hormones (42,44),

and this work has not been verified in acute or

chronic studies using larger numbers of cows treated

for longer periods with a wider dose range of

purified bST (1 1,16,59,78).

It also has been postulated that somatotropin will

reduce resistance to infectious and contagious diseases and thereby increase sickness and suffering in

dairy cows (23,30,63,64). Incidence of disease is

generally very low in dairy cows and a thorough

evaluation of these claims will require extensive

summarization across studies to obtain a large data

set. However, none of the hundreds of bST studies

reported lower milk yield or decreased productive

efficiency, both of which are associated with any

increase in sickness and suffering. On the contrary,

somatotropin plays a key role in several aspects of

maintaining immune competence (39). Immunity

and disease resistance are compromised in somatotropin-deficient laboratory animals and humans and

somatotropin supplementation enhances immune

competence in both groups. Such studies have not

yet been extended to lactating cows, but it has been

demonstrated that bST supplementation had a beneficial effect on cows’ recovery from experimentally

induced E. coli mastitis (14).

Stress is more difficult to evaluate, but several

indices exist that demonstrate no stress effects due

to bST. Dairy cows that are stressed produce less

milk less efficiently and expend more energy as heat

than expected. All of the several hundred studies of

bST in the scientific literature report increased milk

yield and productive efficiency. The duration of bST

use in these studies has ranged from a few weeks to

at least four successive lactations. While numerous

physiological variables have been monitored to

assess stress and have been shown not to change,

nothing illustrates the normalcy of bST-supplemented cows as effectively as the persistent gains in

milk yield and productive efficiency throughout the

treatment period. Recent studies spanning positive-tonegative energy and nitrogen balances, moreover,

have clearly demonstrated that bST has no effect on

the energy expended for maintenance or for the

synthesis of a unit of milk (40,68,73).

Subtle health effects require examination of

‘‘large numbers of animals treated under a range of

environmental and management conditions” (21). A

complete summary of individual studies done throughout the world is beyond the scope of this review.

Many have appeared as abstracts in the last 2 years

and have not yet been published as full-length

papers. However, these summarizations are required

of companies seeking the Food and Drug Administration (FDA) approval and are used by regulatory

agencies in their evaluation. Phipps (59) summarized a substantial portion of the studies conducted

through 1988. This review showed that the indices

of animal health for bST-supplemented animals

were similar to these for controls and were consistent

with values reported in the literature for untreated

cows at a similar level of milk production. Variables

examined included physical examinations, bone

radiography, blood chemistry, metabolic disorders,

subclinical ketosis, udder health, and welfare of the

treated cows as well as the health, growth, and

performance of their offspring.

Subtle effects on the incidence and duration of

mastitis are of special interest. Major factors affecting the incidence of mastitis include milking management and herd health programs. However, the

incidence of mastitis and milk somatic cell counts

are also positively correlated with milk yield (58,60,69).

Effects are quite small and amount to an annual

increase of approximately 0.4 cases/cow for each

1,000 kg genetic gain in milk yield. Thus, it will take

very large numbers of cows to detect and evaluate

whether subtle effects, independent of milk-yield

response, occur with the use of bST. Phipps (59)

summarized the incidence of clinical mastitis across

studies totaling over 1,300 cows and found that the

relative incidence of mastitis was not affected by

bST supplementation. Ferguson (27) likewise summarized eight studies reporting mastitis and found

that there was no indication that bST was associated

with increased mastitis infections.

Concern has been raised that even the small

increased incidence of mastitis from higher producing animals will increase the use of antibiotics in

cows. However, Burvenich et al. (14), reported that

recovery time from experimentally induced mastitis

is reduced in cows receiving bST supplement; it will

be of interest to learn whether the same beneficial
Chapter 3---An Emerging Technology: bovine Somatotropin ● 43

effects of bST supplement are observed for naturally

occurring cases of mastitis under field conditions.

ONFARM ENVIRONMENTAL

POLLUTION

Environmental pollution is reduced with bST use

as a result of the gain it yields in productive

efficiency. Substantially less feed is required to

produce the same quantity of milk. This correspondingly reduces the use of fertilizer and other inputs

associated with producing, harvesting, processing,

and storing of dairy feedstuffs.

Total U.S. animal fecal waste could also be

reduced by as much as 6 x 109 kg assuming 100

percent adoption and production of milk at 1988

levels (see table 3-l). Similarly, the productive

efficiency gains with use of bST supplement could

result in an annual reduction of 8 x 109 liters urine

and 8 x 107 kg of urinary nitrogen for the total U.S.

dairy herd (see table 3-l).

Ruminants also produce methane, a gas having a

strong greenhouse effect. Ruminants and animal

waste account for about one-fifth of total worldwide

methane emissions (18), with cattle accounting for

about three-fourths of the livestock methane emissions or about 15 percent of total global methane

emissions (47). Because of the gain in productive

efficiency when bST is used, methane production by

dairy cows could be reduced by as much as 5.5

percent per unit of milk produced. For milk production at 1988 levels, this amounts to an annual

reduction of 8 x 1010 liters of methane in the United

States (see table 3-l).

It has been suggested that even though total

environmental pollution may be reduced, the more

relevant concern is whether animal wastes (manure

and urine) are dispersed widely or concentrated (34).

On large feed-lot farms, located primarily in the

West and South, most feed is not grown on site and

animal wastes are collected and stored. Such operations may represent point-sources of surface and

groundwater contamination. On diversified farms

located in the Upper Midwest and Northeast most

feed is grown on site; animals have access to pasture,

and wastes are left in pasture fields and/or recycled

onto the fields. Some argue that diversified farms are

less polluting than confined operations because

wastes are spread over a more extensive area. A

concern exists that bST will provide the economic

incentive to create more confined operations and

thereby increase pollution of ground and surface

water.

These concerns are questionable. Diversified pasture operations are potential nonpoint sources of

pollution in ground and surface water. If not

properly managed, they could be significant sources

of pollution. By the same token, handling practices

and environmental regulations can minimize the

threat of pollution from confined operations. Effective in-use handling practices include: 1) flush,

lagoon irrigation systems; and 2) mechanical scrapers, storage pit, and tank wagon transport systems. In

some areas, there is also a market for wastes for use

as fertilizer, feed stuff, or fuel. In addition, the U.S.

Environmental Protection Agency has provided

regulations for confined livestock and poultry operations for surface-water protection and several States

and local entities have stringent groundwater protection requirements for these operations (74). It is

expected that these requirements will become quite

common throughout the United States and eventually be applicable to most farming operations. Many

small, diversified dairy operations will be at an

economic disadvantage compared to larger operations in meeting these environmental requirements

(66).

INSTITUTIONAL INVOLVEMENT

IN bST RESEARCH

Research in the technology of bovine somatotropin has involved scientists and financial support

from Federal agencies (NSF, NIH, USDA), State

agricultural experiment stations, and private industry worldwide. This extensive collaboration has

been of tremendous value in developing an understanding of the biology of somatotropin and of

lactation. The number of publications on somatotropin to date is probably unprecedented for an

animal technology not yet approved for commercial

use. The bST literature is substantially larger than

that for many dairy technologies in current use.

Some claim that extensive cooperation has totally

compromised the quality and value of the research

with bST. Kronfeld (44,45,46) has claimed that

academic and government scientists are ‘ ‘indentured’ and ‘‘biased’ because of this association.

Rifkin (63,64) and Epstein (23) have quoted Kronfeld and echoed these claims, repeatedly suggesting

that the reporting of data has involved exclusion of
44 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

sick cows and the suppression and deletion of

adverse or negative results observed with bST

supplementation of lactating cows. While these

individuals offer no specific documentation of

scientific fraud, such claims are not to be taken

lightly. Current events demonstrate that research

fraud is possible. However, a distinguishing feature

of science is that research results are examined and

repeated by others. This mechanism helps to identify

inaccurate research. Published studies on bST have

involved at least 10,000 dairy cows and results have

been verified not only by numerous groups of U.S.

scientists but by many other scientists throughout

the world. The claims of Kronfeld, Rifkin, and

Epstein imply a worldwide conspiracy involving at

least 1,000 animal scientists in academia, government, and industry and hundreds of dairy farmers

involved in the bST experiments. The possibility of

such a conspiracy seems remote.

TIMING OF’ COMMERCIAL

INTRODUCTION

Commercial use of bST requires approval by FDA

and until this occurs, bST cannot be sold legally.

Currently, bST is under review by the FDA and

Federal law prohibits the agency from disclosing

proprietary information on a drug under review.

However, companies interested in bST have been

relatively open about the fact that they are seeking

approval and have published a considerable quantity

of their own proprietary research. In addition, FDA

has published an article using the companies’ data to

demonstrate the safety of bST for human consumption (38). This extensive disclosure of information

on a drug under review is rare.

Each company wishing to market bST must prove

that its product is effective (does what the company

claims) and safe in order to secure FDA approval

(67). The safety evaluation involves three areas:

safety of the animal food products for humans;

safety of the bST supplement to the target animals;

and safety of using bST to the environment. In

addition, each company must prove to the FDA that

their manufacturing process can produce bST to

consistent and acceptable quality standards.

In 1984, the FDA had sufficient scientific information from extensive published literature and

then-unpublished studies (38,67) to make the determination that the milk and meat from bSTsupplemented cows were safe for human consumption. Specific conclusions were:

1. bST is a protein that is digested enzymatically

like any food protein when consumed orally.

2. bST has no biological activity in humans even

if injected.

3. A trace level of bST naturally occurs in milk

and meat but this level is not appreciably

altered in cows receiving bST supplement.

4. The overall composition of milk is not altered

due to bST treatment. The minor changes that

can occur in the first few weeks of treatment

due to shifts in nutrient balance are temporary

and well within the normal variation encountered over the course of a lactation.

Thus, animal products were allowed to be marketed for the remainder of the investigational period.

In all other countries where bST is under review,

the appropriate regulatory agencies have also completed the human safety evaluations and without

exception, allow the milk to be used for human

consumption. By 1990, a few countries completed

all facets of their review and registered bST for

commercial use by one or more companies (Soviet

Union, Czechoslovakia, Bulgaria, Mexico, Brazil,

and South Africa). In March 1991, the Committee

for Veterinary Medicinal Products of the Commission of the European Communities released a

favorable opinion on the application by one company for the marketing of bST.

PRODUCT LABELING

Some States are seriously considering mandatory

labeling of all food products derived from milk of

cows supplemented with bST. The basis for labeling

seems to be a concern about the safety of the

products for human consumption. At least two

considerations need to be addressed.

First is the scientific merit or basis for labeling. If

there is a valid safety concern then the food should

not be marketed for human consumption. Labeling

is not the appropriate method for handling a valid

concern for consumer safety. If the regulatory

system to evaluate food safety is inadequate, then the

system should be changed. Labeling does not excuse

the inadequacy. As just discussed, food safety

concerns have been addressed and the conclusion

reached is that food produced from bST-treated

cows is safe for human consumption (38).
Chapter 3--An Emerging Technology: bovine Somatotropin ● 45

The second consideration is verification. An

effective labeling program requires development

and adoption of appropriate regulations and the

establishment and funding of a system for implementation and verification. In the case of bST, there

is no known test or technology that could be used to

distinguish milk from bST-supplemented cows (38,

67). Indeed, no change in milk composition as a

result of bST supplementation was found in human

safety evaluations by FDA or analogous agencies in

other countries.

CONCLUSIONS

OTA concludes that recombinant bovine somatotropin has no known adverse health effects on the

cows receiving bST supplements or on humans

drinking milk or consuming milk products from

these cows. Recombinant bovine somatotropin is the

first major biotechnology developed for agriculture.

It will have potentially significant impacts on the

dairy industry, based mainly on the fact that it can

produce an average gain in milk per cow of 12

percent per year. However, this technology is not

magic. It is distinguished only by the unprecedented

magnitude of the productivity gains it yields. For

example, the gain in productive efficiency obtained

with bST supplementation would take 10 to 20 years

to achieve using a combination of artificial insemination (using superior sires) and embryo transfer

techniques (see table 3-3). Only the eradication of

mastitis could increase milk yield per cow and

Table 3-3—Comparison of Theoretical Gains in Milk

Yield Per Cow for Different Dairy Technologies

Theoretical annual gain in

Technology milk per Cowa

Artificial insemination (Al) . . . . . . . . . . . . . . . 100 kgb

Al plus sexed semen . . . . . . . . . . . . . . . . . . . . 115 kgb

Al plus embryo transfer . . . . . . . . . . . . . . . . . . 135 kgb

Bovine somatotropin . . . . . . . . . . . . . . . . . . . . . >1,000 kac

aActuaI observed gain would average less because of variation in quality of

management and other factors. For example, observed gain from using

artificial insemination andsuperiorsires is approximately 50 percent of the

theoretical gain.

bFrom Van V[eck (76). Gain would be cumulative for successive generations so long as variation exists in the population.

cFrom Bauman et al. (9)

SOURCES: L.D. Van Vleck, “Potential Genetic Impact of Artificial insemination, Sex Selection, Embryo Transfer, Cloning and Selfing

in Dairy Cattle,” in: New T&nologies in Animal Breeding,

B.G. Brackett, G.E. Seidel, Jr., and S.M. Seidel (eds.) (New

York, NY: Academic Press, Inc., 1981), pp. 221-241; D.E.

Bauman, P.J. Eppard, M.J. DeGeeter, and G.M. Lanza,

“Response of High Producing Cows to Long-Term Treatment

With Pituitary-and Recombinant-Somatotropin,” J. Dairy

Science, 68:1352-1362, 1985.

productive efficiency as much as or more than the

use of bST (6).

For bST to be effective, dairy farmers must be

expert managers. Poorly managed farms, where

animals are stressed, underfed, and/or sick, will have

negligible milk response to bST. In this respect, the

bST-supplemented cow presents the same challenges as any high producing cow—the ultimate

gains to be captured depend not on the technology

per se, but on the management skills of its adopters.

1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

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Chapter 3--An Emerging Technology: bovine Somatotropin ● 47

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48 ● U.S. Dairy Industry at a crossroad: Biotechnology and Policy Choices

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Chapter 4

Emerging Technologies

in the Dairy Industry
Contents

Page

BIOTECHNOLOGY AND THE DAIRY INDUSTRY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

Reproductive Technologies and Transgenic Animals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

Animal Health Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

Food Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .65

KNOWLEDGE-BASED INFORMATION SYSTEMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

Expert Systems and Other Computer-Based Decision Aids.... . . . . . . . . . . . . . . . . . . . . 66

Application of New Information Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

CONCLUSIONS .. .. . .. .. .. ... ... ..... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....67

CHAPTER PREFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Box

4-A. Definitions

Figure

of Commonly

Box

Page

Used Terms . . . . . . . . . . . . . . . . . . . . .. . . . ....... . . . . . . 52

Figures

Page

4-1. Reproductive Technologies Used To Produce Transgenic Animals . . . . . . . . . . . . . . . 54

4-2. Identification and Isolation of Desired Gene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

4-3. Process of Producing a Transgenic Mouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

4-4. Gene Transfer Using Embryo Stem Cell Culture . . . . . . . . . . . . . . . . . . . . . . . . . .

4-5. Nuclear Transplantation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4-6. Preparation of Monoclinal Antibodies . . . . . . . . . . . . . . . . . . . . + . . . . . . . . . . . . . . .

Tables

Table

4-1. Predicted and Actual Sex Ratios of Offspring After Intrauterine Insemination

of Sorted X and Y Chromosome-Bearing Rabbit Sperm... . . . . . . . . . . . . . . . . .

4-2.Monoclinal Antibodies for Diagnostic Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

,.....5 8

... ...60

... ...64

Page

. . . . . . 62

. . . . . . 65
Chapter 4

Emerging Technologies in the Dairy Industry

Bovine somatotropin (bST) is the first major

biotechnology product developed for the dairy

industry. This product has been controversial and

has raised many scientific and socioeconomic questions. BST, however, is not the only new technology

that will affect the dairy industry. Advances in

animal reproduction, animal health, and food processing are occurring, and many of the new technologies being developed use highly sophisticated and

complex biotechnology methods. By comparison,

the biotechnology methods used to produce bST are

actually rather rudimentary; potentially some of

these new technologies could make bST obsolete.

These new technologies will increase the level of

management skills needed to use them effectively;

new information technologies will aid the decisionmaking process. Several conclusions can be drawn

concerning the development of these new technologies:

The dairy industry is on the verge of a

technological revolution. Biotechnology methods that are more advanced than those used to

produce bST are currently under development.

The impact of these technologies, in conjunction with new information technologies in the

not too distant future may rival that of bST.

Assessment and analysis, similar to that of bST

may be warranted for many of these technologies.

The field of animal reproduction is advancing

rapidly. Researchers ‘have significantly improved their understanding of egg development

in the ovary, how to stimulate the release of

numerous eggs at once, and how to achieve

fertilization and development of eggs outside

of the cow. Embryos can be frozen for later use.

Both embryos and sperm can be sexed. It is also

possible to create multiple copies of an embryo,

each of which can be transplanted into a cow

whose reproductive cycle has been adjusted to

be able to accept the embryo and carry it to

term. These new technologies make it possible

to improve herd quality more rapidly than can

be achieved using traditional breeding methods.

●

●

●

●

●

[t is now possible to create transgenicl cattle,

however, the techniques currently used are

inefficient and require the use of thousands of

eggs to produce just one transgenic animal.

These inefficiencies make it too expensive to

commercially produce and market transgenic

livestock. However, scientific breakthroughs

are leading to the development of technologies

that will improve the efficiency of transgenic

animal production and substantially lower the

cost of doing so. Transgenic livestock may

become commercially available in small numbers by the end of the decade.

BST potentially could be supplanted by the

development of transgenic cattle. Dairy cows

can be developed to produce higher levels of

bST so that daily injections or timed release

formulations are no longer needed. Alternatively, genes that code for chemicals that

suppress bST production can be altered in the

cow such that a cow’s normal bST production

will increase.

New biotechnology products are also being

developed to improve animal health. Products

include new vaccines and diagnostic kits, as

well as compounds that enhance an animal’s

ability to fight disease.

Not only are new biotechnology products being

developed for use in livestock production, but

they are also being developed for use in food

processing. New products will improve the

production of milk products such as cheese and

yogurt. They can also be used to detect milk

contaminants.

Effective use of these new technologies will

place a premium on management skill. New

information technologies are being developed

to aid farm management. These new technologies can incorporate individual farm data, with

pertinent information from national databases,

into computer programs that will aid farmers in

the decisionmaking process.

This chapter describes information systems, and

biotechnology methods and products that have been

developed, or are expected to be developed for use

lm~5 whose heredi~ DNA has been augmented by the addition of DNA from a source other than parental germplasm uStig recombmt DNA

techniques.

-51–
52 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

in the dairy industry in the decade of the 1990s.

Many of these technologies are highly sophisticated,

cutting-edge technologies, and as such have not been

extensively discussed in the lay literature. However,

it is important that the potential of these technologies be understood. Given the nature of these new

technologies, the following descriptions are, by

necessity, somewhat technical.

BIOTECHNOLOGY AND THE

DAIRY INDUSTRY

The term biotechnology refers to a wide array of

techniques that use “living organisms (or parts of

organisms) to make or modify products, to improve

plants or animals, or to develop microorganisms for

specific uses’ (46). Under this broad definition,

biotechnology includes many long-practiced dairy

technologies such as animal breeding and cheesemaking. New biotechnologies include recombinant

DNA techniques, cell culture, and monoclinal

antibody (hybridoma) methods (see box 4-A). The

application of these new methods to the dairy

industry has already generated a number of products

for improving milk production, animal health, and

food processing, and will continue to do so. Products

now emerging range from rapid diagnostic tests for

contaminants in dairy products to cows genetically

engineered to produce high-value pharmaceuticals.

Reproductive Technologies and

Transgenic Animals

Animal scientists generally agree that the most

important cause of economic loss in the animal

industries results from reproductive inefficiency

Box 4-A—Definitions of Commonly Used Terms

Antibody: Proteins produced by specific white blood cells (i.e., B lymphocytes) that bind specifically to

foreign antigens in the body.

Antigen: Any substance that elicits a defensive (immune) response.

Cell culture: The growth and maintenance of cells derived from multicellular organisms under controlled

laboratory conditions.

Chromosome: A thread-like structure composed primarily of DNA, that carries the genes which convey

hereditary characteristics; in mammals chromosomes are contained in the nucleus and the X chromosome conveys

female characteristics and the Y chromosome the male characteristics.

DNA (deoxyribonucleic acid): The molecule that is the repository of genetic information in all organisms

(with the exception of a small number of viruses in which the hereditary material is ribonucleic acid-RNA).

Estrus: The period during which a female mammal is receptive to sexual activity.

Estrous cycle: The period of time needed for the reproductive cycle that includes egg maturation and ovulation

in the ovary and preparation of the uterus to receive fertilized eggs. This cycle is under hormonal control and extends

from the beginning of one period of estrus to the beginning of the next.

Hybridoma: A new cell resulting from the fusion of a particular type of immortal tumor cell line, a myeloma,

with an antibody-producing B lymphocyte. Cultures of such cells are capable of continuous growth and specific

antibody production

In vivo: Within the living organism.

In vitro: Outside the living organism and in an artificial environment, e.g., test tube.

Monoclinal antibodies: Identical antibodies that recognize a single, specific antigen and are produced by a

clone of specialized cells.

Recombinant DNA: A broad range of techniques involving the manipulation of the genetic material of

organisms; term is often used synonymously with genetic engineering; term also used to describe a DNA molecule

constructed by genetic engineering techniques composed of DNA from different individuals or species.

Transgenic animals: Animals whose hereditary DNA has been augmented by the addition of DNA from a

source other than parental gerrnplasm using recombinant DNA techniques.

Uteri: The plural for uterus—the organ of the female mammal for containing and nourishing the young during

development prior to birth.

SOURCE: Office of Technology Assessment, 1991.
Chapter 4--Emerging Technologies in the Dairy Industry ● 53 —

(i.e., low conception rates and embryo mortality).

The field of animal reproduction is currently undergoing a scientific revolution. In the 1986 report

Technology, Public Policy, and the Changing Structure of American Agriculture, OTA predicted that,

beginning about the year 2000, eggs matured and

fertilized in vitro and transplanted to a recipient

animal (artificial inembryonation) would in part,

replace natural and artificial insemination in the

animal breeding system, and embryos altered by

recombinant DNA techniques (transgenics) would

be commercially available. In fact, embryos produced by new reproductive methods are currently

being marketed, although at present no transgenic

embryos are commercially available. However, significant new advances are occurring, and the direction and timetable of developments will almost

certainly be affected. This section focuses on recent

advances in reproduction and recombinant DNA

techniques and their application to the dairy industry

during the decade of the 1990s.

It is now possible to select genetically superior

females and induce them to shed large numbers of

eggs (superovulation) that can be matured in vitro

and fertilized with sperm from males selected for

their desirable traits. The resulting embryos can be

sexed, split to make duplicate copies, and stored

frozen until needed. An embryo can then be transferred by nonsurgical techniques into the uterus of a

recipient animal whose estrous cycle has been

synchronized with the stage of development of the

embryo. These new reproductive technologies can,

and are being used to improve the quality of

livestock herds more rapidly than could be achieved

with traditional breeding, although currently many

of these technologies are still relatively inefficient.

The ultimate goal of many workers in the field of

animal biotechnology, however, is to produce animals whose hereditary DNA has been augmented by

the addition of DNA from a source other than

parental germplasm, using recombinant DNA techniques (transgenic animals) (47). Transgenic animals can be created that possess traits of economic

importance including improved disease resistance,

growth, lactation, or reproduction.

Transgenic livestock may also prove to be effective factories for the production of high-value

pharmaceuticals, a development particularly pertinent for the dairy industry (9). Genes that code for

animal proteins (e.g., tissue plasminogen activatorTPA) can be linked to regulatory sequences that

direct high levels of gene expression in the mammary gland. This enhanced expression results in

increased secretion of the desired animal protein into

the milk of lactating females. This protein could then

be extracted and purified from the milk. Transgenic

cows producing pharmaceuticals have not yet been

reported, but these animals are under development in

a number of public and private laboratories. High

levels of milk production coupled with the ease of

milk collection may make this production method

more cost effective than the cell culture systems

currently used in the production of certain pharmaceutical proteins.

The production of transgenic animals is inextricably linked to development of new reproductive

technologies. It is impossible to produce animals

containing foreign DNA in their germlines without

first manipulating the embryo and transferring it to

a recipient animal. New reproductive technologies .

such as superovulation, in vitro egg maturation and

fertilization, nuclear transplantation, and embryo

sexing can be used to upgrade livestock herds.

However, when they are combined with recombinant DNA technologies (the identification, isolation,

and transfer of selected genes), they provide opportunities to efficiently and cost effectively produce

transgenic animals, and to rapidly improve livestock

quality (see figure 4-l). Therefore, advances in

reproductive technologies will be discussed within

the context of their applicability to the production of

transgenic animals, recognizing that they are in their

own right powerful tools for livestock improvements.

Steps in the Development of Transgenic Animals

The production of transgenic animals is a complex process, and involves four major steps. First,

the desired gene must be identified, isolated, and

prepared for insertion into a fertilized egg. Second,

the host cell must be obtained and prepared for gene

insertion. In livestock, the host cells used are

generally fertilized eggs or early stage embryos.

Third, the desired gene must be transferred to the

host cell. And fourth, the resulting recombinant

embryo is duplicated, and the resulting multiple

embryos are transplanted into recipient cows that

have had their estrous cycles synchronized to receive

the embryo. This duplication process allows for the

production of multiple offspring of genetically

superior animals. Advances in each stage, discussed
Figure 4-1—Reproductive Technologies Used To Produce Transgenic Animals

k

Identtflcatlon and Isolatlon

r I

E\ .+;~’’’’’’’nisrandom”

superovulation combined with

egg

I Host cell preparation using 1

superovulation combined with

in vitro egg maturation and

fertilization 1

I I 1

2 to 4

+

2 to 4

embryos Embryo cell embryos

L J multiplication I J

by splitting

1

Embryo multiplication by

nuclear transplantation

and recloning

Egg cell with nucleus removed

Early stage embryo

(less than 64 cells) -

Gene transfer

I

Implantation into cow

whose estrous cycle has ~ m

~ been synchronized to J

Y receive the embryo

E + I

istargete d

”

by gene identification

and isolation.

SOURCE: Office of Technology Assessment, adapted from J.P. Simons and R.B. Land, “Transgenic Livestock,” J. Reprod Fert. Supp/. 34:237-250, 1987.

I
Chapter 4--Emerging Technologies in the Dairy Industry .55

below, are improving the efficiency of transgenic

animal production.

