Title: Beef cattle management systems for the southeast
Full Citation
Permanent Link: http://ufdc.ufl.edu/UF00098110/00001
 Material Information
Title: Beef cattle management systems for the southeast an application of computer modeling
Physical Description: xi, 141 leaves : ill. ; 28 cm.
Language: English
Creator: Boyd, Hines Finlayson, 1943-
Publication Date: 1976
Copyright Date: 1976
Subject: Beef cattle -- Economic aspects -- Mathematical models   ( lcsh )
Animal Science thesis Ph. D
Dissertations, Academic -- Animal Science -- UF
Genre: bibliography   ( marcgt )
non-fiction   ( marcgt )
Thesis: Thesis--University of Florida.
Bibliography: Bibliography: leaves 134-140.
General Note: Typescript.
General Note: Vita.
Statement of Responsibility: by Hines Finlayson Boyd.
 Record Information
Bibliographic ID: UF00098110
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: alephbibnum - 000355728
oclc - 02686961
notis - ABZ3981


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The author is grateful to Dr. Marvin Koger for his guidance and

enthusiastic support through this research. Without his vast experience

as an animal husbandman and the many hours spent in conference with

the author, this study could not have been a success. The author

is also grateful to his committee members and to the numerous other

faculty members at the University of Florida who have made many help-

ful suggestions during the course of this work.

Miss Cindy Sterling has provided invaluable assistance in com-

pleting the computer runs, assembling and organizing results, and

typing the manuscript. Her many hours of dedicated help are greatly


The author is grateful to his wife, parents, and family for

their patience and support. Their encouragement was a vital stimulus

to completing this study while working away from the University of

Florida. He also expresses his gratitude to those others who made it

possible for him to complete the study while being absent from the




ACKNOWLEDGEMENTS........................................ ii

LIST OF TABLES .......................................... v

LIST OF FIGURES...................................... ..viii

Chapter ABSTRACT......... ...................................... ix

I INTRODUCTION............................................ 1

II REVIEW OF LITERATURE................ .... ............... 5

Beef Production: The Cow............................
Cow size............................ 5
Milk yield................ ........... 6
Fertility........................... 6
Beef Production: The Calf ......................... 7
Birth weight......................... 7
Weaning weight ...................... 8
Post-weaning growth ................ 9
Compensatory growth................ 11
Forage and Feeding Systems ....................... 12
Beef Production Efficiency....................... 14
Breeding Systems.................................. 17
Livestock Production Models....................... 18

III EXPERIMENTAL PROCEDURES ............................... 20

Design of the Study............................... 20
Description of the Model........................ 20
Selection of a modeling technique.. 20
Model I: Cow efficiency estimator.. 23
Model II: Herd efficiency estimator 36
Sources of Information............................ 39
Cost and Price Assumptions........................ 39

BREED GROUPS ........................................... 44

Beef Research Unit Data and Assunptions........... 44
Results of Beef Research Unit Analysis............ 49
Biological components.............. 49
Economic components................ 49

COASTAL PLAINS ......................................... 53


Chapter Page

Coastal Plains Data and Assumptions................. 53
Forage and feeding systems............ 53
Animal production characteristics.... 57
Market characteristics............... 61
General assumptions.................. 62
Results of Coastal Plains Analysis.................. 65
Biological components................ 65
Cost components .................. ... 70
Profit components.................... 74
Fertility, culling policy, and
other factors........................ 81
Factors Affecting Biological Efficiency............. 85
Cow size....... ..................... 85
Milk yield........................... 85
Fertility............................ 86
Forage and feeding systems........... 86
Factors Affecting Profitability ..................... 86
Cow size............................. 86
Milk yield........................... 87
Fertility............................ 87
Culling and management practices..... 89
Forage and feeding systems........... 89


Recommendations for Additional Research ............. 91
Applications of Results............................. 92

VII SUMMARY AND CONCLUSIONS................................. 95

APPENDIX A............................................. 100

APPENDIX B........................... ................... 123

BIBLIOGRAPHY........................................... 134

BIOGRAPHICAL SKETCH.............; ....................... 141


Table Page

1 MILK YIELD FACTOR......... .............................. 27

RATION QUALITY. ........................................ 33


4 NON-FEED VARIABLE COSTS. (S/YEAR)....................... 41



COMPONENTS, BEEF RESEARCH UNIT DATA ..................... 50


COASTAL PLAINS DATA ..................................... 58





COMPONENTS.......... ................................... 100

15 PASTURE BUDGET: CLOVER-GRASS.......................... 100



18 PASTURE BUDGET: MILLET.................. ............. 101


Table Page

19 RATION COMPOSITION AND COSTS........................... 102

20 BREEDING COSTS......................................... 102

SYSTEMS ................................................ 103

22 ACREAGE REQUIREMENTS, 1000 BROOD COW HERD.............. 104

WEANING RATE .......................................... 105

24 POUNDS BEEF SOLD PER ACRE.............................. 106


26 POUNDS TDN PER POUND BEEF SOLD......................... 108

27 INDEXED COST PER POUND TDN CONSUMED.................. 109

28 INDEXED COST PER POUND BEEF SOLD...................... 110

RATE.............. ..................................... ll

HIGH PRICE STRUCTURE................................... 112

HIGH PRICE STRUCTURE.. ....................... ..... .. 113

LOW PRICE STRUCTURE.......... .......................... 114

PRICE STRUCTURE......................................... 115

PRICE STRUCTURE........................................ 116

PRICE STRUCTURE........................................ 117

STRUCTURE.............................................. 118

HIGH-HIGH PRICE STRUCTURE.............................. 119

STRUCTURE................ ............................. 120


Table Page

STRUCTURE............ ................................ 121

COW OPERATION... ......... ............................ 122


Figure Page

1 Simplified flow diagram, Model I, Cow Efficiency
Estimator.......................... ..................... 24

2 Simplified flow diagram of herd inventory sector, Model
II, Herd Efficiency Estimator.......................... 25

3 Assumed relationships between feed quality and
efficiency of ME conversion to NE....................... 32

4 Design of Coastal Plains beef modeling study ........... 54

5 Hypothetical price-cost curve for three price
structure ............................................... 64

6 Pounds TDN per pound of beef sold for four cow sizes
and two milk levels..................................... 69

7 Indexed cost per pound of beef sold for four cow sizes
and two milk levels..................................... 73

8 Indexed net returns per acre at high-high price structure
for four cow sizes and two milk levels................... 78

9 Indexed net returns per acre at high-high price and
uniform weaning rate for four cow sizes and two milk
levels................................ ..... ............. 79


Abstract of Dissertation Presented to the Graduate Council
of the University of Florida in Partial Fulfillment of the
Requirements for the
Degree of Doctor of Philosophy




December, 1976

Chairman: Marvin Koger
Major Department: Animal Science
Two mathematical models for the evaluation of beef production

systems were developed and computerized .using DYNAMO programming.

The first model, a cow efficiency estimator, computed the TDN

requirements for a cow and her calf using variables such as animal

weight and gains, seasonal changes in cow weight, cow milk production,

physical activity of the animals, and the quality of feed being consumed.

The second model, a herd efficiency estimator, used data from

the first model plus data on cattle prices, fixed costs, pregnancy

and calf survival rate, death losses, heifer replacement and culling

policies, herd size, and TDN produced per acre from each TDN source.

This model calculated biological efficiency factors such as TDN per

unit of beef sold, beef produced per land unit and.economic efficiency

factors including cost and net returns per unit of beef sold and net

returns per land unit.

The models were tested using data collected over a nine year

period at the University of Florida Beef Research Unit. They were


then used to evaluate five feeding and pasture systems suitable to the

southeastern United States. Animal production traits, market struc-

tures, and herd culling procedures were also studied.

Cow size had no effect on measures of biological efficiency.

In general, cow size had little or no effect on profitability except

that large cows were at a disadvantage when a relatively expensive

high-energy corn silage ration was fed to brood cows.

Increasing milk yield improved biological efficiency, decreased

costs, and improved returns at weaning. However, if the calf was

maintained in the herd and finished to slaughter weight, there was

no advantage to high milk yields in the cow herd.

Fertility was the only animal production characteristic examined

in the study which consistently showed a substantial effect on profit-

ability. Increasing fertility always increased profitability.

The pasture and feeding system used had a substantial effect on

biological efficiency and profitability. A confinement system in

which brood cows were fed corn silage in a drylot had the lowest TDN

per unit of beef produced but was uniformly unprofitable. A semi-

confinement system in which brood cows were heavily stocked at 1.67

animal units per acre and supplemented with corn silage rated second in

measures of biological efficiency. With high cattle prices it also

gave the greatest returns per land unit. In the other three systems

examined, cow-calf production occurred on clover-grass pastures.

Calves went directly into the feedlot or were grazed on annual forages

or topseeded perennial pastures before a short feedlot finishing phase.

A system in which calves were grown out on topseeded perennial grass

pastures had the lowest cost per unit of beef produced and the highest

return per unit of beef sold. It also surpassed the semi-confinement

system in net returns per land unit when cattle prices were low.

The method by which non-pregnant cows are removed from the herd

was demonstrated to have a substantial effect on profitability. The

most profitable procedure was to detect and immediately cull non-

pregnant cows as soon as they weaned their last calf. Profits were

substantially reduced by delaying culling until six months after

weaning or by culling a fixed percentage of the cow herd at the end

of the production year regardless of pregnancy status.

The models developed in this study are flexible, easy to use,

and inexpensive to run. When adequate input data for a given area

and time are known,, the models can be useful tools in building recom-

mendations for an optimum beef production system.


The chief concern of most beef producers is to maximize some

economic objective, usually net returns. To accomplish this objective,

the producer must first decide what kind of production system will

yield the greatest profits. The second step is to decide how to man-

age both the animals and their environment to achieve this optimum

production system. Animal scientists can usually supply producers

with extensive information regarding animal selection, the nature of

the selection response, animal nutrition, reproductive physiology, and

meat quality. Up to the present, however, animal scientists have not

been able to give producers much help in choosing production goals.

The inadequacy of research efforts in this regard has been pointed out

by Gregory (1972) and Harris (1970).

To evaluate alternative production goals the producer must eval-

uate entire production systems. If animal scientists are to assist

livestock producers in selecting production goals, they must adopt re-

search techniques for analyzing entire production systems. One of the

major techniques used in many fields but, until very recently not applied

in animal science, is computer modeling.