Step 1: Gene Identification and Isolation--Before a foreign gene can be transferred into the

genome of a host cell to create a transgenic

organism, the gene must first be identified and

purified. This is done by a process called cloning.

The tools used to clone DNA include special

enzymes that cut and paste DNA, nucleic acid

fragments that can be used to identify specific DNA

sequences (probes), vehicles used to carry a foreign

gene into a host cell (vectors), and host cells that can

be used to produce multiple copies of the gene. The

host cells used to multiply gene numbers are usually

bacteria. The vectors most commonly used are

bacterial plasmids, circular pieces of DNA that are

easily inserted into bacterial cells and are capable of

independent replication inside the bacteria (see

figure 4-2).

Isolating a single gene is complicated by the fact

that a DNA sample may contain millions of genes.

Researchers must be able to separate the one gene of

interest from all of the other genes. To do this, the

DNA sample containing the desired gene is cut into

pieces with special enzymes (restriction endonucleases). The bacterial plasmid (vector) is also cut

with the same enzyme. The pieces of sample DNA,

including any pieces carrying the desired gene, are

inserted into vectors and the loose ends of the sample

DNA and bacterial plasmid are pasted together

(using the enzyme DNA ligase). These recombinant

DNA vectors are then inserted into bacterial cells,

and the bacterial cells are grown. At this point the

bacterial cells containing the plasmid carrying the

desired gene must be identified and isolated from the

rest. This is done by using a probe, a nucleic acid

sequence that recognizes the desired gene. Once the

bacterial cells containing the desired gene are found,

those cells can be grown in isolation to produce

millions of copies of the vector containing the

desired gene. The vector can be removed from the

bacterial cells, and the desired gene isolated. This

procedure can yield millions of copies of the desired

gene that are free from contamination by other genes

(48).

The purified gene can then be combined with

appropriate regulatory genes that control the circumstances under which the gene is turned on and off.

The purified gene and its regulatory sequences can

be inserted into a vector such as a virus, for example,

Figure 4-2—identification and Isolation

of Desired Gene

DNA containing gene to be isolated

1

Use restriction enzymes

to cut the vector and to

i

cut the DNA containing

.$: the desired gene into

~ pieces I I

f

9,

\

- .

F %

8, $

\

/’

%

/’ ;

--m

‘$

{k

&

,..

’ c7~

1

,,&f@

%, Joining of Vector

\ /

DNA Fragments With

$“ DNA Fragments to be

q, c’ Cloned Using the % k’ -%.?$:2:.... .;” Enzyme DNA Ligase

‘“’ $

7

”

Recombinant DNA Molecules

Introduction ~

into Bacteria tj;~.,; tiim Vector with

( 2

Cloned DNA

Bacterial Fragment

Chromosome

@ 3

j ,

Multiplication of Bacteria Containing the

@@’@@

Desired

Gene To Yield Many Identical Copies of Fragments

SOURCE: Office of Technology Assessment, 1989.
56 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

that will carry these genes into an animal cell and

incorporate them into the genome (see gene transfer

technologies). The tools used to purify genes are

well developed. The major challenge is determining

which genes are to be purified.

Step 2: Preparation of the Host Cell—Because

current technologies used to transfer a gene into a

host cell are inefficient, to get just one transgenic

animal requires the use of thousands of fertilized

eggs. To attain such large numbers of embryos, cows

must be induced to shed large numbers of eggs

(superovulation) that can be matured and fertilized

in vitro. Increased understanding of the control of

ovarian functions is improving the efficiency of

obtainin g sufficient numbers of fertilized eggs.

Control of Ovarian Functions-The lack of

highly repeatable, efficient means for inducing

superovulation is a major constraint. Induction of

superovulation requires detailed knowledge of the

hormonal factors that control the development of the

egg in the ovary. The process of egg development

has been subjected to intense investigation and a

number of significant advances have been made

during the past 5 years. Studies that have explored

the basic mechanisms controlling egg growth and

maturation, and corpus luteum2 function, have

paved the way for developing even more precise

methods for regulating the estrous cycle, producing

superovulation, and reducing the heavy losses due to

early embryo deaths.

Perhaps the most important development in ovarian physiology in recent years is the discovery of the

ovarian hormone inhibin, which decreases the ovulation rate.3 Some breeds of animals with exceptionally high ovulation rates, such as the Booroola

strain of Merino sheep in Australia, are known to

have low levels of circulating inhibin (4). Cattle

immunized against inhibin have lower circulating

levels in their blood and show increased ovulation

rates (21). The genes controlling inhibin production

have been cloned and the potential exists for

producing transgenic animals in which these genes

are repressed or deleted.

Progress has also been made in understanding the

control mechanisms that regulate corpus luteum

function and its production of progesterone, a

hormone that regulates the length of the estrous

cycle and helps maintain pregnancy. This understanding paves the way for development of more

precise methods for regulating the estrous cycle,

which is needed to synchronize surrogate mothers,

and for producing superovulation. Superovulation

treatments are initiated when the ovaries are under

the influence of progesterone. Currently, superovulation treatments use highly purified hormones

produced by recombinant DNA technology and

produce, on average, about 10 viable eggs per

treatment (compared to the 1 egg a cow normally

produces per ovulation) (21). As the new knowledge

of the factors controlling egg development and

corpus luteum function is applied, the number of

viable embryos produced by each superovulation

treatment is expected to increase.

In Vitro Maturation and Fertilization of Eggs—In

vitro maturation and fertilization of eggs recovered

by superovulation provides a means of overcoming

the problem of livestock reproductive inefficiency.

Normally, a bovine ovary contains about 50,000

immature eggs at puberty, however, on average only

3 to 4 of these eggs will result in the births of live

calves during the animal’s lifetime. Using present

superovulation methods, about 10 viable eggs can be

harvested from the ovaries of 1 treated cow and

about half of these develop into embryos suitable for

transfer. Improved superovulation technology may

lead to the recovery of more eggs suitable for in vitro

fertilization such that the number of live births

resulting from a superior animal could be quite high.

In vitro fertilization occurs only when a capacitated sperm (i.e., a sperm specially prepared to

penetrate the egg cell membrane) encounters an egg

at an optimal maturation state. Great progress has

been made in understanding the factors involved in

egg maturation and sperm capacitation in livestock.

As a result, offspring have been produced in cattle,

swine, sheep, and goats following in vitro fertilization (16) and attempts to market embryos produced

with these techniques are already underway.

Step 3: Gene Transfer Technologies—Achieving the goal of transgenic animal production requires

the development of efficient and cost effective ways

to transfer the selected genes to an embryo. Mice

were the first transgenic mammals created (see

figure 4-3), and were produced by microinjecting

z~e CO~u.S lute~ is a temp~~ endocrine organ that is produced at the site of ovulation dtig each W@Ous cYcle.

%hibin decreases owlation rates by suppressing the secretion of follicle stimulating hormone (FSH), a hormone produced by tie Pitiw gl~d.
Chapter 4--Emerging Technologies in the Dairy Industry ● 57

Figure 4-3-Process of Producing a

Transgenic Mouse

YImplant injected embryos

into pseudopregnant

Q

4’

Fetal Developmental regulation

expression / . Live birth

\

test for transgene

e

Founder animal

1 Breed transgenics

6 3

A & ~ 2

Fetal/neonatal pup

Adult

SOURCE: Sally A. Camper, Fox Chase Cancer Center.

cloned DNA into a fertilized egg4 (32). Alternatively, viral vectors can be used to transfer cloned

DNA into a host embryo (14). The embryo is then

transferred to a recipient animal whose estrous cycle

has been synchronized to accept and carry to term,

the developing embryo.

A number of transgenic cattle, pigs, sheep, and

chickens have been produced by these techniques,

however, they are of limited use because of the high

cost and low efficiency of microinjection techniques, and the absence of appropriate viral vectors

for use in most livestock species. Additionally, DNA

transferred by these methods is inserted randomly

into the host genome, resulting in a lack of control

of the gene transfer process (20).

Because of the deficiencies encountered with

using viral vectors or microinjection methods to

create transgenic livestock, alternative methods are

being sought. A promising new method for generating transgenic animals has recently been developed

in mice and may be applicable to other mammals.

This new technique uses stem cells derived from an

embryo. Stem cells are cells that are normally

undifferentiated, that is, they do not become specialized tissue cells such as muscle, brain, liver cells,

etc. However, stem cells retain their ability to

become specialized cells when given the proper

stimuli (i.e., they are pluripotent).5 These stem cells

can be used as vectors to introduce selected genes

into a host embryo. This method has several

significant advantages over microinjection methods,

the most profound of which is that for the first time,

it is possible to insert DNA at specific, predetermined sites within the genome of the stem cells (8).

Targeted insertion is possible because stem cells

have an intrinsic ability to recombine similar (homologous) DNA sequences, which results in the

replacement of the endogenous gene with the desired

gene.

Stem cells must first be isolated (see figure 4-4).

An early stage embryo is cultured on a thin layer of

specially prepared cells. The proliferating embryo

cells are recultured until individual stems cells can

be isolated. These individual stem cells can then be

cultured indefinitely. At this stage, DNA sequences

containing desired genes can be inserted into the

stem cells.6 A genetically transformed stem cell is

then microinjected into an immature embryo to

produce a chimera, an organism that contains cells

from more than one source. If the stem cells are

incorporated into the germ lines of these chimeric

animals, then these animals can be interbred to

obtain offspring that are homozygous for the desired

trait (8).

Application of the gene targeting method makes

possible a broad range of phenotypes for transgenic

animals that could not be produced economically

using direct microinjection or viral vectors. Targeted

gene insertion allows endogenous genes to be

4SPcific~Iy, tie DNA is ~ject~ into tie male Pronucleus of the fertilized egg. The pronucleii are the egg ~d sPerm nucleii Present after tie ‘Pm

penetrates the egg membrane.

Splmipotency help me stem cells attractive vectors of DNA transfer. While in tissue culture, DNA Cm emily be tiefied ~to stem ce~s. men

stem cells are injected into an early stage embryo, the conditiom for tissue specialization are present, and stern cdls undergo the normal tissue

development that occurs as the embryo develops during pregnancy. Thus, using stem cells provides an efficient means to transfer DNA.

6Me~ods US~ inc]ude viral infmtion and use of an electric pulse to make cell membranes leaky (electropomtion).
58 ● U.S. DairyIndustry at a Crossroad: Biotechnology and Policy Choices

Figure 4-4—Gene Transfer Using Embryo Stem Cell Culturea

A

-,: I - t-

- 1 -

–7 1- 1- -1 , :

1- .

, . . “ ;: I - -. ‘ +–

,—, - .(

, . .

t

A mouse embryo (blastocyst)

is donated.

The embryo is cultured

onto a thin layer of

specially prepared

(feeder) cells.

The embryo attaches to

the cell layer, and the

inner cells of the embryo

begin to proliferate.

Groups of these differentiating

embryo cells are separated,

recultured and single colonies

of embryonic stem cells are

identified and transferred.

Single cells are reseeded

onto the feeder cells. Foreign

K“’’’O t

he~ <

l < l

F r

#+-’-JTJ

A second mouse embryo is donated

and is injected with a cultured

embryonic stem cell. This embryo

is transplanted into a surrogate

mouse, which gives birth to a

chimera (a mouse with cells from

both parent embryos). Mating two

chimeras gives rise to offspring

with the desired traits.

. - ---

Y’

.. . ( -‘“* 3

: 

“

aThis technique is currently developed only for mice and hamsters and possibly rabbits and swine. It is not yet developed for cattle.

SOURCE: M.R. Capecchi, “The New Mouse Gene!ics: Altering the Genome by Gene Targeting,” Trends in Genetics 5:70-76, 1989.
Chapter 4--Emerging Technologies in the Dairy Industry ● 59

inactivated or replaced with modified forms of the

gene, such as one that is expressed at a higher level,

has anew pattern of tissue specific expression, or has

a modified biological activity.

Perhaps the most significant advantage of the

gene targeting approach is that it allows for endogenous genes to be effectively removed. Genes

can be inactivated by targeting insertion into an

essential region of the gene. This fact is of particular

interest to the livestock industry, because inactivation of genes that have inhibitory physiological

effects is likely to result in improvement in a number

of productive traits. For example, bovine somatostatin is a hormone that inhibits bovine somatotropin

production; inactivation of this gene would result in

increased endogenous somatotropin secretion and,

presumably increased milk production and more

efficient growth. If successful, this technology

would supplant the need to administer bST exogenously to increase milk production (see ch. 3).

The genes controlling the production of inhibin, the

ovarian hormone that reduces ovulation rate, is yet

another example. The ability to inactivate genes also

provides a powerful research tool that allows scientists to study the function of genes in vivo. The

absence of a method to produce embryo stem cell

lines from cattle is currently preventing the use of

the gene targeting approach in the dairy industry,7

however, a number of laboratories are trying to

develop this technology.

Step 4: Embryo Multiplication-The production

of multiple copies of a genetically engineered

embryo is the final step in the development of

transgenic animals. Efficient and inexpensive multiplication technologies are tremendously important

for improving the efficient development of transgenic

animals. Multiple copies of a mammalian embryo

were first produced by physically splitting an early

embryo into halves, giving rise to identical twins

(21). If the embryo is divided more than twice,

however, few offspring survive. Thus, no more than

four identical animals can be produced by splitting

and generally only two embryos are produced by this

method. This procedure is already used in the cattle

embryo transfer industry, nearly doubling the number of offspring produced.

A more efficient and promising method of producing multiple copies of an embryo is by a technique

called nuclear transplantation. Basically, the procedure involves the transfer of a nucleus from a donor

embryo into an immature egg cell whose own

nucleus has been removed. The recipient egg cell is

activated by exposure to an electric pulse, allowed to

develop into a multicelled embryo, and then used as

a donor in subsequent nuclear transplantations to

generate multiple clones. This procedure (outlined

in figure 4-5) has been used successfully with cattle

(7,35), sheep (42,49), and swine (36). Using this

technique, hundreds of pregnancies have already

been produced in cattle and recloning has been

performed successfully resulting in as many as eight

calves from one embryo (28).

The value of this technique to the dairy industry

is enhanced by the ability to successfully transfer

nuclei from frozen embryos into eggs whose nuclei

have been removed. Conception rates obtained after

transfer of embryos produced by nuclear transplantation are variable, but rates as high as 50 percent

have been obtained. However, embryo losses after

transfer are higher than normal, resulting in actual

pregnancy rates ranging from 15 to 33 percent (7).

Combining the techniques of in vitro fertilization,

embryo cloning, and artificial estrous cycle regulation will likely result in major changes in dairy cattle

breeding and in the rates of genetic improvement.

While significant advances in transgenic animal

production have been made, it is unlikely that

transgenic animals will be commercially available

before the end of the 1990s at the earliest. The ability

to produce transgenic cattle possessing traits of

economic value is currently limited by the absence

of embryo stem cell technology and the lack of

knowledge about the relationship between the expression of a specific gene and the physiological

consequences. While the techniques for isolating

and sequencing bovine genes are now straightforward, understanding of the functions of the genes

has lagged. Analysis of gene function is complicated

by the fact that many traits are controlled by multiple

genes. Thus, manipulation of such traits will require

detailed understanding of these genes and their

interactions. Ultimately identifying and understanding the physiology of the major genes controlling

lactation, reproduction, and disease and stress resistance in dairy cattle is needed. An active genome

mapping program could help enhance these developments.

7~e stem ce~ tec~o]on has been developed for mice, titers, ~d swine.

292-860 0 - 91 - 3
60 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Figure 4-5—Nuclear Transplantation

— 1 — , — , — , —,

An embryo is nonsurgically removed

from a donor cow or is produced by

in vitro fertilization.

Individual embryo

are removed.

cells

Each embryo cell is injected into

a specially prepared egg cell that

has had its nucleus removed. An

electric pulse is administered to

cause fusion.

Each egg cell is grown to a

multicell embryo at which point

the cloning procedure can be repeated

or

the embryo can be transplanted to

a cow that eventually gives birth.

SOURCE: ~’fice of Technology Assessment, adapted from R.S. Prather and N.L. First, “Cloning Embryos by Nuclear Transfer,” Genetic Engineering of

Anima/s, W. Hansel and B.J. Weir (eds.), Journa/ of Reproduction and Ferti/ify~td, Cambridge, UK, 1990, pp. 125-134.
Chapter 4--Emerging Technologies in the Dairy Industry . 61

Sexing of the Offspring

The availability of a technique to preselect the sex

of the progeny is of great economic potential for the

dairy industry where females are the major income

producers and artificial insemination is already

widely used. Until recently, none of the methods

resulted in the degree of separation needed for

commercial use. However, recent advances in the

separation of the X and Y sperm, and sexing of the

embryo have been made.

Separation of the X- and Y-Beating Sperm—It

has long been a goal of mammalian physiologists t o

develop a method for effectively separating X and Y

chromosome-bearing sperm to control the sex of the

offspring. Most sperm separation techniques are

based on potential differences in the size and density

of the two sperm types. 8 These methods, however,

have met with limited success (41).

Development of cell sorting techniques based on

the differences in sperm size and fluorescence of

sperm DNA (flow cytometric measurements) has

provided the first effective method to sort the sperm

cells. Johnson et al. (24) recently reported successful

separation of intact viable X and Y chromosomebearing sperm using this method (see table 4-l).

Although the difference in DNA contents of the X

and Y chromosome-bearing sperm in rabbits amounts

to only about 3 percent, 94 percent of the rabbits

(does) inseminated with X-bearing sorted sperm

produced females and 81 percent of the does

inseminated with Y-bearing sorted sperm produced

males. Commercial use of this process is limited, at

present, by the number of sperm that can be sorted

per hour and by increased embryo mortality observed in the embryos produced after insemination

with the sorted sperm. Neither of these factors is

thought to represent an insurmountable difficulty.

Embryo Sexing—The most accurate method for

sexing embryos is to create a picture of the number,

size, and shape of the chromosomes contained in the

embryonic cells (karyotyping). However, this method

requires removal of about half of the cells of

early-stage embryos, which decreases embryo viability and limits the number of embryos that can be

transferred. Another method uses antibodies to

detect proteins (antigens) unique to male embryos.

This method is not damaging to the embryos and

encouraging results have been obtained in one

laboratory (2), however, the technique yields variable results and has not been widely adopted.

More recently, the sex of bovine embryos has

been determined by using fragments of DNA that are

contained only on Y chromosomes as a means of

identifying the same DNA fragments in the embryo

(6). Due to its chemical structure, a fragment of

DNA will combine with a second DNA fragment

that has a corresponding nucleic acid sequence.

Therefore, a fragment of DNA that is specific to

males can be used as a probe to identify male DNA

fragments in the embryo. Combined with technologies that multiply the number of copies of the DNA

fragments, this method determines the sex of the

embryo using only a few cells. It is rapid (about 6

hrs) and extremely accurate, but may be overtaken

by the rapidly developing technology, described

above, for separating X and Y chromosome-bearing

sperm.

Animal Health Technologies

Biotechnology is rapidly acquiring a prominent

place in veterinary medical research. Initially applied to vaccine development, it most recently has

contributed to efforts to develop diagnostic procedures and to improve detoxification systems.

Vaccines

Vaccines are agents that stimulate an effective

immune response but do not cause disease. Traditional methods of vaccine development involved

killing or modifying the pathogenic organism to

reduce the potential for disease while preserving its

ability to induce an immune response. Recombinant

vaccine development involves either deletion or

inactivation of genes necessary for disease, or

insertion of immunizing genes into nonpathogenic

vectors.

Gene deletion technology has been successfully

used to develop both viral and bacterial vaccines. A

naturally occurring mutant of E. coli, for example,

has been shown to provide protection against

gram-negative bacterial infections in cattle and

swine (15,18). Live Salmonella modified to prevent

gMethods used me differenti~ s~imentation techniques including differential velocity sedimentation free-flow electrophoresis, and Convection

counter streaming galvanization.

%e antibodies are attached (labeled) to a fluorescent compound to allow for detection.
Table 4-1—Predicted and Actual Sex Ratios of Offspring After Intrauterine Insemination of Sorted X and Y Chromosome-Bearing Rabbit Sperm

Percentage and number of offspring

Number of does Total of Predicted a Actualb

Treatment of sperm Inseminated Kindled young born Males Females Males (N) Females (N)

.—

Sorted Y . . . . . . . . . . . . . . . . . . . . . . . . . 16 5 21 81 19 81 (17) 19 (4)

Sorted X . . . . . . . . . . . . . . . . . . . . . . . . . 14 3 16 14 86 6 (1) 94 (15)

Recombined X and Y . . . . . . . . . . . . . . . 17 5 14 50 50 43 (6) 57 (8)

Total ... , . . . . . . . . . . . . . . . . . . . . . . 47 13 51 — — 47 (24) 53 (27)

aRepresents the results of reanalysis for relative DNA content of aliquots of sorted X- and Y-bearing sperm populations.

bRepresents actual biflhs.

SOURCE: L.A. Johnson, J.P. Flook, and H.W. Hawk, “Sex Pre-Selection in Rabbits: Live Births From X and Y Sperm Separated by DNA and Cell Sorting,” Bio/. Reprcd. 41 :199-203, 1989.
Chapter 4--Emerging Technologies in the Dairy Industry ● 63

reproduction in vivo have also proven to be effective

vaccines for cattle (12).

The first gene deletion viral vaccine to be

approved and released for commercial use was the

pseudorabies virus vaccine for swine (26,30). Initially, a single gene deletion reduced the virulence of

the virus. Since then, other genes have been deleted

with a continuing reduction of virulence.

Vaccines can also be created by inserting into

pathogens, genes that produce protective antigens

that reduce the ability of the pathogen to cause

disease. 10 Some of these vaccines, however, will

have to be carefully tested because they have a slight

potential to cause human infection (31). Others are

in the early developmental stages (notably herpes

virus vaccine and adenovirus vaccine).

Immunomodulators

Immunomodulators are chemical compounds that

boost or accentuate immune response. Several such

compounds (e.g., interleukins and interferon) have

been identified in mammals, and the genes encoding

some of these compounds have been isolated and

cloned into bacteria (31). Mechanisms by which

these regulatory proteins modulate immune response is now being investigated in domestic

animals (l). Biotechnology is being used to identify

and replicate these compounds so that their function

can be investigated.11

Interleukin genes and genes for compounds that

cause immune responses in animals (antigens) are

being inserted together into viral or bacterial vaccines. This combination could possibly enhance the

immune response of the animal and lead to increased

protection against the antigen. The recombinant

interleukins produced in bacteria or other expression

vectors may also be used therapeutically to assist in

overcoming certain infections.

Diagnostics

Safe, accurate, rapid, inexpensive, and easy-touse diagnostic procedures are critical to the dairy

industry at virtually all points in the production

process. Examples of diagnostic tests include pregnancy tests and assays for pathogenic organisms.

Many of the currently used diagnostic tests are

costly, time consuming, and labor intensive, and

some still require the use of animal assay systems.

Monoclinal antibodies and nucleic acid hybridization probes can be used to produce simpler, easily

automated, and highly sensitive and specific diagnostic procedures.

Antibodies are proteins produced by the body in

response to foreign chemical substances. Monoclonal antibodies are produced by a cell line expressing

only a single antibody type (see figure 4-6). They

can be used to prevent disease,12 and are the primary

tools for biotechnology-based diagnostics. At least

15 different rapid diagnostic tests are on the market

or will be soon. These tests are highly specific and

most lend themselves to automation, potentially

allowing their application in mass screening systems

for disease surveillance and control. Some of the

tests have been adapted to field use and can be used

by veterinarians or producers. The rapid commercialization of these products is having a significant

impact on animal health management and disease

control.

Monoclinal antibodies are also being used in

enzyme-linked-immunoabsorbent-assay (ELISA)

systems to provide sensitive, quantitative blood

assays (see table 4-2) of toxins, hormones, chemicals

(e.g., pesticide and antibiotic residues), and a variety

of antigens including microbial agents (19,29,34,38).

Many of these tests are commercially available. In

some instances monoclinal antibody diagnostics

have been used to replace bioassays such as mouse

inoculation tests.

“Nucleic acid hybridization’ can also be used to

diagnose the presence of microbes and parasites.

Such assays rely on the bonding of a specific DNA

or RNA segment to complementary RNA or DNA

fragments in a test sample. Specific segments

(probes) are available to detect viruses such as

lo~e first veterinq recombinant viral vaccine was the vaccinia vectored vesicular stomatitis vaccine (27). This has been followd by the vaccfiia

vectored rabies and rinderpest vaccines (3,5,50).

1 lclon~ ~terle~n genes, such as bovine ~p~, beta and ~mm intefieron, bov~e interlefin.2 ~L.2) etc. have been s~died both h vitro ~d h

vivo.

12A comerci~ Prepmation of monocloMI antibodies directed to the K-99 pilus antigens of pathogenic E. cOIi, for examP1e, Prevents ~~hea h

newborn calves (31).
64 . U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Figure 4-6—Preparation of Monoclinal Antibodies

*

* Mouse is

immunized With

A

a foreign

substance or

“antigen”

.

. . - - :. - Spleen is

1 removed and

minced to

release antibody

Producing cells

(B lymphocytes)

a“. ,

.

.,”. >

. ..’:. --,..t.t

.

Myeloma cells

are mixed and

fused with

B lymphocytes

1

SOURCE: Office of Technology Assessment. 1988.

bluetongue, bovine virus diarrhea, and foot and

mouth disease as well as many parasites and

bacterial diseases. The major limitation of this

technique is the small amount of target nucleic acid

present in some samples. Also, the most reliable

methods use radioactively labeled probes, and reY Mouse myelomaa

- % %

(tumor) cells

are removed

t and placed in

u tissue culture

0

“.

.,,. . . , ~.

:... s:,.: Cells divide in

liquid medium

J

u

The products of this

fusion are grown in a

selective medium. Only

those fusion products

which are both “immor.

tal ” and contain genes

from the antibody-pro.

ducing cells survive.

These are called

“hybridomas.”

Hybridomas are cloned

and the resulting cells

are screened for antibody production. Those

few cells that produce

the antibodies being

sought are grown in

large quantities for

production of monoclonal antibodies,

quire expensive equipment and trained technicians,

thus precluding their use in the field. Alternative

calorimetric techniques currently in development

will replace the radioactively labeled probes and

make the use of this technology more commercially

attractive.
Chapter 4--Emerging Technologies in the Dairy Industry ● 65

Table 4-2—Monoclinal

Antibodies for Diagnostic Tests

E. coli K99 antigen

Pseudorabies virus antibody

Avian Ieukosis virus antigen

Equine infectious anemia antibody

Avian reovirus antibody

Bluetongue virus antibody

Bluetongue virus antigen

Brucella abortus antibody

Avian encephalomyelitis antibody

Bovine progesterone

Sulfa methazine in milk

Crytosporidium

Bovine leukemia virus

Bovine herpes virus

Aflatoxin B

Sulfamethazine-swine

SOURCE: B.1. Osburn, “Animal Health Technologies,” commissioned

background paper prepared for the Office of Technology

Assessment, Washington, DC, 1990.