Scientists in many disciplines conduct experiments with models

rather than performing the experiments under field conditions. Engi-

neers, for example, have used models of structures such as buildings,

bridges, or airplanes for experimental testing before building the


actual structure. If a system can be accurately described and ex-

pressed in explicit quantitative terms, then it is possible to con-

struct a mathematical model of that system and to use a digital com-

puter to perform calculations that represent the behavior of the


Mathematical models of beef systems can be constructed for

several levels of production. These levels are as follows:

I. Region/country/world

II. Herd

III. Individual animal

IV. Sub-systems of individual animals (e.g. digestive system,

reproductive system)

Techniques are available which would allow modeling at all levels.

The limiting factor in modeling beef systems is not modeling technique

but lack of basic input information and data to build and execute

valid models. The most extensive and reliable input information and

data exist at levels II and III. The efforts of this study involved

levels II and III since information about these levels could be most

readily applied by beef producers.

Most beef production models reported thus far at the individual

cow and herd level have used a linear programming (LP) technique. The

study reported here differed in that it employed the DYNAMO computer

language (Pugh, 1970). While LP is a convenient technique commonly

used by agricultural scientists, its usefulness is restricted by a

rigorous set of assumptions outlined by Heady and Candler (1958).

LP assumes "linearity." Thus non-linear relationships, such as nutrient

requirements for maintenance and growth, must be approximated in an

LP model by the use of pre-calculated coefficients or by subdivision

into several activities. This subsdivision process may lead to pro-

blems with the LP assumption of finitenesss." Only a limited number

of activities or equations may be considered. Otherwise, the model

becomes too costly to run and too cumbersome to interpret. This

assumption of finiteness also requires the specification of limits on

the supply of each resource. Other problems may arise with the LP

assumption of "single-value expectations" especially when a value

changes with time as, for example, with cow milk yield as lactation

progresses or pasture TDN values as the season changes.

None of the restrictions mentioned above for LP models are serious

problems when using DYNAMO. Nevertheless, DYNAMO is not an optimizing

technique as is LP. Optimizing can be done with DYNAMO by using a

series of runs, though this reiteration approach may become burdensome

if large numbers of interacting variables are involved. Generally,

however, livestock production models do not require optimization since

animal-environment interactions preclude the existence of a univer-

sally optimum production system. The objective of livestock produc-

tion modeling should be to gain an understanding of the behavior of

different production systems and their associated animal-environment

interactions. A more versatile modeling technique such as DYNAMO

makes this objective easier to achieve.

It was the goal of this study to develop a mathematical model for

analyzing beef production systems and, with the aid of a computer, to

use the model to represent beef systems which are currently in use or

which might be feasible in the future for parts of the southeastern

United States. More specifically, the objectives, of the research were

1) Develop a model which, with minor adaptations, could

be used to evaluate any beef production system where

standard input data are available.

2) Estimate the effects of production variables such

as cow size, fertility, milk yield, and calf gain

on production efficiency and profitability.

3) Estimate the effects of certain environmental

factors such as feeding and pasture systems, herd

management procedures, and markets on production

efficiency and profitability.

4) Examine alternative beef production systems for

the southeastern United States, especially Florida

and the lower Coastal Plains.

5) Evaluate possible interactions between animal

production characteristics and the environment

in which the production occurs.


Building a realistic model of a beef production system entails the

interrelating of many variables and requires data and information from

all stages of the beef production cycle. This information, of course,

must come from many separate sources. Thus, a reservoir of compatible

data and information must be assembled for the successful construction

and execution of a beef system model. This chapter is a review of some

of the literature which influenced the development of the models and

the evolution of the study.

Beef Production: The Cow

Cow Size

In a review of mature cow weights, Warwick (1971) reported

average weights of about 800 to 1300 pounds for British breed cows, with

most weights in the 1000 to 1200 pound range. Cow weight, however, may

not always be a good measure of cow size. O'Mary, Brown, and Ensminger

(1959) used 15 body measurements to reflect cow size. Klosterman,

Sanford, and Parker (1968) found condition and weight-height ratio to be

highly correlated, emphasizing the importance of cow condition in size

determination. The effects of season, lactation status, and pregnancy

status were illustrated in a study by Vaccaro and Dillard (1966). They

found that cows lost weight at parturition and continued to lose weight

for 60 days after calving; then began to gain. Fitzhugh, Cartwright,

and Temple (1967), found that age accounted for a significant portion

of cow weight.

Cow weight seems to be the most obvious and readily available

indicator of cow size. However, if weight is to be used as a measure

of cow size, then factors such as cow condition, pregnancy status,

lactation status, age, and season need to be specified.

Milk Yield

The milk yield of a cow may be influenced by her breed, age, size,

plane of nutrition, and stage of lactation. Joandet and Cartwright

(1969) reported average daily milk yields of 7..4 to 12.0 Ibs/day for

British-Brahman cross cows. Dawson, Cook, and Knapp (1960) reviewed

data and suggested a range of 6 to 13 Ibs/day for Angus and Hereford

cows. Melton, Riggs, Nelson, and Cartwright (1967) observed values of

7 to 10 Ibs/day for the Angus, Hereford, and Charolais cattle used in

their study. These same authors also reported that milk yield increased

with cow age and that cows nursing bull calves gave more milk than cows

nursing heifer calves.

The relationship of milk yield to cow size is well recognized in

dairy cattle (Preston and Willis, 1970). Harville and Henderson (1964),

for example, reported a correlation between body size and milk yield of

approximately 0.4.

The effects of stage of lactation on milk yield has been demon-

strated in several studies. Dickey (1971); Rutledge, Robison,

Ahschwede, and Legates (1971), and Melton, Riggs, Nelson, and Cart-

wright (1967) all reported a decline in milk yield as lactation pro-



The works of Cunha, Warnick, and Koger (1967) and Preston and

Willis (1970) provide excellent reviews of the many factors affecting

fertility in the beef cow. These factors include breed, age, nutri-


tion, environment, herd management, milking level, and lactation status

Of special interest in this study are the effects of milk yield

and cow size on fertility levels. ,Neither of these factors have been

studied thoroughly. Willham (1972) reviewed works suggesting that

reproductive performance is lowered by increased milk production.

Butts (1972) cited evidence that pregnancy rate is correlated

with cow size. Cartwright communicated to him data indicating a neg-

ative correlation (r= -.235) between number of calves weaned per year

and mature size. Sanders in Tennessee also reported to Butts a

negative correlation of -.45 between shape of weight-age curve

of cows and reproduction, although this correlation tended to dis-

appear where adjustments were made for variation in body composition.

These studies suggest that fertility in the modern beef cow may decrease

as cow size increases.

Beef Production: The Calf

Birth Weight
The birth weight of calves is affected by numerous factors,

including sex of calf, age of dam, breed, nutrition of dam and

weight of dam. Work by Lampoand Willen (1966) illustrated the effect

of sex of calf and age of dam. Franke, England, and Henry (1965),

examining six sire breeds and a variety of dams, found breed of dam to

be the most important factor in determining calf birth weight, although

dam breed accounted for only 7.4% of the total variance The influence

of diet and level of nutrition of the dam has been demonstrated in stu-

dies by Clanton, Zimmerman, and Albin (1964) and Smithson, Ewing and

Renbarger (1966).

Probably the most important factor affecting calf birth weight is

the weight of the dam. Lampo and Willen (1965) obtained correlation

coefficients of 0.43 to 0.55 between dam pre-calving weight and calf

birth weight. Vaccaro and Dillard (1966) also noted that the heaviest

cows 90 days before calving had the heaviest calves.

Weaning Weight

In a classic study in 1945, Koger and Knox proposed a method for

estimating weaning weight of calves at a constant age. Weaning weight

is an easy, convenient trait to measure and since that 1945 report

has been studied intensively. Weaning weight can vary with calf age,

sex, breed, birth weight, and by age, size, and milk yield of dam.

Preston and Willis (1970) reviewed studies of the effects of breed,

sex, and dam age on weaning rates. For calves weaned at 200 to 215

days of age, average weaning weights were reported to vary from 282 to

509 pounds. In a recent comprehensive study of beef production traits

for different breeds, researchers at the U. S. Meat Animal Research

Center (1975) found 200-day weaning weights to vary from 395 pounds

for a straightbred Hereford calves to 558 pounds for Angus-Brown Swiss

F1 calves out of Swiss dams. These data were for dams 4 years or older.

Environmental factors also add to the great variability found among

weaning weights in different studies.

Vaccaro and Dillard (1966) studied the relationship between dam

weight and calf weight changes. They found that the heaviest cows 90

days prepartum tended to produce the heaviest calves at weaning.

Older cows also produced heavier calves. They noted that birth weight

of calf was the most valuable predictive measure of gain to weaning at

180 days.

Butts (1972) reviewed the relationship between cow weight and

weaning weight of progeny. He summarized reports which showed increases

in weaning weight of 0 to 15 pounds for each 100 pounds increase in

cow weight. As pointed out by this author, however, cow weight may

be an inadequate measure of cow size. O'Mary, Brown, and Ensminger

(1959) reported a correlation coefficient of 0.51 between cow weight

and calf weaning weight. They also found a multiple correlation

coefficient of 0.91 between three body measurements of a cow and the

weaning weight of her calf. Thus when cow size can be adequately

determined it appears to be highly correlated with calf weaning weight.

The effect of milk yield on weaning weight has also been studied

extensively. Milk yield and weaning weight are highly correlated. In

13 studies reviewed by Preston and Willis (1970) the correlation co-

efficient between milk yield and weaning weight varied from 0.14 to 0.91.

Most reports ranged from 0.4 to 0.6.

Post-Weaning Growth

Preston and Willis (1970) considered six major factors which influ-

enced post-weaning growth. These factors included breed, sex, exogen-

ous hormones, nutrition, environment, and management. In this study,

nutritional programs are the factors of chief concern.

After weaning, most calves will either go directly into a feedlot

where they are fed a high-energy ration or they may graze a high quality

forage. This forage program may include some grain supplementation or

may be concluded with a short feedlot phase to improve carcass quality.

Placing calves directly into a feedlot offers the advantage of

rapid growth. However, the slower gains attained by grazing high quality

forages may be the least expensive gains.

In an extensive comparison of breed differences, the U. S. Meat

Animal Research Center (1975) in Nebraska fed weaned calves for periods

ranging from 220 to 282 days. Gains varied from 2.02 lbs/day for Red

Poll-Angus crossbreeds to 2.66 Ibs/day for Maine Anjou-Hereford crosses.

In Georgia, Chapman, Utley, and McCormick (1971) attained daily gains

of 2.73 to 2.82 Ibs for Hereford and Hereford crossbred weanling steers

fed for 204 days. Similar gains have been reported by Florida researchers.