Food Applications

Dairy products will be among the first food

products to be impacted by biotechnology. For

example, during the next decade, the genetically

engineered version of the enzyme rennet, recently

approved by FDA for use in cheese manufacturing

systems, will replace the enzyme preparation normally extracted from the forestomach of calves.

Other enzymes, which are added to the curd to

accelerate ripening, or to produce dairy products

acceptable for digestion by lactose-intolerant individuals, will also be produced more economically by

engineered microorganisms (22).

Dairy starter cultures are living microorganisms

used for the production of fermented dairy products

including cheese, yogurt, butter, buttermilk, and

sour cream. They have been safely consumed by

humans for centuries and serve as ideal hosts for the

production of these natural foods. The metabolic

properties of these organisms directly affect the

properties of the food product including flavor and

nutritional content. In order to improve various

properties of food products, food microbiologists

attempt to manipulate the traits of the microorganisms, primarily through mutation and selection. The

cloning and gene transfer systems developed in the

1980s are being used to construct strains with

improved metabolic properties more rapidly and

precisely than is possible with traditional methods.

The development in this decade of new strains with

precise biochemical traits will have an impact on

several aspects of dairy fermentation, including

production economics, shelf-life, safety, nutritional

content, consumer acceptance, and waste management (22).

Although much of the current work in new strain

development has focused on the use of E. coli and

other nonfood microorganisms, there are distinct

advantages to engineering starter cultures for producing high-value foods. For example, construction

of cultures resistant to attack by viral infection will

impact processing costs by eliminating waste. Cloning of the genes responsible for ripening of aged

cheeses will decrease storage costs by accelerating

ripening. Production of natural preservatives such as

nisin, effective in inhibiting foodborne pathogens

and spoilage organisms, will help ensure the safety

and extend the shelf-life of fermented dairy products. Cloning of the gene(s) responsible for enzymatic reduction of cholesterol or modification of the

degree of saturation of milk fat will improve the

nutritional quality of fermented dairy products. The

ability to engineer strains capable of producing

enhanced flavors or natural stabilizers will influence

consumer acceptance of fermented dairy foods.

Engineered yeast strains capable of fermenting

the lactose in whey to value-added products, such as

vitamin C, biofuels such as ethanol and methanol, or

pharmaceuticals, will facilitate management of this

waste product. Whey protein could potentially be

used to produce specialty chemicals with biotechnology.

Nucleic acid probes and monoclinal antibodies

can be used to analyze raw materials, ingredients,

and finished products for pathogenic organisms,

bacterial or fungal toxins, chemical contaminants

(i.e., pesticides, heavy metals), and biological contaminants (i.e., hormones, enzymes). Animal cell

cultures may partially replace whole animal systems

to test for acute toxicity. Biosensors maybe used to

monitor food processing, packaging, transportation,

and storage (22).

KNOWLEDGE-BASED

INFORMATION SYSTEMS

The economic vitality of an animal enterprise is

dependent on expert managers who formulate,

implement, and continually fine-tune relevant plans

and goals in order to optimize resource use and

output (10). However, producers may have difficulty

evaluating the many interrelated factors that go into
66 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

such planning (17). Even a relatively simple animal

operation requires that complex decisions be made,

based on simultaneous consideration of dynamically

changing factors related to risk, efficiency, disease,

milk production, gestation status, and weather. With

technology changing so rapidly, it has become

almost impossible for agricultural managers to

balance all of the facets of milk production now

under their control (45).

Many producers rely on consultants and experts to

sift through the data and information needed for

informed management decisions. In addition, computers have come to play a significant role in

dairying, an industry that historically has used

records to make management decisions. Initially,

data resided in mainframe computers. This allowed

for professional maintenance of the database, but the

ultimate user-producer had limited access to that

database.

Examples of database access via telecommunication systems include the Direct Access to Records by

Telephone (DART) system, run by the Dairy Records Processing Center at Raleigh, North Carolina;

and the Remote Management System (RMS) available through Northeast Dairy Herd Improvement

(DHI). Although dairy records processing centers

(DRPCs) like the one at Raleigh have not developed

software for onfarm data calculation and information storage, the private sector has. Pollock and

Fredericks (33), for example, offer a microcomputerbased diagnostic program with which producers can

avoid the time, recurring costs, and problems of

phone access to a distant mainframe.

As computer languages have evolved and microcomputers decreased in price and gained computing

capacity, database accessibility has increased. Microcomputers provide for direct, rapid delivery of

management data, as well as more efficient data

handling and user interfaces. They have, accordingly, revolutionized production record-keeping,

and made possible onsite data manipulation and

farm-level processing of information (45).

Expert Systems and Other Computer-Based

Decision Aids

Management decisions rest on a knowledge base

consisting of two kinds of information: that which is

widely shared and generally publicly available

(domain information); and rules-of-thumb judgments and sometimes educated guesses (heuristics),

which typically characterize human decisionmaking. Both kinds of information are fundamental to

computer-based expert systems (11), the objective

of which is to raise the performance of the average

producer to the expert level (39). Expert systems

effectively and rationally integrate numeric, judgmental or preferential, and uncertain information, all

of which come into play in the biologically based,

weather-influenced production systems that typify

animal agriculture (23). Another promising new

information technology is the management-information system, with which managers can test the

outcome of various management alternatives. Decision-support systems also hold high promise of

enabling managers to balance production inputs in a

way that maximizes response (output).

Expert systems, knowledge-based systems, or

decision-support systems offer the potential of

bringing the consultant to the farm through the

microcomputer. An expert system provides a flexible yet structured approach to many problems that

Extension specialists now solve relatively routinely

(43). Interest in these systems is beginning to emerge

as a field of research and development in agriculture,

reflecting both industry awareness and appreciation

of new information-management technologies (13).

With the widespread introduction of specialized

development tools, expert system construction has

accelerated (25,37). For example, development of

expert systems was, until recently, restricted to

expensive LISP (a computer language) processing

machines and mainframe computers. Recent advances in hardware and software have made possible

the development of reasonably sized expert systems

on microcomputers. Newly released expert system

shells have removed the necessity to program in

LISP (44). While conventional computer programs

manipulate data (11), expert systems manipulate

knowledge and help determine which data are useful

to the decisionmaker. They are not competitors but

extensions to conventional computer programs.

Application of New Information Technology

Pressure for the management expertise offered by

these new information technologies will grow in the

1990s as farms increase in size, new technologies

emerge, prices fluctuate, and consumer concern

about food safety and diet increases. Problem

solving and successful adoption of new agricultural

technologies like bST will be facilitated if the

knowledge acquired from research and the expertise
Chapter 4-Emerging Technologies in the Dairy Industry . 67

acquired in practice are combined and made readily

available in easy-to-use forms.

Indeed, the possibility of fusing expert knowledge

from different domains (extension, research, producer/

managers) into a cohesive, accessible structure

might be the most promising advantage of the new

information technologies (11). This will allow

management opportunities to be maximized, a wider

group of individuals to be reached, and specialists to

allocate more time to new areas of concern. Expert

systems, for example, will provide farmers with

online access to needed knowledge: the human

expert farmers would otherwise rely on gains time

for research and for expanding his or her expertise

(40).

New information technologies will also revolutionize dairy record-keeping. For example, milk data

are typically recorded once during a 30-day interval

and extrapolated to predict total milk for that period.

With new automatic metering devices, milk weights

could be recorded from each milking, For a 305-day

lactation, this would increase the data points from

12 to 710, if the cow is milked twice a day. With

appropriate data-handling tools, this information

could be tied to other information, such as measures

of milk conductivity and temperature, and profiles

developed to monitor cows for estrus. This would

allow increased reproductive efficiency, while reducing labor requirements, and decrease the need for

visual observation.

CONCLUSIONS

Advances in biotechnology and information technology will revolutionize the dairy industry. Attention by farm groups, consumers, and policymakers

has focused on the first major biotechnology product

from this new era—bST. In the future bST will be

surpassed by more advanced biotechnology methods in animal reproduction, transgenic animal production, and animal health technologies. The more

advanced technologies, for example, will increase a

cow’s endogenous bST production and milk synthesis by inactivating genes that inhibit bST production,

eliminating the need to administer bST exogenously.

Similar advanced technologies will produce higher

quality cows, improve disease prevention and management, and allow for the production of high-value

pharmaceuticals in milk.

These advanced biotechnologies will require

sophisticated management capability to use them

effectively. Knowledge-based information systems

will assist in providing this management capability.

Expert systems, for example, can help farmers

integrate information for decisionmaking. To effectively use these systems farmers will need access to

software that is specific to their individual situation

and feasible for use in a variety of economic and

policy situations.

The technologies from this new era are in various

stages of development. Some of these technologies,

such as embryo transfer, recombinant DNA vaccines, and information systems, are already commercially available or will be soon. Other technologies,

such as transgenic cattle and advanced reproductive

technologies, will not be available until the end of

the decade. The next chapter examines the collective

effect these emerging technologies, including bST,

will have on the dairy industry in the economic and

policy environment of the 1990s.

1.

2.

3.

4.

5.

6.

7.

8.

9.

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Chapter 5

Economic and Policy Impacts of

Emerging Technologies on

the U.S. Dairy Industry

TECHNOLOGY ADDITION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

NATIONAL AND REGIONAL IMPACTS UNDER ALTERNATIVE

DAIRY POLICIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ● . . . . .

Fixed Price Support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..

Support Price Adjusted by Trigger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . +.... . . . . . +.

Milk Production Quota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . .

Regional Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

NATIONAL IMPACTS UNDER ALTERNATIVE DEMAND AND

SUPPLY SCENARIOS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Small Demand Reduction . . . . . . .. ....... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Large Demand Reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . , . . . . . . . . . . . . . . .

Large Supply Increase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

FARM LEVEL IMPACTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Alternative Dairy Policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Alternative Demand and Supply Scenarios . . . . . . . . .... . . . . . . . . . . . . . . . . . . . . . .

Enhancing the Survival of Traditional Farms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

BENEFICIARIES OF TECHNOLOGICAL CHANGE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

INTERNATIONAL TRADE PROSPECTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

POLICY IMPLICATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. .. .. .. .. .. ..+. . . . . . . . . .

CHAPTER PREFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .+ . . . . . . . . . . . . . . . . . . . .

73

74

74

74

75

75

76

76

76

77

78

78

80

82

82

84

84

85
Figures

Figure Page

5-1. Comparative bST Adoption Curves Projected for the Pacific, Lake States,

and Northeast Regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

5-2. Projected Impact of a Temporary Demand Reduction on Government Milk

Purchases Under Trigger Price Policy, 1990-98 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

5-3. Projected Impact of a 10-Percent Permanent Demand Reduction on Government

Purchases Under Alternative Dairy Policies, 1990-98 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

5-4. Dairy Price Indexes at Three Market Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

5-5. Farm and Retail Prices of Beverage Milk per Half Gallon . .. . .......+. ., ...., ..+ 83

5-6. Farm, Wholesale, and Retail Prices of Cheese . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

Table

5-1.

5-2.

5-3.

5-4<

5-5.

5-6.

5-7.

5-8.

5-9.

Tables

Page

Forecasted Adoption Rates for bST Technology, Selected Years, 1991 -2000 . . . . . 73

Level of Milk Production, With and Without bST, Under Alternative Policy

Scenarios, 1990-98 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

Level of CCC Purchases, With and Without bST, Under Alternative Policy

Scenarios, 1990-98, Milk Equivalent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .74

Summary Characteristics of Representative Moderate- and Large-Size

Dairy Farms, by Region . . . . . . . . . . . . . . . ... , . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

Impacts of bST Adoption on the Economic Viability of Moderate-Size

Representative Farms, Assuming No Change in Demand for Milk Due to bST,

Trigger Price Policy, by Region, 1989-98 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

Impacts of bST Adoption on the Economic Viability of Large-Size

Representative Farms, Assuming No Change in Demand for Milk Due to bST,

Trigger Price Policy,

by Region, 1989-98 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

Impacts of bST Adoption on the Economic Viability of Representative

Large-Size (125-COW) Upper Midwest Farms Under Alternative Dairy Policies,

Assuming No Change in Demand for Milk, 1989-98 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

Comparison of Average Annual Economic Payoffs from bST Adoption for Eight

Representative Dairy Farms Under Three Alternative Dairy Policies, Assuming

No Change in Milk Demand, 1989-1998 . . . . . . +... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

Impacts of bST Adoption on the Economic Viability of Moderate-Size

Representative Farms, Assuming Small Decrease in Demand for Milk

Due to bST, Trigger Price Policy, by Region, 1989-98 . . . . . . . . . . . . . . . . . . . . . . . . . . 81

5-10. Impacts of bST Adoption on the Economic Viability of Large-Size

epresentative Farms, Assuming Small Decrease in Demand for Milk

Due to bST, Trigger Price Policy, by Region, 1989-98 . . . . . . . . . . . . . . . . . . . . . . . . . . 81
Chapter 5

Economic and Policy Impacts of Emerging

Technologies on the U.S. Dairy Industry

Technologies from the biotechnology era will

play an important role in sustaining or accelerating

the historical trend of constantly increasing milk

output per cow. The new technology likely to have

the most to do with this growth is bovine somatotropin (bST). In the following analysis of the

economic and policy implications of emerging

technologies, special emphasis will be given to bST.

As with any analyses, the conclusions are only as

accurate as the assumptions made. Of special

interest and importance is the assumption regarding

the adoption of bST by farmers.

TECHNOLOGY ADOPTION

It is not known when and how many dairy farmers

will adopt new technologies, such as bST, once they

become commercially available. Several studies of

bST either directly address the issue of adoption or

make assumptions regarding adoption rates and

patterns. In a survey of dairy farmers, Lesser et al. (6)

found that about 50 percent of respondents would

adopt bST within the frost year of its commercial

availability, and that over 80 percent would within

3 years. Most analysts, relying heavily on such

studies, have tended to assume relatively rapid

adoption of bST (1,4).

However, the use of surveys to indicate prospective adoption rates of a technology that is not yet

available is problematic. For example, information

regarding the technology is incomplete. Most of the

bST surveys were done several years ago when there

was little negative reaction from public interest

groups. Moreover, new dairy technologies, as a

general rule, have not tended to be adopted rapidly.

For example, despite having been available commercially for over 40 years, artificial insemination

technology is used only by 65 to 70 percent of dairy

farmers. Likewise, Dairy Herd Improvement (DHI)

technology, available for 50 years, is used by only

45 percent of farmers (13). In addition, regionally

variable patterns of use are associated with both

technologies.

This report considers the history of technology

adoption by farmers for insight into potential rates of

bST adoption. Statistical analyses indicate that the

- .

variables most closely (and positively) related to

farmer adoption of new technologies (e.g., automatic grain-feeding systems, automatic milking-unit

removal, three-times-a-day milking, DHI, and artificial insemination) were milk output per cow and size

of herd. Efficiency in the utilization of capital, labor,

and feed were also found to be significantly related

to technology adoption in particular regions (7).

Using this information, and assuming that adoption of bST would closely parallel that of other

technologies, bST technology adoption curves were

derived (see figure 5-l). (See app. A for details.)

Comparative regional information on the level of

adoption after 1,5, and 10 years is contained in table

5-1. The results reflect:

. the tendency of the dairy industry to adopt

technologies at different rates regionally;

. the progressiveness of the Pacific region dairy

industry compared with that of other regions,

including traditional milk production regions;

and

● a slower rate of adoption than is indicated by

producer surveys of probable bST use, and one

that is more typical of past dairy industry

technology adoption patterns.

Figure 5-l-Comparative bST Adoption Curves

Projected for the Pacific, Lake States,

and Northeast Regions

80

0

1990 1992 1994 1996 1998 2000

Year

. . . Pacific — Lake States -. Northeas t

SOURCE: Office of Technology Assessment, 1991.

-73 -
74 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Table 5-l—Forecasted Adoption Rates for

bST Technology, Selected Years, 1991-2000a

Percent of farmers adopting

Region 1991 1995 2000

Pacific . . . . . . . . . . . . . 17% 46% 67%

Lake States . . . . . . . . . 15 35 46

Northeast. . . . . . . . . . . 15 31 43

Appalachia . . . . . . . . . 15 32 46

Southeast . . . . . . . . . . 15 29 39

Southern Plains . . . . . 13 34 42

Corn Belt . . . . . . . . . . . 13 25 31

%ST is assumed to be commercially available in 1991.

—

SOURCE: Office of Technology Assessment, 1991.

OTA’s analysis indicates that during the first year

that bST is commercially available, no more than 17

percent of farmers will use it. After 5 years, bST

adoption is forecast to range from 25 percent in the

Corn Belt to 46 percent in the Pacific region. After

10 years, bST adoption is forecast to range from31

percent in the Corn Belt to 67 percent in the Pacific

region.

NATIONAL AND REGIONAL

IMPACTS UNDER ALTERNATIVE

DAIRY POLICIES

Future milk-supply prices and dairy farmer returns are determined by the interactions of technology adoption, consumer demand, and dairy policy,

as established in the 1990 farm bill. These interactions were captured using a national computer

simulation model referred to as LIVESIM with the

following assumptions:l

*

a

o

●

*

o

●

regional adoption curves as indicated in the

preceding section;

output per cow increases 1.5 percent per year in

base scenario without bST;

output per cow increases 1,320 pounds annually with use of bST;2

bST is injected for 150 days annually;

cost of bST use is $0.30 per cow per day;

feed efficiency increases by 5 percent due

mainly to bST; and

the minimum level of government purchases by

the Commodity Credit Corporation to satisfy

food program needs (i.e., school lunch program, etc.) is 3.0 billion pounds annually.

The policy options analyzed included a fixed price

support, a price support trigger, and a quota program.

It is important to keep in mind that this analysis

begins with the industry in relative supply-demand

balance and in the absence of strong incentives for

either increased or reduced production (10).

Fixed Price Support

This option fixes the price support level at $10.60

per cwt ($0.50 per hundredweight (cwt) higher than

the level authorized by the 1990 farm bill) for all

years and serves as a useful bench mark for policy

option comparisons. In this scenario, the government purchases excess milk, at the support price, in

order to clear the market. Without bST, milk

production would increase progressively under this

scenario from a projected 144 billion pounds in 1990

to 152 billion in 1995 (see table 5-2). With bST,

production would increase an additional 4 to 5

billion pounds over the period 1994 to 1998; annual

government purchases for food programs would rise

as high as 9.0 billion pounds, but generally increase

by 3 to 4 billion pounds over the minimum (3 billion

pounds) (see table 5-3).

Support Price Adjusted by Trigger

This option, similar to policy from 1985-1990,

triggers a price support reduction each time the level

of government purchases rises above 5.0 billion

pounds annually. This option resembles the assessment option in the 1990 farm bill that effectively will

trigger reductions in producer returns as milk price

declines. The simulation period begins with a milk

support price of $10.60 per cwt. This is adjusted

downward in $0.50 per cwt increments in any year

that expected government purchases are greater than

5 billion pounds. Without bST, a single price support

reduction brings the support price to $10.10 per cwt

in 1991. With bST, two price support reductions are

triggered; one in 1991 and another in 1993, reducing

the price support level to $9.60 per cwt. These price

reductions moderate production increases to keep

~L,IVESIM was &VelOped by D.S. Peel, Department of Agricultural Economics, Oklahoma State University. App. B provides a description of tie

model and detailed results of the analysis.

Z’rhe ticreme in output per cow in a given herd tends to be closer to an absolute number of pounds of milk than to a perCentage ticrease. neEfO%

approximately the same increase in pounds of milk produced pcr cow might be expected in comparably managed herds with cows each producing 12,000

to 20,000 pounds of milk per year.
Chapter 5-Economic and Policy Impacts of Emerging Technologies on the U.S. Dairy Industry ● 75

Table 5-2—Level of Milk Production, With and Without bST, Under Alternative Policy Scenarios, 1990-98

(billions of pounds)

Policy scenarios

Fixed support Trigger Quota

Year With bSTa Without bST With bSTa Without bST With bSTa Without bST

1990 . . . . . . . . . . . . . . . . . 144 144 144 144 144 144

1991 . . . . . . . . . . . . . . . . . 146 144 146 144 146 144

1992 . . . . . . . . . . . . . . . . . 146 143 146 143 145 144

1993 . . . . . . . . . . . . . . . . . 153 150 153 150 148 146

1994 . . . . . . . . . . . . . . . . . 153 149 152 148 150 148

1995 . . . . . . . . . . . . . . . . . 156 152 156 152 152 150

1996 . . . . . . . . . . . . . . . . . 157 153 155 153 155 153

1997 . . . . . . . . . . . . . . . . . 160 155 159 155 157 155

1998 . . . . . . . . . . . . . . . . . 161 157 159 157 160 157

abST is assumed to becommercially available in1991.

SOURCE: Office of TechnoloW Assessmen~ 1991.

Table 5-3-Level of Government Purchases, With and Without bST, Under Alternative Policy Scenarios,

1990-98, Milk Equivalent (billions of pounds)

Policy scenarios

Fixed support Trigger Quota

Year With bSTa Without bST With bSTa Without bST With bSTa Without bST

1990 . . . . . . . . . . . . . . . . .

1991 . . . . . . . . . . . . . . . . .

1992 . . . . . . . . . . . . . . . . .

1993 . . . . . . . . . . . . . . . . .

1994 . . . . . . . . . . . . . . . . .

1995 . . . . . . . . . . . . . . . . .

1996 . . . . . . . . . . . . . . . . .

1997 . . . . . . . . . . . . . . . . .

1998 . . . . . . . . . . . . . . . . .

3.0

7.3

4.3

9.0

6.0

7.0

4.8

5.3

3.6

3.0

5.3

3.0

5.7

3.0

3.0

3.0

3.0

3.0

3.0

7.3

3.0

6.8

3.0

3.0

3.0

3.0

3.0

3.0

5.3

3.0

3.8

3.0

3.0

3.0

3.0

3.0

3.0

7.3 “

3.5

3.4

3.1

3.0

3.0

3.0

3.0

3.0

5.3

3.0

3.0

3.0

3.0

3.0

3.0

3.0

abST is assum~ to be commercially available in 1991.

SOURCE: Office of Technology Assessment, 1991.

Commodity Credit Corporation (CCC) purchases

near the 3.0-billion-pound minimum (see table 5-3).

Milk Production Quota

Several proposals have been made to improve

supply control in Federal dairy policy. Quota

systems utilized in California and Canada, for

example, have been suggested for use nationally in

the United States. While these systems differ in their

implementation, each results in a much stronger

opportunity for management of excess dairy production. In the simulation model, control of milk

production is accomplished by reducing the number

of cows in a herd. In practice, these reductions might

be triggered by a two-tiered pricing system or some

other mechanism that provides disincentives for

producing over quota levels.

The quota policy is designed to maintain government purchases at or near the minimum government

use target of 3.0 billion pounds. The quota is

adjusted downward any year CCC purchases exceed

3.0 billion pounds. The price support remains at

$10.6O per cwt; however, the market price is allowed

to adjust as under the other options. The quota yields

a much stabler market price, one that is generally

higher than that under the trigger option. However,

with bST a tendency still exists for the price to rest

at the support level. The quota avoids the high level

of government purchases necessary under the fixed

price support scenario (see table 5-3).

Regional Impacts

Substantial controversy has arisen over the potential regional impacts of bST and other emerging

technologies. The results of this analysis suggest a

continuation of current trends toward greater concentration of production in the Pacific region and the

largest decline in the Corn Belt. Shifts in future

market shares will be largely a function of differ-
76 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

ences in rates of adoption of bST and other

technologies. The more rapid rate of bST adoption

predicted for the Pacific region will increase its

market share even faster than the historical trend.

Regional shifts in production patterns could be

moderated by changes in farm policy. The market

mechanism, as reflected in the trigger price support

mechanism, places the greatest pressure on higher

cost producers and regions. The freed price support

blunts the price declines associated with supply

increases, thus providing a degree of protection to

higher cost regions. Quotas tend to freeze production

patterns. Thus, the regional impacts of bST and other

technologies could be reduced through the adoption

of a quota policy. However, by freezing production

patterns, quotas discourage efficiency. The benefits

of the quota tend to be capitalized in fixed-asset

values, thus raising costs, particularly to new entrants to the industry (i.e., new entrants must buy

quota from current dairy operators). And, because

dairy farmers would not want to see a valuable asset

(quota) lose its value, it would also be difficult to

discontinue a quota policy.

NATIONAL IMPACTS UNDER

ALTERNATIVE DEMAND AND

SUPPLY SCENARIOS

Many claims have been made concerning the

potential adverse health impacts of milk produced

with bST. While these claims remain unsubstantiated, consumer perceptions can be more important

than reality in determining market demand. As

indicated previously, initiatives to label milk produced by cows receiving bST could create a

perception that consumption of this milk may not be

desirable. Since policy needs to be designed considering the full range of potential developments, two

scenarios regarding reduced milk consumption were

analyzed. One of these involved a substantial but

temporary reduction in demand followed by recovery to a smaller long-term reduction. The second

involved a large permanent reduction.

Small Demand Reduction

The small reduced-demand scenario drops percapita demand by 10 percent (about 55 pounds) in

1991,5 percent in 1992 (i.e., demand increases from

1991 to 1992), and 2.5 percent permanently thereafter. The effects of these reductions are CCC

purchases totaling 21.2 billion pounds (14.5 percent

Figure 5-2—Projected Impact of a Temporary Demand

Reduction on Government Milk Purchases Under

Trigger Price Policy, 1990-98

21.2 I

A

1990 1992 1994 1996 1998

Year

SOURCE: Office of Technology Assessment, 1991.

of production) in 1991, 9.7 billion pounds in 1992,

and 8.4 billion pounds in 1993 (see figure 5-2). The

analysis assumed a continuation of the trigger

milk-price support policy. The support trigger decreases the price support level down to $9.10 per cwt

in 1994. In 1994, the industry begins to stabilize at

the 3.0-billion-pound minimum purchase level. Even

though government purchases are exceedingly high

for 3 years, the trigger mechanism seems to accommodate a small demand reduction quite well.

Large Demand Reduction

The second reduced-demand scenario assumes a

permanent 10-percent reduction in per-capita consumption. If the price support is sustained at $10.60

per cwt under the fixed support scenario, CCC

purchases continue at a level that approaches or

exceeds 20 billion pounds of production through

1998 (see figure 5-3). This would exact a high cost

to the government.