Baker, Crockett, Carpenter, West, and Palmer (1974) fed crossbred steers

for 178 days on a high moisture corn ration. They obtained daily gains

of 2.84 Ibs. Bertrand, Lutrick, and Dunavin (1974) achieved daily gains

of 2.48 to 2.83 Ibs using a dry corn ration and a feeding period of 128

to 146 days. These investigators also reported significantly lower

gains where grain sorghum was substituted for corn in their rations.

The gains reported for forage systems have been highly variable,

even for different investigations of the same type forage. These

variations are not surprising since environmental factors such as

season and grazing management practices are known to have signifi-

cant influences on the results of grazing trials.

Daily gains on winter grazing in Florida, Georgia, and Alabama,

have varied from 1.58 to 2.3 Ibs (Baker, 1975; Harris, Anthony,

Brown, Boseck, Yates, Webster, and Barrett, 1971; Anthony, Hoveland,

Mayton, and Burgess, 1971; Utley, Marchant, and McCormick, 1976).

For the summer annuals, millet and sorghum-sudan grass, investigators

in the same three states have reported gains of 1.06 to 2.13 Ibs/day

(Baker, 1975; Hoveland, Harris, Boseck, and Webster, 1971).

On perennial sods, Utley, Marchant, and McCormick (1976) obtained

average daily gains of-1.26 Ibs on Pensacola babia, 1.41 Ibs on Coastal

bermuda and 1.58 lbs on Coastcross-1 bermuda. Oliver (1976) grazed steers

on Coastal bermuda from May through September and reported daily gains of

1.16 Ibs for European cross steers and 1.58 Ibs for Brahman cross steers.

Both groups gained about the same in the month of May but the Brahman

cross calves showed a progressive advantage as the season advanced.

The author concluded that the Brahman calves used lower quality forage

more efficiently.

Compensatory Growth

Calves which have been maintained on a low plane of nutrition will

gain faster and more efficiently than calves of similar weight which

have been well fed. This phenomenon is known as compensatory growth

and has been documented by Winchester and his associates (Winchester

and Howe, 1955; Winchester and Ellis, 1956; Winchester, Hiner, and

Scarborough, 1957). These authors studied the effects of both energy

and protein levels in identical twin calves 3 to 12 months old. The

calves were fed rations varying from maintenance to liberal levels,

then all were switched to the liberal ration. There were no sig-

nificant differences in the amounts of energy consumed over the entire

trial period or in carcass quality or dressing percent. Calves

fed the restricted diet required a longer period of time to reach

slaughter weights.

Meyer, Hull, Weitkamp, and Bonilla (1965) assigned calves which

had been on restricted diets to four energy intake levels including

three different grazing intensities. Compensatory growth always occurred

during this second phase of their experiment, even where the second

phase energy intake level was low.

These studies on compensatory growth illustrate the importance of

carefully defining the overall life history of a calf when modeling its

entire life cycle. They also demonstrate the need for caution in

interpreting gain data from experiments where previous history

of the cattle is not indicated.


Forage and Feeding Systems

In the southeastern United States, beef production has traditionally

occurred in three phases. These phases include the cow-calf phase, the

stocker phase, and the feedlot phase.

The cow-calf phase nearly always occurs on perennial grass pasture,

frequently with some supplemental feed such as hay or silage during the

winter. One of the most extensive cow-calf pasture studies was con-

ducted in Florida (Koger, Blue, Killinger, Greene, Myers, Warnick, and

Crockett, 1970). Calves were produced on all-grass and clover-grass

pastures planted on "flatwoods" soil -- a somewhat poorly drained Leon

fine sand. The most productive program yielded 385 Ibs of calf per

acre per year on a clover-grass mixture stocked at 0.7 cows per acre.

This pasture received only 30 lbs of P205 and 60 Ibs of K20 per year.

Additional P205 and K20 did not increase the amount of beef produced

per acre. An all grass program which received 120 Ibs of N, 45 Ibs

of P205 and 90 Ibs of K20 carried 0.71 cows per acre and produced only

332 lbs of calf per acre. These production rates and carrying capa-

cities were for pasture only and did not include the use of an addi-

tional 0.13 acre per cow for growing corn silage used as a winter

supplement. With the silage land included, beef produced per acre

would have been 351 Ibs for the clover-grass pasture and 304 lbs for

the all-grass pastures.

Neville and McCormick (1976) in Georgia used heavily stocked

Coastal bermuda pastures for a cow-calf program. Including hay land,

they stocked cattle at 1.01 and 0.75 cows per acre during a two year

study. The heavily stocked pastures received 288 Ibs of N, 72 lbs of

P205 and 144 Ibs of K20 per acre, while the more lightly stocked

pasture was fertilized at about one-half this rate. These two treat-


ments produced 355 and 292 Ibs of calf per acre, respectively.

One highly productive cow-calf program was a 16-year Louisiana

study reported by Doane (1976). Twenty-four cows were grazed on 16

acres of Coastal bermuda which was topseeded each fall with clover

and ryegrass and fertilized with 293 lbs of N annually. All of the

hay to meet winter feed requirements was also produced on the 16

acres. Each acre produced 641 lbs of beef plus one-half ton of

surplus hay per year.