While the trigger mechanism copes reasonably

well with a small permanent consumption reduction,

the industry has difficulty adjusting to a large

permanent demand reduction scenario with this

mechanism. The support price must be triggered

down to $7.60 in 1997 in order to bring CCC

purchases to below 4 billion pounds. Such a low

support price would make it difficult (impossible)

for even the best managed dairy farms to avoid

economic losses. As indicated in figure 5-3, for each

of the years 1991 to 1995, the CCC is purchasing at

least 12 billion pounds (at least 8 percent of the milk

supply).
Chapter 5--Economic and Policy Impacts of Emerging Technologies on the U.S. Dairy Industry ● 77

Figure 5-3—Projected Impact of a 10-Percent

Permanent Demand Reduction on Government

Purchases Under Alternative Dairy Policies,

1990-98

30

1

.~. ... ~o*. .o .

“ ● : . ● “ = “ “ “ . . . .

. ----------- —--- -

1990 1992 1994 1996 1998

Year

— Trigger Price s ■ I Fixed Support

-- Dairy Termination - - Quota

SOURCE: Office of Technology Assessment, 1991.

Under this reduced demand scenario, a dairy

termination program might be considered as an

alternative to the severe price support reduction

discussed above. A termination program involves a

one-time buyout of dairy cows, to be implemented

when government purchases reach a certain level. In

the model, the level was established at 15 billion

pounds annually. When government purchases reach

this level, enough dairy cows would be liquated the

following year to eliminate the excess production.

Such a termination policy would be triggered in

1992 because at least 21 billion pounds of CCC

purchases would have occurred in 1991 (see figure

5-3). The herd kill to bring CCC purchases down to

the minimum 3.0 billion pounds would be 1.3

million cows (13.1 percent of the herd). In the

process, cow prices would fall by $6.11 per cwt (12

percent) with a 6. l-percent drop in beef cattle prices.

(See app. B.)

Once the termination is completed, milk production bounces back and CCC purchases exceed 14

billion pounds in the next year (1993). This result is

similar to that of the 1986 Dairy Termin ation

Program. The lowest producing cows on average are

liquated from the industry. The higher producing

cows remain, providing the industry with the capability of responding to increased prices. Another

termination probably would not be feasible because

of the high cost associated with the program and the

tendency of farmers to bid up the cost of selling out.

However, the support price still would decline to

$7.60 per cwt in 1998—a year later than under the

trigger option without the termination program, once

again verifying that termination programs do not

result in permanent reductions in supply.

If a quota were imposed in 1992 with the objective

of bringing CCC purchases back down to the

minimum 3.0 billion pounds, 12.2 percent of the

dairy herd (1.2 million cows) still would be sent to

market (slaughtered) in order to reduce the herd to

about 8.8 million cows. This compares with 1.3

million cows slaughtered under the termin ation

program. Under the quota, the dairy cow price falls

8.1 percent (compared with 12.0 percent under the

termination program) while the beef cattle price falls

by 4.3 percent (compared with 6.1 percent under the

termination program). Perhaps more important, the

quota program effectively controls milk supply. (See

app. figure B-13.)

This analysis suggests that if a large permanent

reduction in demand occurred, changes in dairy

policy would most likely be needed. A fixed support

price policy would be too costly and a trigger price

policy or producer assessments would be too severe

to producers. The policy alternatives are a termination program or a quota. A termination program is

costly and does not result in permanent reductions in

supply. A quota program does effectively control

supply and, compared to the termination program, is

less costly. Benefits of a quota tend to be capitalized

into fixed asset values, thus raising the costs to new

entrants and making it difficult to discontinue the

quota policy. Thus, consideration should be given to

observing CCC purchases over a 2-year period, as

opposed to 1 year, before a quota is implemented.

This would help to determine whether demand

reduction is permanent or temporary.

Large Supply Increase

Previous survey-based analyses of the impact of

bST typically assume a considerably higher rate of

adoption than this study predicts, based on past

adoption patterns. If bST results in a 15-percent

increase in the milk supply in the first year, instead

of the 5-percent increase used in the above analysis,

CCC purchases rise to at least 20 billion pounds.

Large supply increases could be realized not only

through rapid adoption of bST, but also as firms that
78 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

participated in the 1986 Dairy Termination program

reenter the market beginning in 1991.

The impact of a 15-percent supply increase would

be similar to that of a 10-percent permanent demand

reduction, i.e., CCC purchases equal 20 billion

pounds in the first year (see app. figure B-12). In

both instances, it takes 5 years for the price support

trigger mechanism-even with a price support as

low as $7.60--to bring CCC purchases down from

20 billion pounds to no more than 10 billion pounds.

The problems of managing large government purchases over such a long period suggests the need to

consider production management options. Here

again, the termination program only reduces production temporarily with substantial negative impacts

on beef prices. Quotas are effective at controlling

production but also negatively affect beef prices,

although not to the same degree as a single

termination option.

FARM LEVEL IMPACTS

The combined impacts of emerging technologies,

dairy policies, regional differences in production

costs, and long-term industry trends can be more

easily visualized at the level of individual dairy

farms. Representative farms are briefly described in

table 5-4. The parameters of representative farms

were originally developed for OTA in 1985 and have

since been continuously updated by Agricultural and

Food Policy Center faculty and staff at Texas A&M

University. The farms are simulated with and

without bST adoption utilizing the FLIPSIM model.3

The farm level impacts of the three policy

scenarios-fixed support price, trigger, and quota

—were analyzed over the period 1989 to 1998. It

was assumed that the same farm program provisions

operated over the 10-year period. The initial analyses were conducted assuming no change in demand.

Subsequently, alternative demand assumptions were

analyzed (1 1).

Alternative Dairy Policies

The analysis indicates that once bST becomes

available, there will be strong incentives to adopt the

technology. Regardless of the region, the payoffs

from bST adoption are substantial. For example,

with the trigger price policy, the 52-cow Upper

Midwest dairy, a typical, moderate-size dairy farm

in this region, enhances its chance of survival

(probability that the farm will remain solvent

through 1998) from 58 to 74 percent by adopting

bST once it becomes available (see table 5-5). The

same is true for large dairies (see table 5-6).

Nonadopters of bST have more problems surviving

and, therefore, are more likely to exit the industry.

Tables 5-5 and 5-6 provide insight into competitive conditions in the dairy industry and the reasons

for regional shifts in milk production patterns.

Regardless of size, Upper Midwest farms have

problems realizing sufficient earnings to achieve a

reasonable return on equity, compete, and survive.

While Northeast farms perform better, they too were

found to be at a disadvantage relative to the Pacific

and Southeast farms.

These results raise questions about the advisability of State laws placing a moratorium on the use of

bST. Dairy farmers located in States that have put a

moratorium on adoption will be placed at a substantial disadvantage relative to those in unrestricted

States. If moratoriums are imposed in regions where

farm survival probabilities are already low (relative

to other regions), the impact of a moratorium can be

particularly severe.

Policies and the choice between bST adoption or

nonadoption operate together to impact survival in

a number of ways (see table 5-7). Higher earnings

resulting from the fixed price support increase the

probability of survival for a 125-cow Upper Midwest dairy and the chances of a 5-percent return on

initial equity. However, even with adopting bST, net

worth continues to erode.

Surprisingly, perhaps, the quota program performs worse than either the trigger price or the freed

price support. This is because the quota price

objective is the same as the freed price support

($1O.6O) and because restrictions on output curb-b

expansion and raise costs per cwt. Thus, if a quota is

to be imposed, the price objective must be sufficiently high to offset the effects of lower production

(higher production costs per cwt) or producers could

be worse off.

The absolute economic payoff from bST adoption

is about the same under a trigger price policy and a

3~~s1M ~&~ deve.oped by J.w, ~c~d~~n, Dep~tment of A@cul~~ ~onomics and C.J. Nixon, rlep~rnent of Accounting, Texas A&M

University (12). App. C provides a description of the model and detailed results of the analysis.
i

Table 5-4—Summary Characteristics of Representative Moderate-Size and Large Dairy Farms, by Region

Upper Midwest Northeast Southwest a Southeast

Characteristic Moderate Large Moderate Large Moderate Large Moderate Large

Cow numbers . . . . . . . . . . . . . . . . . . 52 125 52 200 350 1,500 200 1,500

Output/cow (pounds) . . . . . . . . . . . . 16,850 16,850 17,940 17,830 18,590 19,690 15,340 15,310

Total asset value ($000) . . . . . . . . . . 470 940 608 1,395 1,097 3,858 1,569 7,723

Land value ($000) . . . . . . . . . . . . . . . 133 295 274 640 118 492 813 4,591

Percent of feed raked . . . . . . . . . . . 63 60 50 46 0 0 25 2

a[ncl~es farms from both the Pacific and Mountain USDA production regions

SOURCE: Office of Technology Assessment, 1991.

Table 5-5—Impacts of bST Adoption on t he Economic Viability of Moderate-Size Representative Farms, Assuming No Change

in Demand for Milk Due to bST, Trigger Price Policy, by Region, 1989-98 (in percent)

52-cow 52-cow 350-COW 200-COW

Upper Midwest Northeast Southwest Southeast —

Non- bST Non- bST — Non- bST Non- bST

Measure of impact adopter adopter adopter adopter adopter adopter adopter adopter

Probability of survivala . . . . . . . . . . . . . . . . . . . . . . 58% 74% 100% 100% 95% 97% 100% 100%

Probability of earning 5-percent return

on equity . . . . . . . . . . . . . . . . . . . . ., , . . . . . . . . . 58 74 100 100 95 97 100 100

Probability of increasing equityb . . . . . . . . . . . . . . . 0 0 3 3 60 79 13 24

Present value of ending net worth as percent

of beginning net worthc . . . . . . . . . . . . . . . . . . . . 16 29 72 77 109 128 76 89

Whance that the individual farm will remain solvent through 1998, i.e., maintain more than a 10-percent equity in the farm.

%hance that the individual farm will increase its net worth in real 1989 dollars through 1998.

cPresent value of ending net worth divided by initial net worth indicates whether the farm increased (decreased) net worth in real dollars.

SOURCE: Office of Technology Assessment, 1991.

Table 5-6—impacts of bST Adoption on the Economic Viability of Large Representative Farms, Assuming No Change in Demand for Milk

Due to bST, Trigger Price Policy, by Region, 1989-98 (in percent)

125-cow 200-COW 1 ,500-COW 1,500-cow

Upper Midwest Northeast Pacific Southeast

Non- bST Non- bST Non- bST Non- bST

Measure of impact adopter adopter adopter adopter adopter adopter adopter adopter

Probability of survivala 

. . . . . . . . . . . . . . . . . . . . . . 95% 99% 100% 100% 100% 100% 100% 100%

Probability y of earning 5-percent return

on equity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 95 99 100 100 100 100 100

Probability of increasing equityb . . . , . . . . . . . . . . . 8 12 43 53 100 100 88 99

Present value of ending net worth as percent

of beginning net worthc . . . . . . . . . . . . . . . . . . . . 57 69 92 102 195 214 129 147

W2hance that the individual farm will remain solvent through 1998, i.e., maintain more than a Io-peroent equity in the farm.

%hance that the individual farm will increase its net worth in real 1989 dollars through 1998.

cPresent value of ending net worth divided by initial net worth indicates whether the farm increased (decreased) net worth in real dollars,

SOURCE: Office of Technology Assessment, 1991,

I
80 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Table 5-7—impacts of bST Adoption on the Economic Viability of Representative Large (1 25-cow)

Upper Midwest Farms Under Alternative Dairy Policies, Assuming No Change

in Demand for Milk, 1989-98 (in percent)

Trigger price Fixed price support Quota

Non- bST Non- bST Non- bST

Measure of impact adopter adopter adopter adopter adopter adopter

Probability of survivala. . . . . . . . . . . . . . . . . 95% 99%. 99% 100% 85%. 92%.

Probability of earning 5-percent

return on equity . . . . . . . . . . . . . . . . . . . . 90 95 95 98 67 78

Probability of increasing equityb . . . . . . . . . 8 12 11 18 2 3

Present value of ending net worth as

percent of beginning net worthc. . . . . . . . 57 69 67 78 37 46

%hance that the individual farm will remain solvent through 1998, i.e., maintain more than a 10-percent equity in the farm.

bchance that the individual farm will increase its net worth in real 1989 dollars through 1998.

cPresent value of ending net worth divided by initial net worth indicates whether the farm increased (decreased) net worth in real dollars.

SOURCE: Office of Technology Assessment, 1991.

freed support price policy for the representative

dairy farms (see table 5-8). Increasing the price of

milk by maintaining the milk support price at its

current level does not greatly increase the economic

incentive to adopt bST, but that incentive is significantly lower if a quota is in effect. This suggests that

the rate of bST adoption would be slowed by

imposing a quota rather than continuing the trigger

price policy.

Alternative Demand and Supply Scenarios

Potential reductions in demand due to consumer

concern over bST would reduce the economic

payoffs from using this technology. The most

significant result of such demand reduction is

reduced economic viability of all dairy farms, and

particularly of those in the Midwest. For example,

the economic payoff for bST adoption is $10,300 for

the 125-cow dairy in the Upper Midwest if there is

no decrease in milk demand. If demand decreased

slightly, the economic payoff falls to $9,200 and if

the demand decrease is large, the economic payoff

declines to $6,900. Thus, the incentive to adopt and

the rate of adoption would be reduced if milk

demand declines.

The adverse impacts of reduced demand could be

countered by either a termination program (in the

event of a small reduction in demand) or by a quota

(if larger reductions in demand occurred).4 However, even with reduced demand, there would be

strong incentives to adopt bST for all farms in all

Table 5-8—Comparison of Average Annual

Economic Payoffs From bST Adoption for

Eight Representative Dairy Farms Under

Three Alternative Dairy Policies, Assuming

No Change in Milk Demand, 1989-98a

(thousands $)

Policy scenarios

Trigger Fixed

Region/size price support Quota

Lake States:

Moderate . . . . . .

Large . . . . . . . . .

Northeast:

Moderate . . . . . .

Large . . . . . . . . .

Southwest:

Moderate . . . . . .

Large . . . . . . . . .

Southeast:

Moderate . . . . . .

Large . . . . . . . . .

3.9

10.3

3.4

15.8

26.5

90.5

21.9

166.4

4.1

10.9

3.6

16.6

26.6

91.7

22.8

166.3

2.4

7.0

1.0

8.8

18.3

61.2

17.2

132.0

aEconomic payoffs from bST are the average annual change in net cash

farm income between a nonadopter and a bST adopter over the 1989 to

1998 planning horizon. The payoff is net of the cost of bST, the added

transportation costs for milk, and the additional feed.

SOURCE: Office of Technology Assessment, 1991.

regions. For example, with a continuation of the

trigger policy, a 52-cow Upper Midwest dairy’s

probability of survival declines to 40 percent under

a small decrease in demand; adopting bST boosts

survival probability under this scenario to 48 percent

(see table 5-9). Similar trends hold true for the larger

dairies (see table 5-10). Thus, the economic payoff

for bST adoption is positive; those who adopt bST

will experience greater probabilities of survival and

4Sm~1 and lmge dem~d r~uctiom are the same as explained in the previous section. A small demand reduction assumes tit milk dmand would

decrease 10 percent in 1991, 5 percent in 1992 (i.e., demand increases from 1991 to 1992), and 2.5 percent each year in 1993-1998. A large demand

reduction assumes that milk demand wotdd decrease 10 percent in each year 1991-1998,
I

I

Table 5-9—impacts of bST Adoption on the Economic Viability of Moderate-Size Representative Farms, Assuming Small Decrease in

Demand for Milk Due to bST, Trigger Price Policy, by Region, 1989-98 (in percent)

52-cow 52-cow 350-COW 200-COW

Upper Midwest Northeast Southwest Southeast

Non- bST Non- bST Non- bST Non- bST

Measure of impact adopter adopter adopter adopter adopter adopter adopter adopter

Probability of survivala . . . . . . . . . . . . . . . . . . . . . . 40% 48% 100% 100% 88% 94% 99% 100%

Probability of earning 5-percent return

on equity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 48 100 99 88 94 89 94

Probability of increasing equityb . . . . . . . . . . . . . . . 0 0 1 2 35 51 4 9

Present value of ending net worth as percent

of beginning net worthc . . . . . . . . . . . . . . . . . . . . 3 10 65 70 79 99 58 71

Whance that the individual farm will remain solvent through 1998, i.e., maintain more than a 10-percent equity in the farm.

bchana that the individual farm will increase its net worth in real 1989 dolIars through 1998.

cPresent value of ending net worth divided by initial net worth indicates whether the farm increased (decreased) net worth in real dollars.

SOURCE: Office of Technology Assessment, 1991.

Table 5-10—Impacts of bST Adoption on the Economic Viability of Large Representative Farms, Assuming Small Decrease in Demand

for Milk Due to bST, Trigger Price Policy, by Region, 1989-98 (in percent)

125-cow 200-COW 1 ,500-COW 1 ,500-COW

Upper Midwest Northeast Pacific Southeast

Non- bST Non- bST Non- bST Non- bST

Measure of impact adopter adopter adopter adopter adopter adopter adopter adopter

Probability of survivala 

. . . . . . . . . . . . . . . . . . . . . . 85% 91% 100% 100% 100% 100% 100!40 100%

Probability of earning 5-percent return

on equity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 82 98 99 100 100 100 100

Probability of increasing equityb . . . . . . . . . . . . . . . 2 7 26 45 96 98 65 86

Present value of ending net worth as percent

of beginning net worthc 

. . . . . . . . . . . . . . . . . . . . 40 50 86 95 162 180 110 127

%hance that the individual farm will remain solvent through 1998, i.e., maintain more than a 10-percent equity in the farm.

%hance that the individual farm will increase its net worth in real 1989 dollars through 1998.

CPresent value of ending net worth divided by initial net worth indicates whether the farm inoreased (decreased) net worth in real dollars.

I

SOURCE: Office of Technology Assessment, 1991.
82 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

economic success than nonadopters. The positive

economic payoffs for bST adoption are greater under

the dairy termination program than under the trigger

price policy. Thus, bST adoption would be accelerated even with declining milk demand if a termination program were introduced in lieu of the trigger

price policy.

The supply impacts estimated by the LIVESIM

model in the previous section were based on past

adoption practices, not farmer survey results, which

indicate higher adoption for bST. If the survey

results are accurate predictors of adoption then a

large increase in supply would occur. Unless supply

controls such as a dairy termination program or a

quota are imposed, adverse impacts on economic

viability would be substantial (see app. tables C-12

to C-17).

Enhancing the Survival of

Traditional Farms

Results of the preceding analysis indicate that

smaller, less efficient, farms will have difficulties

realizing sufficient earnings to achieve a reasonable

return and survive even with the adoption of bST.

Northeast farms perform better, in part, because they

receive higher Federal milk marketing order prices.

Farms that do not adopt bST will feel even more

severe impacts.

The economic viability of smaller farms may be

enhanced by changes in scale of operation, progressiveness in technology adoption, research and extension, and dairy policy. The following provides a

brief discussion of the importance of each item.

●

●

Scale of Operation--Generally, larger farms

experience lower costs of production. Studies

now in progress indicate that in the Upper

Midwest and Northeast, economies of size have

resulted in the establishment of larger herds

that have the potential to realize even more

economies of size involved in dairying. Farms

with herds larger than 125 cows in the Upper

Midwest and 200 cows in the Northeast will be

more likely to lower their costs of production

and compete than smaller operations.

Technology Adoption--A key to achieving the

economic benefits of a new technology is to

adopt it early. The traditional milk production

regions have a history of lagging behind other

regions in adopting new technology. This study

has shown that, based on experience, the Upper

●

●

Midwest and Northeast regions will lag behind

the Pacific region by more than 20 percent in

the adoption of bST Ways must be found to

encourage producers in these regions to adopt

new technology earlier to enhance their probability of economic success.

Research and Extension-Little, if any, emphasis is given to conducting research and providing extension services to different-size farms.

Small, moderate, and large farms each have

their own unique problems, particularly from a

management perspective. Research is needed

on developing management strategies for each

farm size. Extension strategies also need to be

developed to assist farmers in technology

adoption so they can receive more of the

benefits of new technologies. Laggards in

technology adoption receive little economic

pay-off.

Dairy Policy--Based on this study’s analysis,

a fixed support price policy provides farms in

the traditional milk-producing regions with

higher earnings that increase their probability

of survival and the chance of earning a 5-

percent return on equity. However, even with

this policy, net worth continues to erode for

these farms. Thus, the support price may need

to be increased. This is, of course, more costly

in terms of government expenditures. An alternative would be to target these farms for a

higher support price-but it still will be more

costly and administratively complex compared

to other alternatives. However, if substantial

progress were made on the items discussed

above possibly no change in policy would be

needed.

BENEFICIARIES OF

TECHNOLOGICAL CHANGE

The issue of who benefits from technological

change is not new but is relevant to this study. The

farm-level results indicate that bST adopters are

better off than nonadopters. First adopters, moreover, are the greatest beneficiaries of any technological change. They receive a relatively high price for

their product and realize the cost reductions resulting from bST use. As more farmers adopt, the market

price falls, which makes the consumer the ultimate

beneficiary. As the market price falls, farmers who

do not adopt may be forced out of business.
Chapter 5-Economic and Policy Impacts of Emerging Technologies on the U.S. Dairy Industry ● 83

Figure 5-4—Dairy Price Indexes at

Three Market Levels (change from prior month)

6.0 —

, - - ------- -

\

3.0 — ,#’

m

,0

g , ’

o

: 0.0

% b

c * \ 4’

-3.0 — ‘**---*” ’

\

I

1

I

9

-6.0

-9.0

JFMAMJJASONDJ F M

1989

Month

1990

--- Retail prices, — Wholesale prices, ---- Farm prices,

all dairy products all dairy products all milk

SOURCE: Compiled from U.S. Department of Agriculture dairy statistical

data by Andrew Novakovic, DairyMarketing fWes, 1990, No. 2,

Department of Agricultural Economics, Cornell University, lthaca, NY.

Questions have been raised regarding whether

consumer prices do, in fact, decline as producer

prices fall. Some groups opposing the approval of

bST have attempted to show that retail milk prices

do not fall as producer prices decline and, therefore,

consumers do not benefit from the technology (3). A

review of the relevant data on producer prices

received and retail dairy prices paid do not support

this contention.

Novakovic (8) made a comparison of the changes

in dairy prices at the farm, wholesale, and retail

levels for 1989 through 1990. Figure 5-4 illustrates

the monthly changes in average aggregate farm,

wholesale, and retail dairy prices converted to an

index where 1982 to 1984 = 100. The graph shows

a change in each index from one month to the next.

(A line on the graph below (above) 0.0 indicates

prices fell (rose) compared to the prior month.)

The data show that farm, wholesale, and retail

prices did follow each other. There are, however,

differences in the volatility of change. Farm prices

Figure 5-5-Farm and Retail Prices of Beverage

Milk Per Half Gallon (change from prior month)

$0.05 ~

$0.04 —

$0.03 —

g $o.02 —

= ,

m .

*

=

8

, 1

c

s

: $0.0 0 “’h, :

,

,

I , , *

, , 1 1 , 1 18 i

,

($0.01) – ‘“., /’

,

*

*

*

,

,

($0.02) –“’........ :

s

*

*9

,

*

,

($0.03) J

*

,

JFMAMJJASONDJF M

1989 1990

Month

----- Farm price, all Federal orders — Whole milk, retail price

aThis is the producer price for fluid milk (Class 1) averaged overall Federal

milk marketing orders.

SOURCE: Compiled from U.S. Department of Agriculture dairy statistical

data by Andrew Novakovic, Dairy Marketing /Votes, 1990, No. 2,

Department of Agricultural Economics, Cornell University, lthaca, NY.

are the most volatile while retail prices are the least.

Declines in farm prices are reflected in smaller

declines at retail. However, this is true on the up side

as well. Farm prices increased the most from mid

1989 to the end of 1989 and retail prices increased

the least.

A review of actual price changes for fluid milk

and manufactured products, i.e., cheese, provides a

more insightful analysis (8).5 The pattern in figure

5-5 is similar but not identical to figure 5-4. That is

producer and retail prices for fluid milk did follow

one another up and down.6 Producer prices, however, decreased more than retail prices in the first

half of 1989 and increased less in the second half.

Some buoyancy exists to retail milk prices relative

to farm prices in reflecting declines in farm prices.

Price changes in cheese markets offer a similar but

more responsive change (see figure 5-6). Note that

producer prices lag wholesale prices by 1 month and

retail prices have a 2- to 4-month lag in reflecting

wholesale price changes. For example, the largest

spercentage changes me not the best way to compare farm, wholesale, and retail prices. When expressed in a common ufit of measmement (e.g.,

dollars per cwt of milk), the farm price will obviously be a smaller number than the retail price. Thus taking a percentage of a smaller number is less

than an equal percentage of a larger number. Part of the seemingly lower volatility in prices higher up the marketing channel is a result of comparing

index or percentage changes.

G~e sme result was found by outlaw et al. (9) in a more recent analysis.
84 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

increase in wholesale cheese prices begin in May.

Retail price increases began to increase in August

and peaked in October. By then wholesale prices

were increasing at a more modest rate while retail

prices were increasing by the largest amount.

Examining just the October data, it would be

difficult to justify a 9-cent increase in retail prices by

a 2-cent increase in the wholesale price. It can,

however, be justified by the 5 months of 4- to 8-cent

monthly increases in wholesale prices that occurred

prior to October. Also note that in the second half of

the year, the increase in producer prices was

substantially greater than the increase in retail

prices. These results are similar to other research in

this area. Kinnucan and Forker (5) found the same

asymmetric relationship between farm and retail

dairy prices. This phenomena is found in other

agricultural industries as well.7

This analysis indicates that prices of dairy products to consumers are reflective of changes in supply

and demand factors in the market. Individual dairy

products such as milk and cheese do respond to price

changes differently, reflecting the specific forces at

work in each of their respective markets. Retail milk

prices follow farm price increases but seem to be

relatively slower in reflecting farm price declines.

On the other hand, cheese prices are responsive to

farm price changes and may even start falling before

producer prices. Thus, technological change that

lowers farmers’ production costs will eventually be

reflected in the market and the corresponding

savings passed on through lower prices to the

consumer, the ultimate beneficiary.