Franke (1970) surveyed confinement cow-calf systems. Problems

with confinement systems included high calf death loss and high costs

per cow-calf unit. He did not report on the amount of beef produced

per acre though he did quote a producer who claimed a 50% increase

in herd size was made possible by drylotting his cows during the fall

and spring.

After weaning, most cattle in the southeastern,United States enter

a stocker phase during which they are grazed on either annual or

permanent pastures. Annual pastures are the most popular since they

can be grown during both winter and summer and provide higher quality

feed than the warm season perennials.

Clover-rye-ryegrass mixtures have been used successfully for growing

calves during the winter and early spring months. In a 10-year study

at Alabama (Harris, Anthony, Brown, Boseck, Yates, Webster, and

Barrett, 1971) such a mixture produced 186 days of grazing beginning

in early November. The stocking rate was 1.3 calves per acre with an

average daily gain of 1.48 lbs. Beef production per acre was 390 lbs.

Anthony, Hoveland, Mayton, and Burgess (1971) achieved a similar pro-

duction rate of 394 Ibs per acre with an arrowleaf clover-rye-ryegrass

mixture grazed for 193 days. Their steers gained 2.05 lbs/day when

stocked at one animal per acre. Baker (1975) stocked rye-ryegrass

pastures more heavily to attain 420 Ibs of gain per acre during a 163

day grazing season with an average daily gain of 1.58 Ibs.

Utley, Marchant, and McCormick (1976) reported 453 Ibs of gain per

acre and 2.3 Ibs of gain per animal per day from either oats or rye-

grass planted on a prepared seedbed. When these annuals were top-

seeded on permanent pastures, however, they were slower to develop and

provided only 222 Ibs of gain per acre before the summer perennial

grasses dominated the sward. The permanent pastures in this study

produced an additional 441 to 531 lbs of gain during the summer growing

season. The summer annuals in this same study produced 334 to 467 lbs

of gain per acre (about 2 Ibs per animal per day). Other studies have

reported much lower gain rates on summer annuals. Bertrand and Dunavin

(1970) obtains 344 Ibs of weight gain per acre with a gain rate of 1.18

Ibs per animal per day during an 86-day grazing season. Hoveland,

Harris, Boseck, and Webster (1971) produced 210 lbs of gain per acre

during a 77-day grazing season on summer annuals. Their average daily

gain was 1.1 lbs.

Calves may go from the stocker phase directly to slaughter or into

a feedlot phase. They might also bypass the stocker phase and go

directly into the feedlot where they will be fed a high energy grain

ration. Baker, Crockett, Carpenter, West, and Palmer (1974) and

Bertrand, Lutrick and Dunavin (1974) have demonstrated the practicality

of finishing beef calves on predominantly grain rations in the south-

eastern United States.

Beef Production Efficiency

During recent years there has been a dramatic increase of interest


in factors influencing beef production efficiency. The literature

contains numerous theoretical treatments and reviews of this subject.

Klosterman (1972) concluded that, generally, medium size cattle will

be the most efficient but that no one size will be most efficient under

all conditions. Butts (1972) suggested that cow size is related to

production efficiency through its relationship with other factors in

the production cycle, and that these relationships need more study

before it is possible to design production systems of maximum efficiency.

Willham (1972) concluded that, while some breeds need improved maternal

ability, the maximization of milk production as a means of improving

efficiency does not seem to be a realistic goal, especially in view of

the detrimental effect of high milk yields on reproductive performance.

In a discussion of the effects of breeding programs on production

efficiency, Cartwright (1970) predicted that there will be a growing

emphasis on increasing output per unit of input on a herd rather than

on an individual basis. Cartwright also suggested that greater emphasis

will be placed on specialized herds or breeds, and on utilizing hybrid

vigor. Hendrick (1972) reviewed the effects of body type on production

efficiency and concluded that size or form of the animal is not as

important as meat quality and the proportions of lean meat produced.

The undertone of all these reviews was echoed by Harris (1970)

in a theoretical discussion of breeding for economic efficiency in

livestock production. Harris noted that most of the research in animal

breeding to date has been concerned with methods of genetic evaluation

and the nature of the selection response. Efforts to define realistic

selection goals have not been adequate.

Attempts have been made to examine beef production efficiency

experimentally. Kress, Houser, and Chapman (1969) indicated that re-

productive performance was more closely related to efficiency than

any other variable and that large cows were the most profitable.

Joandet and Cartwright (1969) developed a method for determining the

point at which cumulative TDN required to produce a unit of live

weight is minimal. They called this point the optimum slaughter

weight. Melton, Cartwright, and Kruse (1967) reported that small cows

were the most efficient in terms of units of input per pound of calf


Investigators in Texas have studied beef production efficiency

using computer models for beef production and data from Texas experiment

station herds supplemented with parameter estimates from other research.

In an early study Long and Fitzhugh (1969) concluded that small cows

were more profitable than large cows. However, in a subsequent study

(Long, 1972) indicated that large cows were favored in a straightbreeding

system when fed a high energy, least-cost ration. When fed on pasture

and harvested forage, medium size cows were most efficient. In still

another study (Long, Cartwright, and Fitzhugh, 1975) this group re-

ported that large cows were more profitable on a drylot regime and small

cows were more profitable on a pasture regime. These Texas workers,

however, have consistently pointed out the interactions between factors

such as cow size, milk yield, progeny performance, and production

environment and have cautioned against the concept of a universally

optimum animal type.