INTERNATIONAL TRADE

PROSPECTS

Speculation exists that adoption of new technologies, such as bST, will enhance the U.S. position in

international milk markets. The U.S. dairy industry

primarily focuses its marketing efforts on the

domestic market. It has had limited success in

international markets. This has been due to a number

of factors including: difficulties in identifying markets, monetary policies, import restrictions, and

political uncertainty in many countries. Moreover,

the world market price for dairy products is lower

than the U.S. price—largely because of the use of

Figure 5-6-Farm, Wholesale, and Retail Prices

of Cheese (change from prior month)

$0.09- -

0 ‘ - \

0

$0.05- -

/ .,.. 0

/ .“””

$0.01 -- -/’ ...”L”” , #

($0.01) --

,

... ” , r \-

.- ;“, ;

($().()5) ->.y”’-” ”

\:; /;

‘ i !

($0.09)

+

t

\ /

($0.17)

}

JFM AMJ J A SONDJ F M

1989 Month 1990

---- Farm price, --- Wholesale, ~ — Retail

manufacturing milk’ cheese price cheese price

aThefarm price is the Minnesota-Wisconsin price which is also the Class Ill

(manufacturing) price in Federal milk marketing orders.

~he wholesale price is the National Cheese Exchange (NCE) price for

40 lb block of cheddar.

SOURCE: Compiled from U.S. Department of Agriculture dairy statistical

data by Andrew Novakovic Dairy Marketing Notes, 1990, No. 2,

Department of Agricultural Economics, Cornell University,

Ithaca, NY.

subsidies to increase export sales from competing

countries.

Cost-reducing technologies, such as bST, can

improve the United States competitive position in

international milk markets, but alone are not sufficient. An encompassing strategy that at a minimum

identifies promising new markets, benefits from

favorable monetary policies, addresses export subsidies and import restrictions, as well as supports

research to provide cost-reducing technologies for

the industry will be needed.

POLICY IMPLICATIONS

The dairy industry is familiar with and has gained

strength from technological change. The constant

adoption of new technology has resulted in a

relatively uniform annual increase in output per cow

in the range of 1.5 to 2.0 percent annually. Emerging

technologies in the 1990s, especially bST, may

temporarily accelerate that rate of increase, putting

the industry on a higher output-per-cow growth path.

The impact of bST on the dairy industry is heavily

weighted by the rate of adoption of the new

TI-IahtI (2), for ex~ple, fo~d that the farm, wholesale, and retail prices for beef and pork show significant evidence Of aS~e@iC price interaction.

That is, prices display greater sensitivity to price-increasing shocks than to price-decreasing shocks.
Chapter 5--Economic and Policy Impacts of Emerging Technologies on the U.S. Dairy Industry ● 85

technology. Experience in adoption of dairy technologies suggests slower rates of adoption than has

been predicted by farmer survey. However, this

analysis still indicates substantial economic incentives for, and payoffs from, adoption of bST. The

analysis also indicates that States placing a moratorium on the use of bST run substantial risk of

damaging the economic viability of their dairy

farmers.

The rates of adoption indicated by past technology adoption trends suggest that a mechanism that

allows producer returns to decline as CCC purchases

increase, i.e., a trigger policy or producer assessment

(as provided for in the 1990 farm bill) could

effectively adjust supply to meet demand without

exceedingly large inventory accumulations. However, if sharp demand reductions were to accompany

the introduction of bST, supply management policies such as production quotas or termination

(buy-out) programs may be required. Termination

programs, such as the one implemented in 1986, are

costly and not effective in reducing supply over a

period of time. Production quotas can effectively

control supply. However, quotas do result in freezing regional production shifts and since the quota

has an economic value, make it more costly for new

entrants into the industry.

Regardless of farm size or region, there will be

strong economic incentives to adopt bST. However,

Upper Midwest farms adopting the new technology

still will have problems realizing sufficient earnings

to achieve a reasonable return on equity, compete,

and survive. Northeast farms perform better but they

too are at a disadvantage relative to the Pacific and

Southeast farms. For farms not adopting the new

technology the dilemma will be even more severe.

These results raise questions about the advisability

of State laws, especially in the Upper Midwest, that

place a moratorium on the use of bST. To enhance

the economic viability of farms in these regions

changes in scale of operation, progressiveness in

technology adoption, research and extension policy,

and perhaps dairy policy may be required.

1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

11.

12.

13.

CHAPTER 5 REFERENCES

l?allert, l?. et d., bST and the Dairy Industry, Agricultural Economics Report 579 (Washington, DC:

ERS/USDA, 1987).

Hahn, W., “Price Transmission Asymmetry in Pork

and Beef Markets, ’ Journal ofAgricultural Economics Research, vol. 42, No. 4, 1990.

Hanson, Michael K., Biotechnology and Milk: Benefzt or Threat? (Mt. Vernon, NY: Consumer Policy

Institute, Consumers Union, 1990).

Kaiser, H.M. and Tauer, L. W., “Impacts of Bovine

Somatotropin on U.S. Dairy Markets Under Alternative Policy Options,’ North Central Journal of

Agricultural Economics 11:59-73, 1989.

Kinnucan, H. and Forker, O., “Asymmetry in

Farm-Retail Price Transmission for Major Dairy

products,” American Journal of Agricultural Economics 69:285-292, 1987.

Lesser, W., Magrath, W., and Kalter, R., ‘‘Projecting

Adoption Rates,’ North Central Journul of Agricultural Economics (July 1986).

McGuckin, J. Thomas, “Adoption of bovine Somatotropin: A National and Regional Analysis,” OTA

commissioned background paper (Washington, DC:

1990).

Novakovic, Andrew, Dairy Marketing Notes, No. 2

(Ithaca, NY: Cornell University, 1990).

Outlaw, J., Knutson, R., and Schwart, R., “The

Correspondence of Farm and Retail Price Movements,’ Department of Agricultural Economics Staff

Paper (College Station, TX: Texas A&M University,

February 1991).

Peel, Derrell S., “National and Regional Impacts of

Bovine Somatotropin Adoption Under Alternative

Dairy Program Policies,’ OTA commissioned background paper (Washington, DC: 1990).

Richardson, James W., “Farm hwel Impacts of

bovine Somatotropin Introduction and Adoption

Under Alternative Farm Policies,” OTA commissioned background paper (Washington, DC: 1990).

Richardson, J.W. and Nixon, C. J., “The Farm Level

Income and Policy Simulation Model: FLIPSIM,”

Texas Agriculture Experiment Station Technical

Report No. 81-2 (College Station, TX: July 1986).

U.S. Department of Agriculture, National Economic

Indicator Farm Cost and Return Survey (Washington, DC: Economic Research Service, 1985).
Appendixes
Appendix A

A National and Regional Analysis of the

Adoption of bovine Somatotropin

Chapter 5 presented the summary results of the

national, regional, and farm-level impacts of emerging

technologies and public policies on the U.S. dairy

industry. A crucial assumption in the analyses is the rate

of adoption of bovine somatotropin (bST). This appendix

discusses the results of the analysis supporting OTA’s

adoption rates for bST. For more detail than is provided

in this appendix the reader is advised to read the

background paper on which this analysis is based.1

Review of Previous Studies

There have been numerous studies dealing with the

introduction of bST into the dairy industry (1,2,5,6,7,9).

Lesser, Magrath, and Kalter (7) estimated the rate of

adoption of bST based on a primary survey of producer

attitudes towards the technology. This estimate has been

used in simulation studies of bST (6), which predict the

relatively rapid adoption of bST after it is introduced.

Fifty percent of dairy herds adopt bST technology within

the first year and over 80 percent within 3 years.

Other studies (i.e., Fallert et al. (2) and Sellschopp and

Kalter (9)) reviewed the impact of bST under alternative

policy scenarios. Their conclusions were that with the

introduction of bST, inflexible support prices would

result in large Commodity Credit Corporation (CCC)

purchases during the 1990s. To reduce government

purchases, the government would need to continue

reducing the support price by $0.50 increments.

Using a structural model, Kaiser and Tauer also

analyzed the impact of bST on the national dairy market

during the 1990s under a number of government policy

options. Under one, CCC purchases are held stable by

adjusting the U.S. herd inventory through repeated

implementation of the dairy termination program. The

authors note that such adjustments may be difficult to

accomplish if farmers recognize the intent of the government and raise their dairy termination program bids.

Without these adjustments, CCC purchases rapidly increase with bST even with lower support prices. The

authors conclude that a combination of price support

reductions and dairy termination programs would be the

most effective policy for balancing the conflicting interests of dairy producers, taxpayers, consumers, and beef

producers.

The previous analyses have relied on surveys and

hypothetical estimates for the adoption rates of bST. The

studies have generally lacked a consistent economic

foundation for predicting adoption. This is in part because

a model that systematically explains technological change

and/or the consequences for agricultural policy has been

elusive. As Feder (3) and Just and Zilberman (4) observe,

conventional economic models have not consistently

explained adoption patterns of agricultural innovations or

why seemingly profitable technologies are slowly adopted

by specific classes of farms (i.e., small farms). The

analysis here attempts to predict adoption of bST.

Technological Change

Technological change refers to change in production

processes that results from the application of scientific

knowledge. At the firm level, technological change can be

realized in several ways. It can be embodied in inputs

(changes in input quality); it can be disembodied, and

involve improved use of existing resources such that a

higher output rate per unit of input is obtained; or it can

arise from entirely new processes and new inputs (e.g.,

bST). A combination of these three phenomena underlies

many innovations. For example, the development of

hybrid corn varieties represented the embodiment of

scientific knowledge in corn seed. Disembodied management knowledge was then needed for its successful use,

and eventually a set of new inputs in the form of pesticides

was developed for use with the hybrids.

These definitions apply to the analytical framework

presented here. The adoption of bST is both the consequence and cause of technological change. To use bST

successfully, farmers must adjust to new, higher production levels by increasing technical efficiency. Farmers

with low levels of efficiency are less likely to adjust inputs

to meet the requirements of higher milk production.

Conversely, the higher the current productivity of the

farmer, the more likely he or she will adopt bST

technologies.

Operational Model of bST Adoption

In a theoretical model outlined by McGuckin (8),

changes in technical efficiency (ratio of milk output to

farm resources) drive the adoption of new technologies.

Milk output per cow (a productivity measure) and

changes in scale (size of the dairy unit) are strongly

l~s append~ is bas~ on tie o~ cc)mrnisslon~ backgro~d paper “Adoption of bovine Somatotropin: A National and Regional ~ysis”

prepared by J. Thomas McGuck@ New Mexico State University. It is available through the National Technical Information Service.

–89–
90 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

correlated with technical efficiency and thus technology

adoption. As productivity increases over time so does

adoption of new technologies.

The linkages between productivity change, technical

efficiency, and adoption of bST are the cornerstone of this

analysis. However, because of data limitations, only

general trends in productivity over time can be obtained.

Increasing farm productivity is equivalent to increasing

farm technical efficiency, which drives adoption: as

productivity increases because of improved technical

efficiency, so does the willingness to adopt new technologies such as bST.

The operational model used in this analysis assumes

that a farm’s likelihood of adopting bST is a function of

its scale and technical efficiency (measured by total factor

productivity (TFP)). Because predicting adoption of bST

is ex ante, an index of adoption of previous technologies

(outlined in the data section) is used as a proxy measure.

The empirical model used is the following general

representation:

IAf= g(Sf

,TFPf), for f = 1.. N

where IA is an index of adoption of previous technologies, S is scale or size of the dairy, TFP is total factor

productivity and f represents a cross section of dairy

farms.

Data

The analysis used cross sectional representative farm

data from the 1985 U.S. Dairy Farm Costs and Return

Survey. Detailed data sources and the types of information collected through the survey are reported in the

USDA report by Fallert, McGuckin, Betts, and Bruner (2).

The data include dairy farm milk production, amount of

labor (both hired and family), amount of capital (converted to a cow capacity basis—parlor, housing, and

feeding system can berated by the number of cows milked

per day) and respective prices. As the index for the

technological adoption, five type of technologies were

weighted according to their relevance to bST adoption.

The five technologies include:

1. automatic grain feeding system (parlor or otherwise),

2. automatic milking unit takeoff,

3. three times a day milking,

4. herd production records (DHI), and

5. artificial insemination.

The most heavily weighted (45 percent) measure was

3x milking. Use of this technology indicates that a farmer

can adjust feed, breeding, and herd health practices to a

higher level of production. However, 3x requires additional labor while bST would not. Artificial insemination,

an improved method of breeding that directly affects milk

production, is weighted 20 percent. DHI is a management

information system, known as Dairy Herd Improvement,

that is weighted 15 percent. Automatic takeoffs are

representative of automated milking systems (weighted

15 percent); automatic grain feeders are similar to

automatic takeoffs, though not universally used by

factory style operations.

The rate of change in the index of technological

adoption indicates the change in use of the bST technology over time and across dairy production regions of the

United States. Because the estimated functions are

indices, an initial starting point was derived. A range of

initial adoption levels (low, medium, and high) were

identified for each region.

Results

To predict the adoption of bST, a regression analysis

was used based on historical rates of change in capital,

labor, and feed efficiency in the dairy industry. The results

for each region contain a low, medium, and high scenario

for the initial adoption of the technology in 1991. After

1991, all regional growth in adoption is based on the

relative impact of production efficiency change on the

technological index. The results are presented by region.

The Corn Belt region is one of the lowest adoption

regions (see figure A-l). By 1995, between 20 and 35

percent of herds will receive bST (low and high scenarios,

respectively). By 2000, these percentages rise to 25 and

45 percent, respectively. A medium scenario is 31

percent.

The Southeast is also relatively slow to adopt (see

figure A-2). By 1995, between 24 and 42 percent of herds

will receive bST (low and high scenarios, respectively).

Figure A-l—Projected Adoption Rate of bST

Corn Belt Region

1990 1992 1994 1996 1998 2000

Year

--- Low — Medium . . . . High

SOURCE: Office of Technology Assessment, 1991.
Appendix A--A National and Regional Analysis of the Adoption of bovine Somatotropin . 91

Figure A-2—Projected Adoption of bST

Southeast Region

1, . . . 1 . . . . . . .

I . . . .

I . . . . . . .

0.6 -/ : : : : : : : : :

l:::::::” ”

0.54 : : : : : : : : ... i““ -

0.4

0.3 j

+

0.2 ‘“”

0.1-

. . . . - . . . . - .

. . . . . . . . .:. , .

. .

. ;.. . . . .. :.. . .

. . .

. 0 .

*

● . 0. : : : : : : /: : , : : : : :

;

::::: :

. . . . . . .

1990 1992 1994 1996 1998 2000

Year

--- Low — Medium . . . . High

Figure A-4—Projected Adoption of bST,

Lake States Region

0.8-/ : : : : : : : : :

l:”:::::: :

0.74 : : : : : : : : : I

1990 1992 1994 1996 1998 2

Year

--- Low — Medium . . . . High

Figure A-6—Projected Adoption of bST

Northeast Region

Figure A-3-Projected Adoption Rate of bST

Southern Plains Region

0.94 : : : : : : : : :

I . . . .

i

0.6 : : : : : : : : :

.

. .

0.5- ;::;:::: . . . . . . . . . ”

. . . . . . - . .:. . - . . :“ “ :

0.4- : : .....;.”. ““ ~ ““”-”/” - ; ; : >

: : : -------~ ---+---’ ,y ----------- -

. .

0.2- j“” . .

. .

. . .“ . . .

0.1- ;::; :

‘::: :

1990 1992 1994 1996 1998

Year

--- Low — Medium . . . . High

Figure A-5-Projected Adoption Rate of bST,

Appalachian Region

1 1 . . .

. . . . .

I . . . . . .

0.7 + : : : : : : : : : I . . . . . . .

1990 1992 1994 1996 1998 2000

Year

--- Low — Medium . . . . High

Figure A-7—Projected Adoption Rates of bST,

Pacific Region

‘1 : : : : : : : : :

1 . . . . . . I I . . . .

-i 0.8 : : : : : : : : :

. . . .

. . . . I

0.74 : : : : : : : : : I

1::: :::::: 1

0.6~ : : : : : : : : : I I . . . . . I

0.5

:

0.4 –

0.3

0.2 –

0.1 –

. . . .

. . . . .: ..””

. . . .

. . . . .

. . . .

. . . .

--h--i--------? ‘

- : : {

. *

. .

.-.

.-

/ :

. . -----

● ✎ ✌✜

✎

● ✃ ✎

● .e : .& . ● “ 4 . y. . . .

1990 1992 1994 1996 1998 2300

Year

--- Low — Medium . . . . High

SOURCE: Office of Technology Assessment, 1991.

292-860 0 - 91 - 4

1990 1992 1994 1996

Year

-- Low — Medium

1998 2000

. . . High
92 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

By 2000, these percentages rise to 32 and 55 percent,

respectively. A medium scenario is 39 percent. (However,

confidence in these predicted rates is low, respectively.)

Like the Southeast, the Southern Plains is a low

adoption region (see figure A-3). By 1995, between 28

and 44 percent of herds will receive bST (low and high

scenarios, respectively). By 2000, these percentages rise

to 35 and 53 percent, respectively. A medium scenario is

42 percent.

Adoption rates are slightly higher in the Lake State

region (see figure A-4). By 1995, between 26 and 46

percent of herds will receive bST (low and high scenarios), respectively. By 2000, these percentages rise to 37

and 64 percent, respectively. A medium scenario is 46

percent.

Relatively high rates of adoption are also predicted for

the Appalachian region (see figure A-5). By 1995,

between 27 and 48 percent of herds will receive bST (low

and high scenarios, respectively). By 2000, these percentages rise to 40 and 70 percent, respectively. A medium

scenario is 46 percent.

Adoption rates in the Northeast are similar to those in

the Lake States (see figure A-6). By 1995, between 25 and

44 percent of herds will receive bST (low and high

scenarios, respectively). By 2000, these percentages rise

to 34 and 59 percent, respectively. A medium scenario is

43 percent.

The adoption pattern in the Pacific Region, the fastest

growing dairy region of the United States, is accelerated

relative to that of all other regions (see figure A-7). By

1995, between 45 and 63 percent of herds will receive bST

(low and high scenarios, respectively). By 2000, these

percentages rise to 66 and 81 percent, respectively. A

medium scenario is 67 percent. The strong coefficients of

size and milk output per cow drive the adoption of bST in

this region at a high rate.

Overview of Results

The dairy industry has one of the highest rates of

productivity increases in U.S. agriculture. Yet, adoption

of existing proven technologies is not universal among

dairy producers. Though technologies such as artificial

insemination and herd record systems have existed for

many years, these technologies have only been adopted

by 30 to 40 percent of producers in several major dairy

regions. The most technically efficient producers (highest

ratio of milk output to farm resources) are the most likely

to adopt new technologies. Using regression techniques,

this analysis establishes that producers with high levels of

milk per cow and large operations are more likely to adopt

new technologies (a finding consistent with scientific

literature on adoption of new technologies).

Given that bST has similar characteristics to previous

dairy technologies, improvement in productivity from an

increasing knowledge base will drive its adoption.

Analysis of productivity measures in the major dairy

regions suggest that between 50 and 70 percent of dairy

producers in the United States will adopt bST by the year

2000. The Pacific region will lead all regions in adoption,

possibly reaching 80 percent by 2000.

The projected rates of adoption in this analysis are

lower than other studies based on differing methodologies. Rather than basing predictions on historical trends,

for example, Lesser, McGrath, and Kalter use contingent

surveys of producers and arrive at higher adoption rates.

There is little to suggest that the adoption of bST will vary

from past adoption practices by dairy operators. bST is

simply a continuation of numerous other productive

technologies in the dairy industry. The lower projected

rates of adoption are, therefore, the more realistic

projections of actual adoption rates.

1.

2.

3.

4.

5.

6.

7.

8.

9.

Appendix A References

Aradhyula, S. and Krog, D.R., ‘‘Biotechnology and the Dairy

Herd Buy Out Program: Implications for the U.S. Da.@

Industry,” Paper presented at The American Agr. Econ.

ASSOC., Lansing, ~, August 1987.

l?allert, R. et al. “bST and The Dairy lidustry: A National,

Regional, and Farrn-Uvel Analysis, ” USDA Agricultural

Report 579, 1987.

Feder, G., ‘‘Farm Size, Risk Aversion and The Adoption of

New Technology under Uncertainty,” O@ord Economic

Papers 80(32).

Just, R.A. and Zilberman, D., “Stochastic Structure, Farm

Size and Technology Adoption in Developing Countries,”

O@ord Economic Papers 83(35):307-28.

Kalter, R.J. et al., “Biotechnology and the Dairy Industry:

Production Costs and Commercial Potential of the Bovine

Growth Hormone,” A.E. Research Report No. 82-22, 1984,

Department of Agricultural Economics, Cornell University.

Kaiser, H. and Tauer, L., ‘Impact of the bovine Somatotropin

on U.S. Dairy Markets Under Alternative Policy Options,’

North Cent. Jour. of Agri. Econ., 89(1 1).

Ixxser, W., McGrath, W., and Kalter, R., “Projecting

Adoption Rates: Application of an ex ante Procedure to

Biotechnology Products,” North Cent. Jour of Agri. Econ

86(8):2.

McGuckin, J. T., “Adoption of bovine Somatotropin: A

National and Regional Analysis,” OTA commissioned

background paper, Washington, DC, 1990.

Sellschopp, J. and Kalter, R., “Bovine Somatotropin: Its

Impact on the Spatial Distribution of the U.S. Dairy

Industry,’ A.E. Research 89-14, Department of Agricultural

Economics, Cornell University, 1989.
Appendix B

Detailed National and Regional Impacts of bovine

Somatotropin and Other Emerging Technologies

Under Alternative Dairy Policies

The national policy evaluation.s in chapter 5 were

conducted with an econometric-simulation model of the

U.S. agricultural sector (AGSIM). AGSIM is a disaggregate agricultural-sector model that utilizes econometric

supply and demand relationships for major crop and

livestock commodities. Figure B-1 illustrates the conceptual framework of the simulation model. The model

contains regional supply representations of major crop

commodities and an annual livestock supply sector. For

this study a regional dairy supply component was

incorporated into the model to analyze regional impacts

of technology adoption under alternative dairy policies.

National demand relationships for all crop and livestock

commodities are utilized in the model.1

Supply relationships in the model are specified as

functions of expected returns to production, Thus, aggregate supply relationships directly reflect the microlevel

impacts of policies or technological change that change

revenue components (e.g., yield) or cost components

(e.g., product cost) or both. Further details of the crop

portion of the model and regarding use of the model for

policy analysis are contained in Taylor (2,3).

The livestock model (LIVESIM) utilized in the agricultural-sector model described above was developed by

Peel (l). LIVESIM contains separate market representations for fed beef, nonfed beef, pork broilers, turkey,

milk, lamb, eggs, and veal. The original aggregate supply

relationships for milk production were replaced by

regional supply equations.

Of particular importance for this study is the disaggregation of beef and dairy sources as contributors to fed and

nonfed meat supplies in the model. The indirect impacts

of dairy policy alternatives on other livestock subsectors

are captured endogenously (within the model) through

changes in fed and nonfed beef supply. Changes in dairy

returns influence not only milk production but also impact

calf crop, cow slaughter, and calf slaughter. The importance of these impacts was highlighted by the controversy

over the dairy termination program of 1986. That program

caused a significant decline in cattle prices.

Crop and livestock sectors are directly linked in the

market in LIVESIM. Livestock returns (which drive

livestock supply equations) are partly determined by feed

Figure B-l-Simulation Model

I Read initial values I

E = -

E

Returns expectations

for crops and livestock

nun

Solve for market equilibrium

prices 1

H

I

Crop and livestock

demands I

SOURCE: D.S. Peel, “National and Regional Impacts of bovine Somatotropin Adoption Under Alternative Dairy Program Policies, ’’OTA

commissioned background paper, Washington, DC, 1990.

1~~ ~PP~D~ is bw~ ~~ fi~ o~ ~O~~~iO~ed baC@O~d paper ‘‘NatiO~ and R@O~ ~pacts Of ~Vine somatotir)pin Adoption Under

Altcrmtive Dairy Program Policies” prepared by Derrell S. Peel, Oklahoma State university. It is available through the National Technical Information

Service.

–93–
94 U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

costs calculated internally from feed rations and crop

prices. Changes in crop prices directly impact livestock

returns and thus livestock supply. In turn, total livestock

production in part determines demands for the individual

crops and influences crop prices accordingly.

The Regional Dairy Model

For this analysis, total milk supply is determined from

regional equations for milk production per cow and dairy

cow inventory. Data for the econometric estimates were

aggregated from State data. Ten regions, consistent with

the standard USDA production regions (discussed in ch.

2), were used in the model. Dairy returns for each of the

regions is based on a USDA data series known as the

regional cost of production budgets for dairy.

Market-clearing prices are calculated by balancing raw

milk production, on a per-capita basis, against per-capita

milk demand. The resulting national milk price is

regionalized in the model via regressions of regional milk

price on national milk price. These regional price

relationships implicitly capture the net effect of the

classified pricing system on regional milk prices.

Modeling Dairy Policy

The econometric-simulation model captures the primary impacts of milk price support programs by calculating milk and dairy returns based on the maximum

equilibrium market price or on an exogenously specified

milk support price. Thus milk production per cow, dairy

herd inventory, dairy replacement inventory, and the

dairy impact on cow slaughter and calf crop all reflect the

influence of the milk support price.

Government support of milk production is treated on a

raw milk equivalent (ME) basis. Since the government

only purchases manufactured milk products, all government purchases are made at a manufacturing milk price,

which is assumed to be $1 per hundredweight (cwt) less

than the all-milk price.

This analysis assumes that a minimum level of

government milk purchases of 3 billion pounds of milk

annually will be required for program needs. Government

may purchase more than this minimum level to balance

milk supply and demand at the prevailing support price.

Modeling Technology Adoption

The impacts of bovine Somatotropin (bST) adoption

and other emerging technologies were incorporated into

the econometric-simulation model under the following

assumptions:

1. output per cow increases 1.5 percent per year in base

scenario without bST,

2. output per cow, due to bST, increases 1,320 pounds

annually,

3. the daily cost of bST is $0.30 per cow,

4. cows are treated for 150 days annually,

5. overall feed efficiency is improved by 5 percent for

treated cows.

The model increases feed use marginally for additional

milk production resulting from bST use. However, feed

required per cwt of milk production is 5 percent lower

with bST because cow maintenance requirements are

spread over more units of production. The model also

assumes that per cwt variable costs for other production

expenses increase incrementally with bST use.

Three alternative rates of industry adoption of bST

(low, medium, and high) were considered for the 10

production regions of the United States. Complete

presentation of the development and assumptions of the

alternative adoption rates are presented in appendix A.

Results

Various combinations of the policy alternatives described above and the alternative adoption rates for bST

were analyzed. In addition, the possibility that bST

adoption could have some exogenous impact on milk

demand was considered in several scenarios.

Impact of bST Adoption

Of primary concern in formulating dairy policy is the

impact that bST adoption will have on total milk

production and consequently on government purchases

related to the dairy program. Figure B-2 shows total milk

production under different levels of bST adoption. This

figure assumes an annual trigger adjustment for milk

support price. The maximum impact in terms of addiFigure B-2—Projected Total Milk Production With

Trigger Policy Under Alternative bST Scenarios

160 ● *

158-

156-

,e

154-

g

●

.5 152 –

=—m

150-

148-

. . . . .

./ ; : .

~---- ,

144- I : ; ~

1990 1991 1992 1993 1994 1995 1996 1997 1{

Year

---, No bST _ - Low.bST — Medium bST --- High bST

SOURCE: Office of Technology Assessment, 1991.
Appendix B--DetailedNational and Regional Impacts of bovine Somatotropin and Other Emerging Technologies . 95

Figure B-3-Projected Milk Production per Cow

174

172-

170-

168- :::: ;

142--::: :

140 ““’:: :

1990 1991 1992 1993 1994 1995 1996 1997 1998

Year

--- No b S T = - L OW b S T — Medium bST --- High bST

SOURCE: Office of Technology Assessment, 1991.

tional milk production occurs in 1994, with total production of 154 billion pounds under high bST adoption

compared with 151 billion pounds under low bST

adoption. Figure B-3 shows the impact of bST on milk

cow productivity.

Differences in milk production due to alternative levels

of bST adoption would be more pronounced if the milk

support price was not triggered down (see figure B-4).

With no bST, the baseline simulation of the model results

in a single $0.50 per cwt adjustment in milk-support price

from $10.60 to $10.10 in 1992. Under each of the three

alternative levels of bST adoption, an additional $0.50 per

cwt decrease to $9.60 in 1994 is required to keep

government purchases of milk under the 5 billion pound

level. Figure B-5 shows the high levels of government

purchases of milk in 1991 and 1993 that precipitate the

reductions in milk support price.

Comparison of Alternative Policies

The implications of bST adoption depend on the policy

scenario under which adoption takes place. This section

considers the impacts of alternative policy options on

milk production and price under the assumption of a

medium level of adoption.

Figure B-6 shows total milk production under the fixed

support price, annual trigger, and quota policies. The

impact of the dairy termination (buyout) program is not

included in this section because government milk purchases never exceed 15 billion pounds-the amount

assumed to initiate a buyout program. Milk production

generally increases to similar levels under each of the

policies. However, milk production is lowest for the quota

and highest for the freed support scenario for most years.

The trigger policy results in milk production levels

Figure B-4—Projected All Milk Price With

Trigger Policy Under Alternative bST Scenarios

13.2 I

12.8

12.6

12.4

w i 1

● :. . . =

12.2 . ● * ,

4

,* ● .

●

12.0 ● .* ● ,

4 ., ● +* . .,

. . . .

I

\.

10.6 % .

I

1990 1991 1992 1993 1994 1995 1996 1997 1998

Year

= ■ = - No bST — Low bST --- Medium bST --- High bST

SOURCE: Office of Technology Assessment, 1991.

between those associated with the other two policies and

production that is somewhat more variable from year to

year.

The fixed support price and quota scenarios maintain a

milk support price of $10.60 (see figure B-7). The all-milk

price is $1.00 greater than the manufacturing price of

milk. Beginning in 1995, milk price under the quota

policy begins to rise over the support level. In contrast, the

trigger policy allows milk price to fall substantially before

it rises again as the industry cuts production.

The impacts of the alternative policies on government

purchases of milk are summarized in figure B-8. As

expected, the fixed support price policy is the most

expensive, resulting in government purchases well above

the minimum milk purchase level in order to maintain the

support price. The quota and trigger policies are able to

keep government purchases much lower although the

trigger is slower to compensate for the impact of bST

adoption. Annual government purchases between 1991

and 1998 average about one-third less under the trigger

policy compared to the fixed support price.

The trigger and quota policies accomplish their goals

by different means. All of the policies result in increased

government purchases for milk in 1991, the first year of

bST adoption. However, it is assumed that within a year

the quota policy is able to reduce the size of the dairy herd

to a level that limits government purchases for excess

milk and maintains the milk price at the higher support

price ($10.60). The trigger policy reduces the support

price in 1992 and again in 1994 before controlling

government purchases of excess milk.
96 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Figure B-5—Projected Government Milk Purchases With Trigger Policy Under Alternative bST Scenarios

8

7

6

5

~

g 4 .—=.—m

3

2

1

0

I I I

1990 1991 1992 1993 1994

_ No bS . . . . . . . . . . T

SOURCE: Office of Technology Assessment, 1991.

Regional Impacts

In addition to concerns over the national impacts of

bST adoption under different policy scenarios are concerns about how the technology will affect the industry’s

regional structure and dynamics. One way to summarize

what the regional impacts of bST adoption might be is to

analyze changing milk production patterns across the

Nation.

Figure B-9 shows total production shares for the 10

production regions of the country in 1990 and 1998. This

chart assumes a trigger policy for adjusting milk support

price and a medium level of bST adoption. Trends already

observed in the dairy industry continue in this simulation.

Declining market shares are noted for the Corn Belt and

the Northern Plains with smaller reductions in the Delta,

Appalachian, and Southeast. Largest increases in market

share are noted in the Pacific region. The Lake States and

Northeast maintain roughly their current market shares

over this period.

I I I I

1995 1996 1997 1998 1999

my Medium bST _ High b S T

Figure B-10 shows the impact of alternative policies on

regional market shares, with medium level of bST

adoption. There is little difference between the impact of

the fixed support price and that of trigger policies in

regional market shares. The quota does not allow market

shares to change as much as the other policies. Rather, the

quota is assumed to fix market shares at 1990 levels.

Some change occurs because of trends in milk cow

productivity even though the dairy herd is fixed in size.

Alternative Demand Scenarios

Continued consumer concern over bST prompted

consideration of scenarios with exogenous changes in

milk demand reflecting adverse consumer reaction to bST

in milk. Three alternative demand scenarios were compared in the model:

Baseline: used in all previous scenarios

Temporary: large temporary demand reduction with small

permanent demand reduction

Permanent: large permanent demand reduction
Appendix B--DetailedNational and Regional Impacts of bovine Somatotropin and Other Emerging Technologies ● 97

Figure B-6-Projected Total Milk Production

With Medium bST Adoption Under Alternative

Dairy Policies

Figure B-7—Projected All Milk Price With

Medium bST Adoption Under Alternative

Dairy Policies

1990 1991 1992 1993 1994 1995 1996 1997 19

Year

— Fixed -- Trigger -- = Quota

SOURCE: Office of Technology Assessment, 1991.

Figure B-8—Projected Government Milk

Purchases With Medium bST Adoption Under

Alternative Dairy Policies

8

10

9 -

1

.,-

8 -

7

G 6

g 5

.-

‘ 4 I

1990 1991 1992 1993 1994 1995 1996 1997 1998

Year

❑ Fixed RI Trigger ■ Quota

SOURCE: Office of Technology Assessment, 1991.

Details of these alternative demand scenarios are presented in chapter 5.

Alternative Milk Demand Under Current Policy—

Figure B-n illustrates the impacts of alternative milk

demands assuming a continuation of the current trigger

policy for adjusting milk support price and the medium

level of bST adoption. Changes in milk demand have

‘zp

6s

10.6 ] : :

I I I

1990 1991 1992 1993 1994 1995 1996 1997 1

Year

— Fixed -- Trigger --- Quota

SOURCE: Office of Technology Assessment, 1991.

Figure B-9—Actual and Projected Regional

Milk Market Shares With Trigger Price Policy,

1990 and 1998.

30 I

28

26

24

? 22

g 2 0 1

4 -

CB LS NP SP DL MT PA NE AP SE

Region

~ 1990 - 1998

Key: LS - Lake States SP - Southern Plains CB - Corn Belt

NE - Northeast NP - Northern Plains AP - Appalachian

PA - Pacific SE - Southeast

MT - Mountain DL - Delta States

SOURCE: Office of Technology Assessment, 1991.

large implications for milk price. While the base level of

demand results in milk price near $12 per cwt for all years,

a permanent large demand reduction would allow milk

price to fall as low as $8.60 in 1997 before beginning to

rise.

Figure B-12 shows the level of government milk

purchases under the different levels of demand. Reduced
98 ● U.S. Dairy Industry at a crossroad: Biotechnology and Policy Choices

Figure B-l O-Projected Change in Milk Market

Shares for Alternative Dairy Policies Between

1990 and 1998

4 -

3 -

2 -

1 -

0 -

-1-

.

-L ‘ — I

I

I I I I I I i I

CB LS NP SP DL MT PA NE AP SE

Region

m Fixed D Trigger m Quota

Key: LS - Lake States SP - Southern Plains CB - Corn Belt

NE - Northeast NP - Northern Plains AP - Appalachian

PA - Pacific SE - Southeast

MT - Mountain DL - Delta States

Figure B-1 l—Projected All Milk Price With

bST Adoption Under Alternative Milk Demands

15

14

13

[. . . . . . I

8

1 : : ~ “ : “

1990 1991 1992 1993 1994 1995 1996 1997 1998

Year

— Base ● ■ - Permanent Demand -- Temporary Demand

(no change) Reduction Reduction

SOURCE: Office of Technology Assessment, 1991.

SOURCE: Office of Technology Assessment, 1991.

milk demand, under both demand reduction scenarios,

results in government milk purchases of 21 billion pounds

in 1991 at a cost of about $2.5 billion. With the temporary

demand reduction, government purchases decline fairly

rapidly as the support price declines. With the permanent

large demand reduction, however, government purchases

decline slowly as the trigger lowers support price.

Policy Comparison With Permanently Reduced Milk

Demand—In the face of large surpluses in milk production, the implications of the alternative policies are more

sharply delineated. Assuming a permanent large reduction in milk demand, and future excess production, the

choice of policies clearly will have much larger impacts

than it would under the baseline demand scenario.

The reduced demand scenario is useful, not because it

is a likely result of bST adoption, but because similar

conditions (in terms of relative supply and demand) could

prevail for a number of other reasons. For example, if bST

results in greater average productivity increases than is

here assumed, or if adoption rates are substantially higher,

then supply excesses similar to those under the reduced

demand scenario could result. This scenario thus can be

viewed as a proxy for a number of supply or demand

situations that could produce large surpluses of milk.

Figure B-13 shows the impact of reduced demand on

milk production (given medium bST adoption) with

alternative policies-fixed support price, trigger-adjusted

support price, production quota, and a dairy termination

program. Differences in the time path of milk production

under the quota and the other policies are readily apparent.

The quota results in a quick downward adjustment in

dairy herd size necessary to avoid large government

expenditures while maintaining milk price at the $10.60

support level. The dairy termination program (buyout

occurs in 1992) adjusts herd size in a manner similar to the

quota in 1992, but herd size and total milk production

climb rapidly before declining again in 1998. The trigger

policy results in an eventual but much delayed decline in

milk production. The fixed support price policy, as

expected, maintains the highest level of milk production

of the alternative policies.

The implications of the alternative policies on milk

price are likewise quite dramatic (see figure B-14). The

fixed support and quota policies maintain a milk support

price of $10.60. Figure B-14 shows that the all-milk price

correspondingly is at the minimum level of $11.60 with

these policies after bST is adopted (and the demand shift

occurs). The trigger and dairy termination programs allow

milk support price to adjust downward in the face of

excess milk production. The trigger results in milk price

declines to a minimum of $8.60 in 1997. The dairy

termination program also allows milk price to fall to this

level but with a delay of 1 year compared to the trigger

policy. This is because the dairy termination program

buyout occurs in 1992, avoiding the need for a reduction

in milk support price prior to 1993.
Appendix B-Detailed National and Regional Impacts of bovine Somatotropin and Other Emerging Technologies ● 99

Figure B-15 reiterates these impacts in terms of

government milk purchases. It is significant to note that

while the dairy termination program reduces milk purchases and expenditures quite successfully in 1992 (the

year that liquidation occurs), milk production quickly

bounces back and milk program purchases are not much

lower than those associated with the trigger policy alone.

From 1995 to 1998, purchases under the trigger policy are

actually less than they are under the dairy termination

program.

Impacts on Other Agricultural Sectors

The adoption of bST appears to have relatively minor

impacts on agricultural sectors outside of dairy. Table B-1

summarizes agricultural commodity prices over the

period 1995-1998 for the freed support price, triggeradjusted support price, and quota policies with and

without bST adoption (medium level).

The adoption of bST does create a marginal increase in

demand for feed in the dairy industry. However, the net

effect, when all markets adjust, is extremely small.

Among all crops, impacts on the all hay price are largest

with bST adoption; average hay prices increase by $1.25

to $2.50/ton depending on the policy scenario.

Impacts in the livestock sectors are limited mostly to

cattle, and average price effects are minute. Interestingly,

how bST adoption impacts yearling, calf, and cow prices

depends on the policy scenario. This indicates that dairy

policy can affect the timing and magnitude of changes in

the dairy herd.

The impact of a dairy termination program on livestock

prices is of particular interest. Figure B-16 shows the

dynamic paths of yearling cattle price for alternative dairy

policies. (Figure B-16 also assumes a permanent milk

demand decrease in conjunction with bST adoption.)

Figure B-12—Projected Government Milk Purchases With bST Adoption Under Alternative Milk Demands

22 1

c

.—o

=

z

21

20

19

I

1 8 -

17–

16

1 5 -

14

13

12

11

10

9

8

7

6

5

4 /m3 ,,,, :.:.:.:

2 g$

:.:.:.:

1 – ;~::.:.:.:

o

x+

1990 1991 1992 1993 1994 1995 1996 1997 1998

Year

❑ Bas e ❑ Temporary Demand ■ Permanent Demand

No Change Reduction Reduction

SOURCE: Office of Technology Assessment, 1991.
100 . U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Figure B-13—Projected Milk Production With

Permanently Reduced Milk Demand Under

Alternative Dairy Policies

162

160- :;;:;: :

156- :::: ’

. 0

150-

~ 146 -

= 144 -

142- I ‘ ; ● ’: ; : : ~;&@@

140- : : : : : : \ ;@@ ;

138- ; i ; : : : ~@:@@e : :

!

136- : :’: ;@ :

134- : 4 : ,.’ ; ,,- : : : :

132- : $

~ 0

130 ‘

‘$- : ; ; ; :

I I I 1990 1991 1992 1993 1994 1995 1996 1997 1998

Year

— Fixed Price ‘--Trigger -- Quota . . Dairy Termination Program

SOURCE: Office of Technology Assessment, 1991.

Figure B-14-Projected All Milk Price With

Permanently Reduced Milk Demand Under

Alternative Dairy Policies

13.5 ,,, ,,, ,

13.0- :::::: :

12.5- :::::: :

12.0-

. . d

11.5- >..* “.* : : : : : 7

+ ’

1 1.0– : ● ?*+ ‘~. : : : :

- . .

10.5

10.0

9.5

1

● ✚☛● ✎

1990 1991 1992 1993 1994 1995 1996 1997 1998

Year

— Fixed -.-Trigger - -Quota = = = Dairy Termination Program

SOURCE: Office of Technology Assessment, 1991.

Figure B-15—Projected Government Milk Purchases With Permanently Reduced Milk Demand

24

22

20

18

16

14

g

.: 12.

=m

1 0

8-

6

4.

2-

0-

Under Alternative Dairy Policies

m

;:;::. . . . . . ;:;;;.:::::. . . . . . ;:::: ..,.,.;::::. . . . . . . :::::, . . . . . .

1990 199l

❑ Fixed

1992 1993 1994 1995

❑ Trigger ❑ Dairy Termination Program

Year

❑ Quota

SOURCE: Office of Technology Assessment, 1991.
Appendix B--Detailed National and Regional Impacts of bovine Somatotropin and Other Emerging Technologies . 101

Table B-l—Impacts of bST Adoption on Other Agricultural Sectors, 1995-98

Policy scenarios

Fixed price support Trigger price Quota

Commodity (units) NO bST bST No bST bST No bST bST

Corn ($/bu) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.85 2.86 2.85 2.86 2.85 2.86

Grain sorghum ($/bu) . . . . . . . . . . . . . . . . . . . . . 2.54 2.54 2.54 2.54 2.54 2.54

Barley ($/bu) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.60 2.61 2.60 2.61 2.60 2.61

Oats ($/bu) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.39 1.40 1.39 1.40 1.39 1.39

Wheat ($/bu) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.09 3.09 3.09 3.09 3.09 3.09

Soybeans ($/bu) . . . . . . . . . . . . . . . . . . . . . . . . 6.46 6.47 6.46 6.46 6.46 6.46

Cotton ($/lb) . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.86 0.86 0.86 0.86 0.86 0.86

All hay ($/ton) . . . . . . . . . . . . . . . . . . . . . . . . . . . 103.06 105.55 102.95 104.64 102.77 104.03

Yearling cattle ($/cwt) . . . . . . . . . . . . . . . . . . . . 74.87 74.94 74.92 74.79 75.08 74.97

Calf ($/cwt) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81.84 82.01 81.93 81.84 82.16 82.06

cows ($/cwt) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56.97 57.11 57.05 56.84 57.33 57.14

Hogs ($/cwt) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.08 51.09 51.06 51.11 51.01 51.04

Broilers (@/lb) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.38 61.45 61.43 61.43 61.46 61.47

Turkeys (¢/lb) . . . . . . . . . . . . . . . . . . . . . . . . . . . 69.32 69.38 69.41 69.29 69.55 69.49

Eggs (¢/dozen) . . . . . . . . . . . . . . . . . . . . . . . . . 81.15 81.20 81.14 81.18 81.14 81.16

Lamb ($/cwt) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91.46 91.63 91.45 91.62 91.41 91.51

KEY: bu==bushel; cwt=hundredweight (100 pounds); Ib= pound.

SOURCE: Office of Technology Assessment 1991.

Figure B-16--Projected Yearling Cattle Price

With Permanently Reduced Milk Demand

Under Alternative Dairy Policies

76

: /

7 5 - : :

7 3 -

~ 71 – *: e 0, : :

6 9 - ;

1990 1991 1992 1993 1994 1995 1996 1997 1998

Year

—Fixe d -.-Trigger --Quota --- DairyTermination Progam

SOURCE: Office of Technology Assessment 1991.

Annual yearling cattle prices are about $4.35 per cwt

lower in 1992 as a result of the dairy termination program

(compared to the trigger policy). Cow prices in 1992 are

over $6.00 per cwt lower with the dairy termination

program compared to the trigger policy. The quota policy

affects cattle price in much the same way as the dairy

termination program; its impacts are slightly less in

magnitude in 1992, the year that the quota is imposed, but

prices are slightly lower under the quota relative to the

dairy termination program for several more years.

1.

2$

3

Appendix B References

Peel, D. S., “A Dynamic Econometric-Simulation Model of

the U.S. Livestock Industry,” Ph.D. dissertation, Department

of Agricultural Economics, University of Illinois, 1989.

Taylor, C.R., “A Description of AGSIM, an EconometricSimulation Model of Regional Crop and National Livestock

Production in the United States,” staff paper ES89-1,

Department of Agricultural Economics and Rural Sociology,

Auburn University, Auburn, Alabama, January 1989.

Taylor, C.R., “AGSIM User’s Manual, Version 89.5,” staff

paper ES89-11, Department of Agricultural Economics and

Rural Sociology, Auburn University, Auburn, AL, October

1989.
Appendix C

Detailed Farm Level Impacts of bovine Somatotropin

and Other Emerging Technologies Under

Alternative Policy and Demand Scenarios

The farm level impacts in chapter 5 were determined by

a Monte Carlo simulation model known as the Farm Level

Income Tax and Policy Simulation Model (FLIPSIM)

developed by Richardson and Nixon (4) at Texas A&M

University. The model is capable of simulating representative dairy farms in different regions of the United States

under alternative policy and technology assumptions.l

Analyzing the consequences of alternative technologies on the economic viability of a representative farm

involves several steps. First, data for the representative

dairy farm that is using existing technologies must be

developed. Second, modifications to the basic dairy

farm’s input/output coefficients must be made for each

technology change to be analyzed. For bST, this is done

by annually changing the milk per cow and the lactating

cow ration and by increasing variable costs per cow to

reflect bST purchases. The result is a new representative

farm that has adopted bST. Third, projections for milk

prices, feed prices, cattle prices, annual percentage

changes in herd size, and macroeconomic variables

(interest and inflation rates) for the policy/technology

scenario being analyzed are merged with the farm’s data.

Projections of regionalized milk prices and feed prices are

provided by the LIVESIM model (described in app. B),

and macroeconomic variables are developed by the

COMGEM/AG-GEM model (3).

Representative Dairy Farms

The regions for analysis are the Lake States, Northeast,

Southeast, and Southwest. Two different-size dairy farms

in each region—moderate and large farms-are considered. In the Lake States, the representative moderate-size

farm owns 52 cows, and the large farm owns 125 cows;

both farms own 185 acres of cropland and farmstead, with

155 acres devoted to the production of dairy feed (see

table C-l). These farms are most representative of dairy

farms in Minnesota. In the Northeast, the representative

moderate-size farm owns 52 cows, and the large farm

owns 200 cows. The moderate-size Northeast farm

devotes 140 acres to the production of hay, corn silage,

haylage, oats, corn, and pasture. The large Northeastern

farm has 450 acres of hay, corn silage, haylage, oats, and

corn, and 50 acres of pasture. The moderate-size farm is

most representative of Pennsylvania dairy farms and the

large farm represents New York dairy farms.

The moderate and large Southwestern dairy farms,

respectively, own 350 and 1,500 milk cows (see table

C-1) and only 25 acres of land. The two farms are

representative of dairy herds in California and Arizona.

The moderate-size Southeastern dairy farm has 200 cows

and 388 acres and is most representative of farms in

Georgia. The Georgia farm has 305 acres devoted to

coastal hay and sorghum silage production and 50 acres

devoted to pasture. The large Southeastern dairy has

1,500 cows and owns 873 acres, which are largely (750

acres) devoted to pasture. The large Southeastern farm is

most representative of large dairies in Florida.

The initial debt-to-asset ratio was assumed to be 40

percent for all of the farms. All land, machinery, and

livestock had 40-percent debt at the beginning of 1989

(see table C-l). This level of debt represents a moderate

initial debt level. Each of the eight representative farms

were simulated over the 1989 to 1998 planning horizon

for alternative assumptions about the dairy farm program

and the adoption of bST.

Technology Scenarios

The economic consequences of bST adoption were

analyzed assuming bST was introduced in 1991, and the

farm either adopted it in 1991 or did not adopt bST

throughout the planning horizon. Initial milk production

per cow was trended up at 1.5 percent per year in the base

situation without bST (see table C-2). For the bST

adoption scenarios, annual milk production per cow with

bST was increased by 1,320 pounds each year from 1991

to 1998. This increase in milk per cow due to the adoption

of bST assumes lactating cows are treated for 150 days

during each lactation. All cows in the herd were assumed

to be treated at an annual cost of $45 per cow.

The quantity of feed required for bST-treated cows

increased marginally due to the increased milk production

per cow. A linear program (LP) model in FLIPSIM was

used to estimate a balanced dairy ration for the higher

producing dairy herd. Research by Chalupa and Galligan

(1) indicates that the nutritional requirements for bSTtreated cows are the same as they are for naturally high

lllis appm~ is basedon tie OTAcornmissioned background paper “Farm Uvelhnpacts of bovine Somatotropin Introduction and Adoption Under

Alternative Farm Policies” prepared by James W. Richardso~ Texas A&M University. It is available through the National Technical Information

Service.

–lo2–
Appendix C--Detailed Farm Level Impacts of bovine Somatotropin and Other Emerging Technologies ● 103

Table C-l—Characteristics of Representative Moderate-Size and Large Dairy Farms in

the Lake States, Northeast, Southwest, and Southeast

Lake States Northeast Southwest Southeast

Moderate Large Moderate Large Moderate Large Moderate Large

Number of dairy cattle:

cows . . . . . . . . . . . . . . . . . . . .

Calves . . . . . . . . . . . . . . . . . . .

Heifers. . . . . . . . . . . . . . . . . . .

Bulls . . . . . . . . . . . . . . . . . . . . .

Calves born . . . . . . . . . . . . . .

Assets ($1,000):

Land . . . . . . . . . . . . . . . . . . . .

Buildings and machinery . . . .

Cattle . . . . . . . . . . . . . . . . . . . .

Total . . . . . . . . . . . . . . . .

Off-farm salary ($1 ,000) . . . .

Minimum family living

($1,000) . . . . . . . . . . . . . . .

Labor costs ($1 ,000) . . . . . . .

Milk/cow (cwt) . . . . . . . . . . . .

52

21

25

0

48

133.1

262.8

68.6

469.5

9.8

19.8

12.7

168.5

125

48

57

0

113

295.0

482.6

161.6

940.2

0

24.8

37.3

168.5

52

20

23

0

47

274.2

260.8

73.0

608.0

9.8

19.8

11.3

179.4

200

75

88

0

178

640.1

503.0

251.5

1,394.6

0

30.9

70.0

178.3

350

130

152

7

326

117.9

467.3

511.4

1,096.6

0

43.3

115.8

185.9

1,500

495

612

25

1,388

491.8

1,080.8

2,284.9

3,857.5

0

61.9

444.2

196.9

200

75

88

0

176

812.9

487.0

269.4

1,569.3

0

30.9

62.8

153.4

1,500

432

503

25

1,268

4,591.1

1,139.2

1,992.3

7,722.6

0

61.9

488.1

153.1

SOURCE: Office of Technology Assessment, 1991.

producing cows. Thus, it was not necessary to change the

input/output coefficients in the ration-balancing LP—the

increased milk production per cow caused the LP to feed

the cow more protein, energy, and forage. In general, the

ration for bST cows contained 7 to 10 percent more

forage, 9 to 12 percent more grain, and 10 to 13 percent

more soybean meal (or whole cottonseed) than the ration

for control cows.

The new values for average annual milk per cow and

bST costs were used to modify initial farm variables to

account for bST adoption. All other variables for the

representative dairy farms were assumed to remain

constant at pre-bST levels. Of 16 representative farms, 8

adopt bST in 1991, and 8 do not adopt bST. The 16 farms

were simulated under alternative dairy policy scenarios to

quantify the interaction between technology adoption and

farm programs.

Farm Program and Milk Demand Scenarios

Four farm programs were selected for the analysis:

trigger price, fixed price support, production quota, and

dairy termination program. Each of the policies was

analyzed with a commodity-specific livestock simulation

model, LIVESIM (discussed in app. B), under the

assumption that the 1985 farm program for crops would

continue through 1998 (2). The LIVESIM analyses of

these four dairy policies were done for a no-bST scenario

and for a scenario with a medium rate of adoption

beginning in 1991. Three different milk-demand scenarios were analyzed to incorporate the possibility of milk

demand changing in response to bST introduction.