It is obvious that the study of beef production efficiency is in

its infancy. Production data on all phases of beef production cycle,

the interactions between animal production factors and environmental

factors, techniques for examining beef production efficiency, and

definitions of production efficiency are all factors which will need


improvement as this field of study progresses.

Breeding Systems

A popular approach in studies of beef production efficiency has

been to compare the efficiencies of different breeding systems. In a

theoretical treatment, Moav (1966) proposed specialized sire and dam

lines to improve "profit heterosis."' Cartwright (1970) has been a

proponent of specialized sire and dam lines to improve beef production

efficiency. He and his Texas associates (Long, Cartwright, and Fitzhugh,

1975; Fitzhugh, Long, and Cartwright, 1975; Cartwright, Fitzhugh, and

Long, 1975) published a series of papers in which they assessed the

effects of several breeding systems on net income and return on invest-

ment. They concluded that breeding plans in which large sires were

mated to either F1 or crossbred cows were more favorable than straight-

breds or two breed crosses.

Systems of crossbreeding and crossbreeding experiments have been

reviewed by Koger, Cunha, and Warnick (1973) and by Cundiff (1970).

The review by Cundiff indicated that heterosis was greatest for traits

of low to moderate heritability (e.g., early growth, fertility, and

survival) and least for traits of high heritability (e.g., post weaning

growth and carcass merit). This conclusion implies that crossbreeding

may be used to improve traits such as fertility but will not have a

substantial effect on highly heritable traits like post weaning growth

and carcass merit. Another study by Cundiff, Gregory, and Long (1975)

suggested that breeders have applied much selection pressure for growth

traits but very little selection for carcass traits. These investiga-

tors estimated the correlation between several breeding values of sires

produced within the same herd. The correlation was high (0.51) for

growth traits and low (0.16) for carcass traits. They concluded that

the high breeding value correlation for growth traits indicates sub-

stantial genetic diversity probably, arising from differential selection

pressure and response.

Studies such as those of Cundiff and his associates have impor-

tant implications for designing breeding systems to maximize the

efficiency of beef production. A breeding system is a means to an end.

Once production goals have been selected a breeding system can be chosen

which will enable the most rapid achievement of those goals.

Livestock Production Models

The use of mathematical models,to examine the behavior of systems

has been extensive in engineering and has been formalized in the area

of study known as systems analysis.' Forrester (1961) proposed a

philosophy and a technique for modeling social and economic systems. In

recent years much interest has developed in the modeling of livestock

production systems with special emphasis on the economic aspects of

these systems.

Linear programming (LP) has been a popular tool for modeling live-

stock production systems. Workers in Texas (Long, 1972; Long, Cartwright,

and Fitzhugh, 1975) have pioneered in the development of LP models of

beef production systems. They have used these models to study the

effects of cow size, milk yield, herd management, heterosis, com-

plimentarity, and mating plan on the efficiency of beef production.

Canadian workers (Wilton, Morris, Jenson, Leigh, and Pfeiffer, 1974;

Morris and Wilson,'1975) have also used an LP model to assess beef pro-

duction efficiency. Miller, Brinks and Sutherland (1976) reported the

use of an LP model to maximize net returns on a southern Colorado hay


and steer grazing operation. Brodnax (1973) employed an LP'model to

study the effects of various tenure and tax management strategies on

large central Florida beef cattle ranches.

Boyd and Koger (1974a, 1974b, 1975) have addressed the problem

of beef production efficiency at both the cow and herd levels using a

model written in the DYNAMO programming language. Meadows (1970) at

MIT, using this same language, developed a model for the United States

swinepopulation and also proposed -a similar model for the United States

beef cattle population. Halter and Dean (1965) used a DYNAMO model.

to evaluate the management policies of a California range-feedlot

operation under conditionsof weather and price uncertainty.

Other models examining certain aspects of livestock production

systems have appeared in the literature. Rogers (1971) and Smith (1971)

have developed decision models to determine the optimum time for re-

placing a breeding animal in the cow herd. Dinkel and Dearborn

(1972) in South Dakota used a program they called "Simumate" to aid

producers in evaluating crossbreeding systems. Hilley and Leman (1976)

reported a model to examine the effects of biological variables on re-

productive efficiency of swine. This model could also be adapted to

handle some economic variables and to determine the effects of certain

management changes on returns.


Design of Study

This study consisted of three phases:

1) the design and development of computer models of a cow

as a system and of a herd;

2) the application of the models to estimate the production

efficiency of five breed groups of cattle using produc-

tion data collected over a nine year period at the Uni-

versity of Florida Beef Research Unit at Gainesville; and

3) the use of the models to evaluate alternative beef produc-

tion systems for the southeastern United States.

The rationale, assumptions, and documentation for the models are

discussed below. The computer model is included in Appendix B.

Description of the Model

Selection of a Modeling Technique

Computer models of real systems have been written in general pur-

pose programming languages such as FORTRAN or PL/1, in pre-packaged pro-

grams such as the MPS 360 Linear Program, or in specialized languages

such as SIMSCRIPT or GPSS. The DYNAMO computer language (Pugh, 1970)

was used to construct the model used in this study.

DYNAMO is a specialized computer language developed at Massachu-

setts Institute of Technology by J. W- Forrester and associates. The

philosophies underlying the genesis of the language and its use to

solve problems commonly found in industrial management have been

described by Forrester (1961).