The trigger-price dairy policy is similar to policy from

1985 to 1990 with the milk-support price decreasing 50

cents per hundredweight (cwt) each year that the Commodity Credit Corporation (CCC) milk purchases are

expected to exceed 5 billion pounds of milk equivalent.

The support price is increased 50 cents per cwt if CCC

purchases of milk are expected to fall short of 2.5 billion

pounds. This policy is also similar to the producer

assessment option in the 1990 farm bill because the

assessment will effectively trigger reductions in producer

returns as milk price declines. The fixed support policy

assumes that the dairy support price is held constant for

all years of the planning horizon. The production-quota

policy calls for the continuation of the trigger-price policy

with provisions for a quota to be imposed if CCC milk

purchases exceeded 7.0 billion pounds of milk equivalent.

Similarly, the dairy termination program would continue

the trigger-price policy but permit a one-time dairy

termination if CCC milk equivalent purchases exceed

15.0 billion pounds in 1 year. The dairy termination

program is analyzed only for the large demand decrease

scenario, as this is the only demand situation that triggers

the termination.

The three milk-demand scenarios respectively assume

constant demand, a slight decrease in demand, and a

significant decrease in demand after the introduction of

bST. The small demand reduction scenario assumes that

milk demand will decrease 10 percent in 1991,5 percent

in 1992 (i.e., demand increases from 1991 to 1992), and

2.5 percent each year from 1993 to 1998. The large

demand reduction scenario assumes that milk demand is

10 percent lower than it currently is in each year from

1991 to 1998. The trigger price, fixed price support, and
104 . U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Table C-2—Average Annual Production of Milk/Cow for Moderate-Size Representative Dairy Farms,

in Selected Regions, With and Without bST, 1989-98 (cwt/year)

Lake States Northeast Southwest Southeast

Years No bSTa

bSTb No bST bST No bST bST No bST bST

1989 . . . . . . . . .

1990 .....,.. .

1991 . . . . . . . . .

1992 . . . . . . . . .

1993 . . . . . . . . .

1994 . . . . . . . . .

1995 ...., . . . .

1996 . . . . . . . . .

1997 . . . . . . . . .

1998 . . . . . . . . .

168.5

171.0

173.6

176.2

178.8

181.5

184.2

186.9

189.8

192.6

168.5

171.0

186.8

189.4

192.0

194.7

197.4

200.1

203.0

205.8

179.4

182.0

184.8

187.5

190.4

193.2

196.1

199.1

202.0

205.1

179.4

182.0

198.0

200.7

203.6

206.4

209.3

212.3

215.2

218.3

185.9

188.7

191.5

194.4

197.3

200.2

203.2

206.3

209.4

212.5

185.9

188.7

204.7

207.6

210.5

213.4

216.4

219.5

222.6

225.7

153.4

155.7

158.1

160.4

162.8

165.3

167.8

170.3

172.8

175.4

153.4

155.7

171.3

173.6

176.0

178.5

181.0

183.5

186.0

188.6

aOutput per cow increases 1.5 percent per year without bST.

bST, introduced in 1991, increases output per cow 1,320 Ibs. per year.

SOURCE: Office of Technology Assessment, 1991.

quota policies were analyzed with and without bST

assuming no change in milk demand. The trigger price

policy was analyzed for the small decrease and large

decrease demand scenarios because this policy represents

current policy under the 1990 farm bill. The dairy

termination program was analyzed for the large decrease

in milk demand and results were compared to those of the

trigger price policy under this demand reduction.

The adoption rates for bST in LIVESIM differ by

region and follow a sigmoid adoption function (see app.

A). It is projected that 43.6 percent of the dairy farms in

the Lake States would adopt bST by 1998. In the

Northeast, 39.9 percent of farms would adopt by 1998; in

the Pacific region, about 63 percent of farms would adopt

bST by 1998; and 36.7 percent of those in the Southeast

would adopt by 1998. Adoption by 1998 in the remaining

regions ranged from 29.7 to 42.9 percent.

For the FLIPSIM analyses, cattle and feed price

projections from LIVESIM were regionalized using

simple regression relationships between National- and

State-level prices. Milk-price projections were region

specific so no adjustment was necessary. The LIVESIM

projected annual changes in the dairy herd that were

region specific; these projections were used to adjust the

number of cows on the representative farms. It was

assumed that each farm’s herd size would change

annually (1990 to 1998) proportional to the annual

percentage change in the respective region’s total number

of dairy cows. Thus, the number of cows milked on the

representative farms fluctuated annually with expected

net returns in the region.

Results

The detailed results of simulating the representative

farms with and without bST are summarized in this

section. Simulation results for various scenarios are

presented in terms of three probabilities and means for the

probability distributions of four key output variables. The

variables used for evaluating the economic impacts of the

alternative scenarios are defined as follows:

● Probability of Survival--chance that the individual

farm will remain solvent through 1998, i.e., maintain

more than 10-percent equity in the farm.

. Probability of Success--chance that the individual

farm will earn a 5-percent or greater after-tax return

on initial equity.

● Probability of Increasing Equity--chance that the

individual farm will increase its net worth in real

1989 dollars over the planning horizon.

● Net Present Value—present value of annual changes

in net worth plus family consumption minus offfarm income.

. Present Value of Ending Net Worth (PVENW)-

ending net worth for 1998 discounted to 1989

dollars, assuming a 5-percent discount rate.

. PVENW as a Percent of Beginning Net Worth—

PVENW divided by initial net worth indicates

whether the farm increased (or decreased) net worth

in real dollars.

. Average Annual Net Cash Farm Income—total cash

farm receipts minus total cash expenses excluding

family living, income taxes, and principle payments.

Economic Payoffs to bST Adoption for

Alternative Farm Policies

Tables C-3 through C-6 summarize the simulation

results for representative dairy farms in the Lake States,

Northeast, Southwest, and Southeast, respectively, assuming bST is introduced in 1991. Results are reported

for the bST adopter and nonadopter. The adopter is

assumed to use bST on all lactating cows beginning in

1991. The nonadopter does not adopt bST over the 1989

to 1998 planning horizon. The economic payoffs for bST

adoption are reported for three different farm policies (see

table C-6).
Appendix C--Detailed Farm Level Impacts of bovine Somatotropin and Other Emerging Technologies ● 105

Table C-3-impacts of bST Adoption on the Economic Viability of Representative Lake State Dairy Farms

Under Alternative Dairy Policies, Assuming No Change in Milk Demand Due to bST, 1989-98

Policy scenario

Trigger price Fixed price support Quota

Non- bST Non- bST Non- bST

adopter adopter adopter adopter adopter adopter

52-COW farm:

Probability of survival (percent).. . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . .

Probability of increasing equity (percent). . . . .

Net present value ($1 ,000) . . . . . . . . . . . . . . . .

Present value of ending net worth

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Present value of ending net worth as a percent

of beginning net worth (percent) . . . . . . . . . .

Average annual net cash farm income

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

125-cow farm:

Probability of survival (percent).. . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . .

Probability of increasing equity (percent). . . . .

Net present value ($1 ,000) . . . . . . . . . . . . . . . .

Present value of ending net worth

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Present value of ending net worth as a percent

of beginning net worth (percent) . . . . . . . . . .

Average annual net cash farm income

($1,000) . -.. .-.. .. ... ------- . . . . . . . . . .

58.0

58.0

0.0

25.2

74.0

74.0

0.0

67.6

73.0

73.0

0.0

65.0

89.0

89.0

1.0

105.6

41.0

41.0

0.0

–15.1

52.0

52.0

0.0

9.8

44.3 81.2 75.9 112.8 7.4 27.8

15.6 28.6 27.1 39.7 2.6 9.8

-2.0 1.9 1.7 5.8 -4.7 –2.3

85.0

67.0

2.0

68.7

92.0

78.0

3.0

127.7

95.0

90.0

8.0

194.8

99.0

95.0

12.0

271.9

99.0

95.0

11.0

265.0

100.0

98.0

18.0

340.1

329.1 396.4 386.9 451.5 211.9 263.7

57.1 68.7 67.1 78.3 36.7 45.7

23.1 33.4 32.1 43.0 11.2 18.2

SOURCE: Office of Technology Assessment, 1991.

Table C-4—impacts of bST Adoption on the Economic Viability of Representative Northeast Dairy Farms

Under Alternative Dairy Policies, Assuming No Change in Milk Demand Due to bST, 1989-98

Policy scenario

Trigger price Fixed price support Quota

Non- bST Non- bST Non- bST

adopter adopter adopter adopter adopter adopter

52-COW farm:

Probability of survival (percent).. . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . .

Probability of increasing equity (percent). . . . .

Net present value ($1 ,000) . . . . . . . . . . . . . . . .

Present value of ending net worth

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Present value of ending net worth as a percent

of beginning net worth (percent) . . . . . . . . . .

Average annual net cash farm income

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

200-cow farm:

Probability of survival (percent) . . . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . .

Probability of increasing equity (percent). . . . .

Net present value ($1,000) . . . . . . . . . . . . . . . .

Present value of ending net worth

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Present value of ending net worth as a percent

of beginning net worth (percent) . . . . . . . . . .

Average annual net cash farm income

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

100.0

100.0

3.0

254.6

99.0

100.0

8.0

277.5

99.0

96.0

0.0

110.8

99.0

97.0

0.0

117.0

100.0

100.0

3.0

232.3

100.0

100.0

3.0

253.9

268.3 286.4 285.6 303.7 169.0 174.7

72.4 77.2 77.0 81.9 45.6 47.1

14.5 17.9 17.8 21.4 -1.9 -0.9

100.0

99.0

43.0

616.7

100.0

100.0

53.0

717.6

100.0

100.0

50.0

705.7

100.0

100.0

66.0

812.3

88.0

64.0

1.0

102.8

91.0

72.0

3.0

166.6

776.8 855.4 842.0 922.0 360.0 415.9

92.3 101.7 100.1 109.6 42.8 49.4

66.2 82.0 79.6 96.2 -1.5 7.3

SOURCE: Office of Technology Assessment, 1991.
106 . U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Table C-5—impacts of bST Adoption on the Economic Viability of Representative Southwest Dairy Farms

Under Alternative Dairy Policies, Assuming No Change in Milk Demand Due to bST, 1989-98

Policy scenario

Trigger price Fixed price support Quota

Non- bST Non- bST Non- bST

adopter adopter adopter adopter adopter adopter

350-cow farm:

Probability of survival (percent).. . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . .

Probability of increasing equity (percent). . . . .

Net present value ($1,000) . . . . . . . . . . . . . . . .

Present value of ending net worth

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Present value of ending net worth as a percent

of beginning net worth (percent) . . . . . . . . . .

Average annual net cash farm income

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,500-cow farm:

Probability of survival (percent).. . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . .

Probability of increasing equity (percent) . . . . .

Net present value ($1 ,000) . . . . . . . . . . . . . . . .

Present value of ending net worth

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Present value of ending net worth as a percent

of beginning net worth (percent) . . . . . . . . . .

Average annual net cash farm income

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

97.0

97.0

56.0

715.4

95.0

95.0

60.0

739.7

97.0

97.0

79.0

885.2

99.0

99.0

81.0

903.5

99.0

99.0

89.0

1,040.0

95.0

95.0

40.0

622.9

701.2 820.7 827.1 939.5 587.1 664.1

109.5 128.1 129.1 146.7 91.7 103.7

109.6 136.1 137.2 163.8 97.1 115.4

100.0

100.0

100.0

4,062.8

100.0

100.0

100.0

4,548.7

100.0

100.0

100.0

4,633.6

100.0

100.0

100.0

5,148.7

100.0

100.0

98.0

3,532.5

100.0

100.0

99.0

3,853.0

4,323.0 4,751.1 4,795.4 5,249.3 3,808.5 4,091.2

194.5 213.7 215.7 236.2 171.3 184.1

713.9 804.4 808.5 900.2 604.8 666.0

SOURCE: Office of Technology Assessment, 1991.

Table C-6—impacts of bST Adoption on the Economic Viability of Representative Southeast Dairy Farms

Under Alternative Dairy Policies, Assuming No Change in Milk Demand Due to bST, 1989-98

Policy scenario

Trigger price Fixed price support Quota

Non- bST Non- bST Non- bST

adopter adopter adopter adopter adopter adopter

200-cow farm:

Probability of survival (percent).. . . . . . . . . . . . 100.0 100.0 100.0 100.0 100.0 100.0

Probability of success (percent) . . . . . . . . . . . . 100.0 100.0 100.0 100.0 93.0 99.0

Probability of increasing equity (percent). . . . . 13.0 24.0 23.0 44.0 5.0 9.0

Net present value ($1,000) . . . . . . . . . . . . . . . . 453.3 601.5 559.9 712.0 333.3 446.7

Present value of ending net worth

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 727.9 854.3 815.3 940.5 615.2 712.8

Present value of ending net worth as a percent

of beginning net worth (percent) . . . . . . . . . . 75.6 88.7 84.7 97.7 63.9 74.0

Average annual net cash farm income

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.3 39.2 32.5 55.3 2.6 19.8

1,500-cow farm:

Probability of survival (percent) . . . . . . . . . . . . . 100.0 100.0 100.0 100.0 100.0 100.0

Probability of success (percent) . . . . . . . . . . . . 100.0 100.0 100.0 100.0 100.0 100.0

Probability of increasing equity (percent) . . . . . 88.0 99.0 97.0 100.0 75.0 91.0

Net present value ($1 ,000) . . . . . . . . . . . . . . . . 4,964.9 6,165.7 5,757.5 7,000.8 4,113.7 5,062.2

Present value of ending net worth

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5,901.3 6,712.4 6,415.4 7,252.3 5,261.1 5,901.2

Present value of ending net worth as a percent

of beginning net worth (percent) . . . . . . . . . . 129.4 147.2 140.7 159.0 115.4 129.4

Average annual net cash farm income

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 609.0 775.4 714.3 880.6 481.9 613.9

SOURCE: Office of Technology Assessment, 1991.
Appendix C-Detailed Farm Level Impacts of bovine Somatotropin and Other Emerging Technologies ● 107

Trigger Price—Under the trigger-price program, the

milk support price is decreased 50 cents per cwt each year

the CCC purchases 5 billion pounds of milk equivalent.

This option is similar to policy from 1985 to 1990 and to

the assessment option in the 1990 farm bill-the assessment will effectively trigger reduction in producer returns

as milk price declines.

The average annual economic payoffs from bST

adoption (change in average annual net cash farm income

due to adoption), given a trigger price dairy policy, ranges

from $3,400 for a 52-cow Northeastern dairy to $166,400

for a 1,500-cow dairy in the Southeast. Average annual

net cash farm income for the 52-cow Northeast dairy

increases from $14,500 to $17,900 due to bST adoption

(see table C-4). The 52-cow Lake States dairy experiences

a slightly greater economic payoff from bST adoption

($3,900) as net cash farm income increases from -$2,ooo

to $1,900 (see table C-3). The greatest economic payoffs

for bST adoption are earned by the 1,500-cow dairy farms

in the Southwest and Southeast. In the Southwest, average

annual net cash farm income increases $90,500 ($713,900

to $804,400) and in the Southeast, the increase is

$166,400 ($609,000 to $775,400) (see tables C-5 and

C-6). Absolute increases in real net worth are also greatest

for these dairies; however, the greatest percentage increases are observed for the dairy farms in the Lake States,

and for the moderate-size dairy in the Southwest.

Increases in average annual net cash farm income due

to adopting bST lead to greater accumulation (or slower

decline) in net worth which, in turn, leads to greater

after-tax net present values for bST adopters. The 52-cow

Lake States dairy producer who adopts bST has a $42,400

greater net present value than the nonadopter, and

$36,900 greater present value of ending net worth (see

table C-3). This pattern of greater net worth and net

present values due to bST adoption is observed for all

eight representative farms.

Increases in average annual net cash farm income due

to bST adoption also leads to improved probabilities of

survival, success, and to increases in real equity. Probability of survival increases from 58 to 74 percent for the

52-cow Lake States dairy as a result of adopting bST (see

table C-3). Adopting bST increases the probability of

increasing real net worth (equity) for five of the eight

representative dairy farms. The three exceptions experienced no change in the probability of increasing real

equity due to adopting bST.

Fixed Price Support--Maintaining the milk price

support at the 1989 value through the 1989-1998 planning

horizon results in higher milk prices and greater average

annual net cash farm incomes than the trigger price policy

(see tables C-3 to C-6). Economic payoffs from bST

adoption are only slightly greater under the fried pricesupport policy than under the trigger price policy for six

of the eight farms. For example, the economic payoff for

the 125-cow Lake States dairy increases only $600 from

$10,300 to $10,9OO due to the policy change (see table

C-3). (The two dairy farms that experience lower economic payoffs (Southwest 350-cow dairy and 1,500-cow

Southeast dairy) experience very small reductions in their

economic payoffs from bST adoption, $700 and $100,

respectively (see tables C-5 and C-6).) These results

suggest that the economic incentive to adopt bST would

not be greatly increased by increasing the price of milk,

i.e., freezing the milk support price at its 1989 level.

Maintaining a fixed support price would result in a greater

probability of survival, success, and increasing real equity

(i.e., increasing a farm’s economic viability) than observed for the trigger price scenario. For a 52-cow Lake

States dairy farm that adopts bST, probability of survival

increases from 74 to 89 percent, and for the nonadopter,

the probability increases from 58 to 73 percent (see table

c-3).

Production Quota—A quota that reduces the number

of dairy cows to maintain milk prices at levels comparable

to the fixed price support policy was analyzed. Results of

the analyses reveal that a quota reduces average annual net

cash farm incomes for adopters and nonadopters, relative

to the other two dairy policies (see tables C-3 to C-6).

Relative to the trigger price, the quota reduces net cash

farm income about $15,000 per year for the 125-cow Lake

States dairy farm that adopts bST, and about $11,900 for

the nonadopter. The large Southeastern dairy that adopts

bST experiences a $161,500 decrease in average annual

net cash farm income under a switch from the trigger price

to the quota policy (see table C-6). Such dramatic

decreases in net cash farm income lead to lower probabilities of increasing real net worth for all eight farms, and

lower the probability of survival for five farms.

The economic payoffs from adopting bST while a

quota policy is in effect are positive for all eight farms (see

tables C3-C6). However, the absolute economic payoffs

are less than under the trigger price policy. The large

Southeastern dairy farm experiences an average annual

economic payoff from bST of $132,000 under the quota,

compared to $166,400 under the trigger price policy (see

table C-6). Similarly, the 52-cow Lake States dairy

experiences a decrease in bST economic payoffs from

$3,900 to $2,400 due to the policy scenario change (see

table C-3).

The primary reason that the farms perform less

favorably under the quota than the other two policies is

that the total milk sold is reduced while fixed costs remain

the same. Fewer cows and pounds of milk are available to

spread out the fixed costs associated with the fixed plant

size. If the dairy farms were able to utilize the resulting

excess capacity for other purposes, the decrease in net

cash farm income, net worth, and probabilities of survival

and success would not be as great. However, the spe-
108 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

cialized facilities associated with modern dairy farming

are not suitable for other enterprises.

Summary--Simulation results for representative dairy

farms indicate that bST adopters enjoy a greater average

annual net cash farm income than nonadopters across

three different types of farm policies. In addition to

increasing net cash farm income, bST adoption leads to

greater real ending net worth, after-tax net present value,

and probabilities of survival and success. Economic

payoffs to bST adopters are greater for larger farms than

for smaller farms. The increased net return for larger

farms may accelerate the growth in average herd size as

producers seek to reduce fixed costs per cow, and take

greater advantage of high-level management practices

associated with bST adoption.

The absolute economic payoff from bST adoption is

about the same under a trigger price dairy policy and a

fixed support price policy (see table C-7). Increasing the

price of milk by maintaining the milk support price at its

1989 level does not greatly increase the economic

incentive to adopt bST. On the other hand, the economic

incentive to adopt bST is significantly lower if a

production quota is in effect. All but one of the eight

representative farms experienced a 20- to 40-percent

decrease in the economic payoff to adopt bST under a

quota. The exception (52-cow Northeast dairy) experienced a 70-percent decrease in the economic payoff

associated with bST adoption. These results suggest that

the rate of bST adoption would be slowed by imposing a

strict production quota rather than a trigger price policy.

Table C-7-Comparison of Average Annual

Economic Payoffs From bST Adoption for

Eight Representative Dairy Farms Under

Three Alternative Dairy Policies,

Assuming No Change in Milk

Demand, 1989-98a (in $1,000)

Policy scenario

Trigger Fixed

Region/size price support Quota

Lake States:

Moderate . . . . . . . . .

Large . . . . . . . . . . . .

Northeast:

Moderate . . . . . . . . .

Large . . . . . . . . . . . .

Southwest:

Moderate . . . . . . . . .

Large . . . . . . . . . . . .

Southeast:

Moderate . . . . . . . . .

Large . . . . . . . . . . . .

3.9

10.3

3.4

15.8

26.5

90.5

21.9

166.4

4.1

10.9

3.6

16.6

26.6

91.7

22.8

166.3

2.4

7.0

1.0

8.8

18.3

61.2

17.2

132.0

aEconomic payoffs from bST are the average annual change in net cash

farm income between a nonadopter and a bST adopter over the 1989-98

planning horizon. The payoff is net of the cost of bST, the added

transportation costs for milk, and the additional feed.

SOURCE: Office of Technology Assessment, 1991.

Economic Payoffs to bST Adoption for

Alternative Milk Demands

The introduction of bST may contribute to a change in

the demand for milk and milk products, depending on the

perception of consumers. To quantify the impacts of milk

demand changes on the economic incentives to adopt

bST, the eight representative dairy farms were simulated

under three alternative milk demand scenarios, with a

trigger price policy. Tables C-8 to C-n summarize the

simulation results for the following changes in milk

demand: no change, small decrease, and large decrease.

For the no-change scenario, milk demand was assumed to

be the same as under the no-bST scenario. A small

decrease in milk demand is defined as a 10-percent

decrease in 1991, a 5-percent decrease in 1992 (i.e.,

demand increases from 1991 to 1992), and a 2.5-percent

decrease from 1993 to 1998. The large milk demand

decrease involves a 10-percent decrease in demand

persisting from 1991 to 1998.

Decreasing the demand for milk reduces the economic

payoffs associated with bST adoption for all eight

representative dairy farms (see tables C-8 to C-12). This

result is observed for both small and large decreases in

milk demand. For example, the economic payoff for bST

adoption is $10,300 for the 125-cow dairy in the Lake

States if there is no decrease in milk demand (see table

C-12). If demand decreases slightly, the economic payoff

falls to $9,200, and if the demand decrease is large, the

economic payoff declines to $6,900 (see table C-12).

Thus, the incentive to adopt and the rate of adoption

would be reduced if milk demand declines due to

consumers’ reaction to bST.

The probabilities of survival and economic success are

reduced as well by decreases in milk demand. These

probabilities decline as lower milk prices lead to lower net

cash farm incomes, net worths, and net present values.

Examining the 350-cow dairy in the Southwest indicates

that for the bST adopter, the probability of survival

declines slightly from 97 to 94 percent if there is a small

decline in milk demand (see table C-10). If the milk

demand decrease is large, this farm’s probability of

survival falls to 69 percent. Because the economic payoff

for bST adoption is positive (see table C-12), those

producers who adopt bST will experience greater probabilities of survival and economic success than nonadopters.

The most significant result for the demand-change

scenarios is the dramatic reduction in the economic

viability of dairy farms (probabilities of survival, success,

and of increasing real net worth) associated with a large

decrease in milk demand (tables C-9 to C-12). AU of the

regions are affected by the lower milk demand, given a

trigger price dairy policy. If a large decrease in milk

demand is experienced, a dairy termination program
Appendix C-Detailed Farm Level Impacts of bovine Somatotropin and Other Emerging Technologies ● 109

Table C-8—Effects of Milk Demand Changes on the Economic Viability of Representative Dairy Farms in the Lake

States Who Adopt and Fail To Adopt bST, Assuming a Trigger Price Dairy Policy, 1989-98

Demand scenario

No change in Small demand Large demand

milk demand reduction reduction

Non- bST Non- bST Non- bST

adopter adopter adopter adopter adopter adopter

52-COW farm:

Probability of survival (percent).. . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . .

Probability of increasing equity (percent). . . . .

Net present value ($1,000) . . . . . . . . . . . . . . . .

Present value of ending net worth ($1 ,000) . . .

Present value of ending net worth as a percent

of beginning net worth (percent) . . . . . . . . . .

Average annual net cash farm income

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

125-cow farm:

Probability of survival (percent).. . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . .

Probability of increasing equity (percent). . . . .

Net present value ($1,000) . . . . . . . . . . . . . . . .

Present value of ending net worth ($1 ,000) . . .

Present value of ending net worth as a percent

of beginning net worth (percent) . . . . . . . . . .

Average annual net cash farm income

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

58.0

58.0

0.0

25.2

44.3

74.0

74.0

0.0

67.6

81.2

40.0

40.0

0.0

–21 .8

7.5

48.0

48.0

0.0

4.7

27.6

13.0

13.0

0.0

-85.5

-47.9

24.0

24.0

0.0

-63.4

-32.2

15.6 28.6 2.6 9.7 -16.9 -11.3

-2.0 1.9 -6.8 -3.8 -12.1 -10.2

95.0

90.0

8.0

194.8

329.1

99.0

95.0

12.0

271.9

396.4

85.0

68.0

2.0

78.3

227.6

91.0

82.0

7.0

150.6

290.9

46.0

37.0

0,0

-126.8

33.3

61.0

47.0

0.0

-48.6

102.6

57.1 68.7 39.5 50.4 5.8 17.8

23.1 33.4 8.7 17.9 –10.7 -3.8

SOURCE: Office of Technology Assessment, 1991.

Table C-9—Effects of Milk Demand Changes on the Economic Viability of Representative Dairy Farms in the

Northeast Who Adopt and Fail To Adopt bST, Assuming a Trigger Price Dairy Policy, 1989-98

Demand scenario

No change in Small demand Large demand

reduction reduction reduction

Non- bST Non- bST Non- bST

adopter adopter adopter adopter adopter adopter

52-COW farm:

Probability of survival (percent).. . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . .

Probability of increasing equity (percent). . . . .

Net present value ($1 ,000) . . . . . . . . . . . . . . . .

Present value of ending net worth ($1 ,000) . . .

Present value of ending net worth as a percent

of beginning net worth (percent) . . . . . . . . . .

Average annual net cash farm income

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

ZOO-COW farm:

Probability of survival (percent) . . . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . .

Probability of increasing equity (percent). . . . .

Net present value ($1 ,000) . . . . . . . . . . . . . . . .

Present value of ending net worth ($1 ,000) . . .

Present value of ending net worth as a percent

of beginning net worth (percent) . . . . . . . . .

Average annual net cash farm income

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

100.0 100.0

100.0

3.0

232.3

268.3

100.0

100.0

3.0

253.9

286.4

100.0

100.0

1.0

199.1

241.0

100.0

99.0

2.0

218.4

258.3

100.0

99.0

0.0

149.8

194.1

100.0

0.0

167.6

210.0

72.4 77.2 65.0 69.7 52.4 56.7

14.5 17.9 9.7 12.8 2.3 5.0

100.0

99.0

43.0

616.7

776.8

100.0

100.0

53.0

717.6

855.4

100.0

98.0

26.0

542.6

722.8

100.0

99.0

45.0

632.7

799.4

98.0

91.0

9.0

352.2

542.9

99.0

94.0

17.0

438.8

618.4

92.3 101.7 85.9 95.0 64.5 73.5

66.2 82.0 56.4 71.1 27.4 40.2

SOURCE: Office of Technology Assessment, 1991.
11O . U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Table C-l O-Effects of Milk Demand Changes on the Economic Viability of Representative Dairy Farms in the

Southwest Who Adopt and Fail To Adopt bST, Assuming a Trigger Price Dairy Policy, 1989-98

Demand scenario

No change in

milk demand

Small demand

reduction

Large demand

reduction

Non- bST

adopter adopter

Non- bST

adopter adopter

Non- bST

adopter adopter

350-cow farm:

Probability of survival (percent).. . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . .

Probability of increasing equity (percent) . . . . .

Net present value ($1,000) . . . . . . . . . . . . . . . .

Present value of ending net worth ($1 ,000) . . .

Present value of ending net worth as a percent

of beginning net worth (percent) . . . . . . . . . .

Average annual net cash farm income

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,500-cow farm:

Probability of survival (percent) . . . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . .

Probability of increasing equity (percent). . . . .

Net present value ($1 ,000) . . . . . . . . . . . . . . . .

Present value of ending net worth ($1 ,000) . . .

Present value of ending net worth as a percent

of beginning net worth (percent) . . . . . . . . . .

Average annual net cash farm income

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

95.0

95.0

60.0

739.7

701.2

97.0

97.0

79.0

885.2

820.7

88.0 94.0

88.0 94.0

35.0 51.0

506.5 655.9

508.3 630.9

52.0 69.0

52.0 69.0

6.0 11.0

70.2 233.2

98.9 236.5

109.5 128.1 79.4 98.5 15.4 36.9

109.6 136.1 70.5 94.7 17.6 34.7

100.0

100.0

100.0

4,062.8

4,323.0

100.0

100.0

100.0

4,548.7

4,751.1

100.0 100.0

100.0 100.0

96.0 98.0

3,230.6 3,678.3

3,600.8 3,992.2

98.0 100.0

96.0 98.0

53.0 70.0

1,820.4 2,268.0

2,278.4 2,671.1

194.5 213.7 162.0 179.6 102.5 120.2

713.9 804.4 554.5 642.5 282.7 360.2

SOURCE: Office of Technology Assessment, 1991,

Table C-n-Effects of Milk Demand Changes on the Economic Viability of Representative Dairy Farms in the

Southeast Who Adopt and Fail To Adopt bST, Assuming a Trigger Price Dairy Policy, 1989-98

Demand scenario

No change in Small demand Large demand

milk demand reduction reduction

Non- bST Non- bST Non- bST

adopter adopter adopter adopter adopter adopter

200-cow farm:

Probability of survival (percent).. . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . .

Probability of increasing equity (percent). . . . .

Net present value ($1,000) . . . . . . . . . . . . . . . .

Present value of ending net worth ($1 ,000) . . .

Present value of ending net worth as a percent

of beginning net worth (percent) . . . . . . . . . .

Average annual net cash farm income

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

100.0

99.0

13.0

453.3

727.9

100.0

100.0

24.0

601.5

854.3

99.0

89.0

4.0

259.9

562.1

100.0

94.0

9.0

400.4

685.6

88.0

51.0

0.0

8.0

321.5

94.0

80.0

1.0

147.2

444.2

75.6 88.7 58.4 71.2 33.4 46.1

17.3 39.2 –9.7 10.7 -42.7 -25.1

1,500-cow farm:

Probability of survival (percent) . . . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . .

Probability of increasing equity (percent) . . . . .

Net present value ($1 ,000) . . . . . . . . . . . . . . . .

Present value of ending net worth ($1 ,000) . . .

Present value of ending net worth as a percent

of beginning net worth (percent) . . . . . . . . . .

Average annual net cash farm income

($1,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

SOURCE: Office of Technology Assessment, 1991.

100.0

100.0

88.0

4,964.9

5,901.3

100.0

100.0

99.0

6,165.7

6,712.4

100.0

100.0

65.0

3,139.9

5,001.4

100.0

100.0

86.0

4,032.3

5,772.3

100.0

89.0

19.0

1,689.1

3,633.2

100.0

99.0

50.0

2,562.2

4,390.7

129.4 147.2 109.7 126.6 79.7 96.3

609.0 775.4 453.8 615.2 200.2 343,8
Appendix C-Detailed Farm Level Impacts of bovine Somatotropin and Other Emerging Technologies . 111

Table C-12—Comparison of Average Annual

Economic Payoffs From bST Adoption for Eight

Representative Dairy Farms Under Alternative

Milk Demand Scenarios, Assuming a Trigger

Price Dairy Policy, 1989-98a (in $1,000)

Table C-13-Comparison of Average Annual

Economic Payoffs From bST Adoption for Eight

Representative Dairy Farms, Given a Large

Reduction in Milk Demand, Assuming a Trigger

Price and Dairy Termination Program, 1989-98a

(In $1,000)

Demand reduction

Region/size No change small Large

Lake States:

Moderate . . . . . .

Large . . . . . . . . .

Northeast:

Moderate . . . . . .

Large . . . . . . . . .

Southwest:

Moderate . . . . . .

Large . . . . . . . . .

Southeast:

Moderate . . . . . .

Large . . . . . . . . .

3.9

10.3

3.4

15.8

26.5

90.5

21.9

166.4

3.0

9.2

3.1

14.7

24.2

88.0

20.4

161.4

1.9

6.9

2.7

12.8

17.1

77.5

17.6

143.6

aEconomic payoffs from bST are the average annual change in net cash

farm income between a nonadopter and a bST adopter over the 1989-98

planning horizon. The payoff is net of the cost of bST, the added

transportation costs for milk, and the additional feed.

SOURCE: Office of Technology Assessment, 1991.

could be implemented (similar to the program in 1986) to

bring production back into line with milk demand.

The LIVESIM model (app. B) analyzed a dairy

termination program, given a large reduction in milk

demand. The result was higher milk prices than under the

trigger price policy, given the same demand scenario. If

the dairy termination program is implemented in 1991

higher milk prices result from 1992 to 1998. Differences

in milk prices between the dairy termination program and

the trigger price policy declined from 50 cents per cwt in

1992 to less than 10 cents per cwt in 1998 as milk supply

increased relative to milk demand.

The farm-level impacts of the dairy termination program are summarized in tables C-13 to C-17. The trigger

price policy results assume the same milk demand (large

demand reduction) and are used as a reference policy. The

dairy termination program leads to higher probabilities of

survival, success, and increasing equity than the trigger

price policy for all eight representative dairy farms. The

moderate-size farms had greater increases in probability

of survival than the large farms from the dairy termination

program.

As observed for the other policy and demand scenarios,

bST adopters were more profitable than nonadopters. This

result is summarized, in terms of the average annual

economic payoffs for bST adoption, in table C-13. The

economic payoffs for bST adoption are positive for the

dairy termination program and they are greater for the

dairy termination program than for the trigger price

Trigger Dairy termination

Region/size price policy program

Lake States:

Moderate . . . . . . . . . . . . . . 1.9 4.1

Large . . . . . . . . . . . . . . . . . 6.9 10.3

Northeast:

Moderate . . . . . . . . . . . . . . 2.7 3.2

Large . . . . . . . . . . . . . . . . . 12.8 15.3

Southwest:

Moderate . . . . . . . . . . . . . . 17.1 25.4

Large . . . . . . . . . . . . . . . . . 77.5 85.3

Southeast:

Moderate . . . . . . . . . . . . . . 17.6 22.3

Large . . . . . . . . . . . . . . . . . 143.6 172.7

aEconomic payoffs from bST are the average annual change in net cash

farm income between a nonadopter and a bST adopter over the 1989-98

planning horizon. The payoff is net of the cost of bST, the added

transportation costs for milk, and the additional feed.

SOURCE: Office of Technology Assessment, 1991.

policy. For example, the economic payoffs for a moderatesize Lake States dairy that adopts bST are $1,900 for the

trigger price policy and $4,100 for the dairy termination

program. A large Lakes States dairy farm had an

economic payoff of $6,900 for the trigger price and

$10,3OO for the dairy termination program (see table

C-13). In the remaining three regions, the large farms

gained more from bST adoption than the moderate-size

farms; this differential was greater under the dairy

termination program than under the trigger price policy

(see table C-13). This reflects the higher milkprices under

the dairy termination program. It also suggests that bST

adoption would be accelerated even in the face of

declining milk demand if a dairy termination program was

introduced.

1.

2.

3.

4.

Appendix C References

Chalupa, W. and Galligan, D.T., ‘Nutritional Implications of

Somatotropin for Lactating Cows,” J. Dairy Sci. 72(1989):

2510-2524.

Peel, D., ‘National and Regional Impacts of bovine Somatotropin Adoption Under Alternative Daixy Policies, ” OTA

commissioned background paper, Washington, DC, 1990.

Penson, J.B., Jr. and Chen, D.T., ‘‘Design and Application of

COMGEM for Farm Policy Analysis,’ Large Scale Modeling of Agriculture Sector, Iowa State University Press, 1990,

ch. 8.

Richardson, J.W. and Nixon, C.J., Description of FLIPSIM.

V: A General Firm Level Policy Simulation Model, Texas

Agricultural Experiment Station, bulletin B-1528, 1986.
112 . U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Table C-14-Effects of a Large Reduction in Milk Demand on Representative Lake States Dairy Farms Who Adopt

and Fail To Adopt bST, Given a Trigger Price and a Dairy Termination Program, 1989-98

Policy scenario

Trigger price policy Dairy termination program

Non- bST Non- bST

adopter adopter adopter adopter

52-COW farm:

Probability of survival (percent) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Probability of increasing equity (percent). . . . . . . . . . . . . . . . . . .

Net present value ($1 ,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Present value of ending net worth ($1,000) . . . . . . . . . . . . . . . . .

Present value of ending net worth as a percent of

beginning net worth (percent). . . . . . . . . . . . . . . . . . . . . . . . . .

Average annual net cash farm income ($1 ,000) . . . . . . . . . . . . .

125-cow farm:

Probability of survival (percent) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Probability of increasing equity (percent). . . . . . . . . . . . . . . . . . .

Net present value ($1 ,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Present value of ending net worth ($1,000) . . . . . . . . . . . . . . . . .

Present value of ending net worth as a percent of

beginning net worth (percent) . . . . . . . . . . . . . . . . . . . . . . . . . .

Average annual net cash farm income ($1 ,000) . . . . . . . . . . . . . ,

SOURCE: : Office of Technology Assessment, 1991.

13.0

13.0

0.0

-85.5

-47.9

-16.9

-12.1

46.0

37.0

0.0

-126.8

33.3

5.8

-10.7

24.0

24.0

0.0

-63.4

-32.2

–11 .3

-10.2

61.0

47.0

0.0

–48.6

102.6

17.8

–3.8

90.0

90.0

1.0

111.9

117.2

41.3

3.3

99.0

97.0

20.0

326.1

438.0

76.0

35.9

96.0

96.0

4.0

146.9

147.5

51.9

7.4

100.0

99.0

31.0

395.6

498.6

86.5

46.2

Table C-15--Effects of a Large Reduction in Milk Demand on Representative Northeast Dairy Farms Who Adopt and

Fail To Adopt bST, Given a Trigger Price and a Dairy Termination Program, 1989-98

Policy scenario

Trigger price policy Dairy termination program

Non- bST Non- bST

adopter adopter adopter adopter

52-COW farm:

Probability of survival (percent) . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 100.0 100.0 100.0

Probability of success (percent). . . . . . . . . . . . . . . . . . . . . . . . . . . 99.0 100.0 100.0 100.0

Probability of increasing equity (percent). . . . . . . . . . . . . . . . . . . 0.0 0.0 3.0 7.0

Net present value ($1 ,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149.8 167.6 245.5 265.1

Present value of ending net worth ($1,000) . . . . . . . . . . . . . . . . . 194.1 210.0 277.6 294.4

Present value of ending net worth as a percent of

beginning net worth (percent) . . . . . . . . . . . . . . . . . . . . . . . . . . 52.4 56.7 74.9 79.4

Average annual net cash farm income ($1 ,000) . . . . . . . . . . . . . 2.3 5.0 15.4 18.6

200-cow farm:

Probability of survival (percent) . . . . . . . . . . . . . . . . . . . . . . . . . . . 98.0 99.0 100.0 100.0

Probability of success (percent) . . . . . . . . . . . . . . . . . . . . . . . . . . . 91.0 94.0 100.0 100.0

Probability of increasing equity (percent). . . . . . . . . . . . . . . . . . . 9.0 17.0 55.0 68.0

Net present value ($1 ,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352.2 438.8 733.8 819.5

Present value of ending net worth ($1 ,000) . . . . . . . . . . . . . . . . . 542.9 618.4 871.6 944.5

Present value of ending net worth as a percent of

beginning net worth (percent) . . . . . . . . . . . . . . . . . . . . . . . . . . 64.5 73.5 103.6 112.3

Average annual net cash farm income ($1 ,000) . . . . . . . . . . . . . 27.4 40.2 82.5 97.8

SOURCE: Office of Technology Assessment, 1991.
Appendix C--Detailed Farm Level Impacts of bovine Somatotropin and Other Emerging Technologies ● 113

Table C-16--Effects of a Large Reduction in Milk Demand on Representative Southwest Dairy Farms Who

Adopt and Fail To Adopt bST, Given a Trigger Price and a Dairy Termination Program, 1989-98

Policy scenario

Trigger price policy Dairy termination program

Non- bST Non- bST

adopter adopter adopter adopter

350-cow farm:

Probability of survival (percent) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Probability of increasing equity (percent). . . . . . . . . . . . . . . . . . .

Net present value ($1 ,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Present value of ending net worth ($1 ,000) . . . . . . . . . . . . . . . . .

Present value of ending net worth as a percent of

beginning net worth (percent) . . . . . . . . . . . . . . . . . . . . . . . . . .

Average annual net cash farm income ($1 ,000) . . . . . . . . . . . . .

1,500 -cow farm:

Probability of survival (percent) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Probability of increasing equity (percent). . . . . . . . . . . . . . . . . . .

Net present value ($1 ,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Present value of ending net worth ($1 ,000) . . . . . . . . . . . . . . . . .

Present value of ending net worth as a percent of

beginning net worth (percent) . . . . . . . . . . . . . . . . . . . . . . . . . .

Average annual net cash farm income ($1 ,000) . . . . . . . . . . . . .

52.0

52.0

6.0

70.2

98.9

69.0

69.0

11.0

233.2

236.5

100.0

100.0

91.0

1,104.0

984.3

100.0

100.0

95.0

1,094.9

1,094.9

15.4

17.6

36.9

34.7

153.7

158.8

170.9

184.2

98.0

96.0

53.0

1,820.4

2,278.4

100.0

98.0

70.0

2,268.0

2,671.1

100.0

100.0

100.0

5,241.5

5,263.1

100.0

100.0

100.0

5,735.8

5,693.9

102.5

282.7

120.2

360.2

236.8

882.1

256.2

967.4

SOURCE: Office of Technology Assessment, 1991.

Table C-17—Effects of a Large Reduction in Milk Demand on Representative Southeast Dairy Farms Who

Adopt and Fail To Adopt bST, Given a Trigger Price and a Dairy Termination Program, 1989-98

Policy scenario

Trigger price policy Dairy termination program

Non- bST Non- bST

adopter adopter adopter adopter

200-cow farm:

Probability of survival (percent) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Probability of increasing equity (percent). . . . . . . . . . . . . . . . . . .

Net present value ($1 ,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Present value of ending net worth ($1,000) . . . . . . . . . . . . . . . . .

Present value of ending net worth as a percent of

beginning net worth (percent) . . . . . . . . . . . . . . . . . . . . . . . . . .

Average annual net cash farm income ($1,000) . . . . . . . . . . . . .

1,500-cow farm:

Probability of survival (percent) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Probability of success (percent) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Probability of increasing equity (percent). . . . . . . . . . . . . . . . . . .

Net present value ($1 ,000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Present value of ending net worth ($1,000) . . . . . . . . . . . . . . . . .

Present value of ending net worth as a percent of

beginning net worth (percent). . . . . . . . . . . . . . . . . . . . . . . . . .

Average annual net cash farm income ($1 ,000) . . . . . . . . . . . . .

88.0

51.0

0.0

8.0

321.5

94.0

80.0

1.0

147.2

444.2

100.0

100.0

45.0

703.1

938.7

100.0

100.0

68.0

837.4

1,054.1

33.4

-42.7

46.1

–25.1

97.5

50.8

109.5

73.1

100.0

89.0

19.0

1,689.1

3,633.2

100.0

99.0

50.0

2,562.2

4,390.7

100.0

100.0

99.0

5,470.5

6,946.5

100.0

100.0

100.0

6,459.4

7,798.4

79.7

200.2

96.3

343.8

152.3

867.7

171.0

1,040.4

SOURCE: Office of Technology Assessment, 1991.
Appendix D

Workshop Participants and Reviewers

Agricultural Research and Technology Transfer Policy for the 1990s Workshop

Norman Berg Paul Genho

Severna Park, MD National Cattlemen’s Association

Deseret Ranches of Florida

Donald Bills

Research Leader Robert Heil

Agriculture Research Service Director

U.S. Department of Agriculture Agricultural Experiment Station

Beltsville, MD Colorado State University

Patrick Borich Jim Hildreth

Director Managing Director

Cooperative Extension Service Farm Foundation

University of Minnesota Verner Hurt

Lucas Calpouzos Director

Professor Agricultural and Forestry Experiment Station

California State University Mississippi State University

Mary Carter

Associate Administrator

Agricultural Research Service

U.S. Department of Agriculture

Neville Clark

Texas Agricultural Experiment Station

Texas A&M University

Arnold Denton

Senior Vice-President

Campbell Soup Co.

Camden, NJ

Chester T. Dickerson

Director, Agricultural Affairs

Monsanto Co.

Catherine Donnelly

Associate Director

Agriculture Experiment Station

University of Vermont

Jeanne Edwards

Weston, MA

W.P. Flatt

Dean

College of Agriculture

University of Georgia

Ray Frisbe

IPM Coordinator

Department of Entomology

Texas A&M University

Terry Kinney

York SC

Ronald Knutson

Professor

Department of Agricultural Economics

Texas A&M University

William Marshall

President

Microbial Genetics Division

Pioneer Hi-Bred International, Inc.

Roger Mitchell

Director

Agricultural Experiment Station

University of Missouri

Lucinda Noble

Director

Cooperative Extension

Cornell University

Ithaca, NY

Susan Offutt

Office of Management and Budget

Washington, DC

Dave Phillips

President

National Association of County Agents

Lewistown, MT

–114--
Appendix D--Workshop Participants and Reviewers ● 115

Jack Pincus

Director of Marketing

Michigan Biotechnology Institute

Dan Ragsdale

Research Director

National Corn Growers Association

Roy Rauschkolb

Resident Director

Maricopa Agricultural Center

Maricopa, AZ

Alden Reine

Dean

Cooperative Agricultural Research Center

Praire View A&M University

Grace Ellen Rice

Legislative Affairs

American Farm Bureau Federation

Robert Robinson

Associate Administrator

Economic Research Service

U.S. Department of Agriculture

Jerome Seibert

Economist

Department of Agricultural Economics

University of California

Keith Smith

Director of Research

American Soybean Association

William Stiles

Subcommittee Consultant

Subcommittee on Department Operations,

Research, and Foreign Agriculture

Committee on Agriculture

U.S. House of Representatives

William Tallent

Assistant Administrator

Agricultural Research Service

U.S. Department of Agriculture

Jim Tavares

Associate Executive Director

Board on Agriculture

National Research Council

Luther Tweeten

Anderson Chair for Agricultural Trade

Department of Agricultural

Economics and Rural Sociology

Ohio State University

Walter Walla

Director

Extension Service

University of Kentucky

Tim Wallace

Extension Economist

Department of Agricultural Economics

University of California-Berkeley

Mike Wehler

Vice President

National Pork Producers Council

Plain, WI

John Woeste

Director

Cooperative Extension Service

University of Florida

Fred Woods

Agricultural Programs

Extension Service

U.S. Department of Agriculture
116 . U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Animal Technology Workshop

Dale Bauman

Professor

Department of Animal Science

Cornell University

David Berkowitz .

Director

Technology Transfer and Coordination Staff

Food Safety Inspection Service

U.S. Department of Agriculture

Roger Blobaum

Director of Americans for Safe Food

Center for Science in the Public Interest

Thomas T. Chen

Associate Director

Center of Marine Biotechnology

University of Maryland

Gary Cromwell

Professor

Department of Animal Science

University of Kentucky

Stanley Curtis

Professor

Department of Animal Science

University of Illinois-Urbana

Dennis Dykstra

Vice-President of Quality Assurance

Jack Frost Golden Plump Poultry

St. Cloud. MN

Terry Etherton

Professor

Department of Dairy and Animal Science

Pennsylvania State University

Don Gill

Regents Prof. and Extension Animal Nutritionist

Oklahoma State University

William Hansel

Distinguished Professor

Department of Veterinary Science

Louisiana State University

Michael Hansen

Research Associate

Consumer Policy Institute

Consumers Union

Norman Harvey

Farmer

Florence, VT

Burke Healey

Farmer

Southern Cross Ranch

Davis, OK

Walter Hobgood

Director of Animal Nutrition and Health

Monsanto Agricultural Co.

Maynard Hogberg

Head

Department of Animal Science

Michigan State University

Gerald Isaacs

Chairman

Department of Agricultural Engineering

University of Florida

Daniel D. Jones

Deputy Director

Office of Agricultural Biotechnology

U.S. Department of Agriculture

Lawrence D. Jones

Assistant Professor

Department of Animal Science

Cornell University

James Kleibenstein

Professor

Department of Economics

Iowa State University

John Kopchick

Professor

Edison Animal Biotechnology Center

Ohio University

Edward Korwek

Partner

Hogan and Hartson

Washington, DC

Darold McCalla

President

Granada Biosciences, Inc.

Houston. TX
Appendix D--Workshop Participants and Reviewers ● 117

Tom McGuckin

Associate Professor

Department of Economics

New Mexico State University

Dave Meisinger

Product Manager

New Products

Pitmann-Moore, Inc.

Jan E. Novakofski

Associate Professor

Department of Animal Science

University of Illinois

B.I. Osburn

Associate Dean for Research

School of Veterinary Medicine

University of California-Davis

Dennis Powers

Director

Hopkins Marine Station

Stanford University

Rodney Preston

Professor

Department of Animal Science

Texas Tech University

Vernon Pursel

Research Leader

Agricultural Research Service

U.S. Department of Agriculture

Allan Rahn

Professor

Department of Animal Science

Michigan State University

Caird Rexroad

Research Leader

Agricultural Research Service

U.S. Department of Agriculture

Tim Rose

Farmer

Lyons, KS

Andrew Rowan

Assistant Dean

School of Veterinary Medicine

Tufts University

Colin Scanes

Professor and Chairman

Department of Animal Science

Cook College, Rutgers University

Tom Sporleder

Professor

Department of Agricultural Economics

and Rural Sociology

Ohio State University

Charles Strong

Extension Biotechnology Coordinator

University of Georgia

Michael Tomaszewski

Professor/Extension Dairy Specialist

Department of Animal Science

Texas A&M University

Edward Veenhuizen

Manager

Animal Science Projects

Lilly Research Laboratories

Eli Lilly and Co.

NOTE: OTA appreciates and is grateful for the valuable assistance and thoughtful critiques provided by the workshop participants. me workshop

participants do not, however, necessarily approve, disapprove, or endorse this report. OTA assumes full responsibility for the report and the

accuracy of its contents.
118 ● U.S. Dairy Industry at a Crossroad: Biotechnology and Policy Choices

Reviewers

L.G. Adams

Professor

Department of Pathology

Texas A&M University

David Barbano

Professor

Food Science Department

Cornell University

Kenneth Bondioli

Research Scientist

Granada Biosciences, Inc.

William Chalupa

Professor

Department of Animal Science

University of Pennsylvania

Richard Fallert

Economist

Economic Research Service

U.S. Department of Agriculture

Ned First

Professor

Department of Meat and Animal Science

University of Wisconsin

Harold Hafs

Vice President-Research

Animal Science Research

Merck, Sharp, Deane Research Laboratories

N.A. Jorgensen

Professor

University of Wisconsin

Robert Kalter

Professor

Department of Agricultural Economics

Cornell University

Ronald D. Knutson

Professor

Department of Agricultural Economics

Texas A&M University

James Lauderdale

Director of Research

The Upjohn Co.

Bernard J. Liska

Professor

Department of Food Science

Purdue University

Kenneth McGuffey

Research Scientist

Lilly Research Laboratories

Eli Lilly and Co.

J. Thomas McGuckin

Professor

Department of Economics

New Mexico State University

Travis McGuire

Professor

Department of Pathology

Washington State University

J.D. Murray

Professor

Department of Animal Science

University of California-Davis

Nanette Newell

Research Scientist

The Synertech Group, Inc.

C.J. Peel

Animal Scientist

Monsanto Co.

Derrell S. Peel

Assistant Professor

Department of Agricultural Economics

Oklahoma State University

James W. Richardson

Professor

Department of Agricultural Economics

Texas A&M University

William Thatcher

Professor

Department of Dairy Science

University of Florida

H. Allen Tucker

Professor

Department of Animal Science

Michigan State University

Henry Tyrrell

Research Scientist

Agricultural Research Service

U.S. Department of Agriculture

J. Gregory Zeikus

President

Michigan Biotechnology Institute

NOTE: OTA appreciates and is grateful for the valuable assistance and thoughtful critiques provided by the reviewers. The reviewers do no4 however,

necessarily approve, disapprove, or endorse this report. OTA assumes full responsibility for the report and the accuracy of its contents.