DYNAMO is an easy language to learn. Thus it is possible for an

experimenter to write and maintain his own programs. The language is

flexible and can handle a large number of variables. DYNAMO programs

are efficient and are inexpensive to run, even for large models. DYNAMO

compilers are compatible with IBM 360 or 370 systems.

The model used in this study was a deterministic model. In other

words, no stochastic (statistical) variables were inserted in the model.

Where experimental data were not available, the best available estimates

were obtained. In some cases it was necessary to rely solely on the

judgment of experienced investigators and producers. The objective of

a study such as this one is to approximate certain aspects of a real

system as closely as possible. If a researcher is to accomplish this

objective, he must be willing to accept some data estimates which may

not be well documented or he must be willing to make the necessary


Since the model was deterministic and the results have no distri-

butions associated with them, a statistical analysis of the differences

between beef production systems was not possible. However, as pointed

out by Forrester (1970) it is not the intention of this modeling

approach to yield analytical solutions. The real systems are far too

complex. Rather, this is an experimental empirical approach in search

of more knowledge, and thereby better results but not promising analy-

tical or "optimum" solutions to any question. The major achievements

of the technique are to reduce a complex composite of variables into

comprehensible terms of significance to the user and to provide infor-

mation for choosing between specific alternatives faced in making mana-

gement decisions.


There are two parts to the model used in this study: Model I,

the Cow Efficiency Estimator, and Model II, the Herd Efficiency Esti-

mator. Model I computes the TDN requirements for a cow and her calf

using variables such as animal weight and gain, seasonal changes in cow

weight, cow milk production, physical activity of the animals, and

the quality of the feed being consumed. TDN may come from various

sources, including pasture, and can be assigned a cost and the amount

of TDN from each source determined. Thus, cost for producing an

individual cow and calf can be determined. A schematic of Model I is

shown in figure 1.

Data on TDN requirements 'and individual animal costs from Model I

are used as input data in Model II, the Herd Efficiency Estimator. In

addition, information on cattle prices, fixed costs, pregnancy and calf

survival rate, death losses, heifer replacement and culling policies,

in Model II. The model will then calculate biological efficiency fac-

tors such as TDN per animal or per herd, and beef produced per acre.

It will also compute economic efficiency factors such as cost per pound

of gain, cost per pound of TDN, cost per pound of beef sold, net returns

to the herd, net returns per pound beef sold, or net returns per acre.

Model II is diagrammed in figure 2.

The symbols commonly used in DYNAMO models and used in the diagrams

of figures 1 and 2 include the following:

Flow channels for resources

- - -- Information flows


SD 4 Rate equations
Source or sink

Level or stock Auxiliary equations

Level or stock equations represent varying contents of reservoirs of the

system. Rate equations define rates of flow between levels of the system.

Auxiliary equations are generally used in DYNAMO to reduce the complex-

ity of rate equations by defining the many factors that enter the sys-

tem. Model I determines cow and calf nutrient requirements. Most of

the diagram in figure 1 indicates how the model makes these determina-

tions within each time period. Thus mostly auxiliary equations. rather

than level or rate equations are used in the model.

Model I: Cow Efficiency Estimator

The model sums the total nutrient requirements of a cow for one

year then continues to add to this total the nutrient requirements for

carrying her calf from weaning to slaughter. Dollar values are assigned

to each unit of TDN consumed. All calculations are made at monthly

intervals. The productionsyear for the cow begins when she weans her

last calf and ends 12 months later when she weans her current calf.

Cow weight in a given month is determined by the equation



COWWTk is cow weight in the kth month in kilograms,

MCW is. mature cow weight in kilograms,

PMCW is percent mature cow weight attained at beginning of

the production year,

CGk is true cow growth during the kth month in kilograms,




O - -

Figure 2. Simplified flow diagram of herd inventory sector,
Model II, Herd Efficiency Estimator

CWFk is a monthly cow weight factor to account for seasonal

weight fluctuations.

The gain of a cow which has not reached 100 percent of her mature

weight is calculated from her estimated average daily gain over the

production year. Seasonal weight fluctuations can be readily changed

to suit the environment being modeled simply by changing the monthly

cow weight factor (CWF).

Under adequate nutrition, cow milk production reaches a peak during

the first or second month of lactation then steadily declines. For

the present model the rate of decline in milk production (table 1) was

approximated using the data of Dickey (1971) and Rutledge, Robison,

Ahlschwede, and Legates (1971). These data also correspond closely to

those reported by Melton, Riggs, Nelson, and Cartwright (1967). Daily

milk yield is determined as:



DMYk is daily milk yield during the kth month,

DMYFM is daily milk yield during the first month of lactation,

MYF is the milk yield factor for the kth month as determined from

table 1.

Net energy maintenance requirements for cows and calves are

calculated from the generally accepted (Crampton and Harris, 1969)


I NEM=AF X 0.070 X W075


NEM is daily net energy for maintenance in megacalories,

AF is an activity factor,

W is animal weight in kilograms.


Month of Lactation Milk yield factor1

1 1.00

2 0.97

3 0.92

4 0.84

5 0.78

6 0.73

7 0.69

8 0.65

9 0.60

IMilk yield as a percent of milk yield during the first month
of lactation X 0.01.


The activity factor represents the energy cost of incidental

activity. According to NRC estimates (NRC, 1970), the activity fac-

tor for an animal confined to a.feedlot is 1.1. Freden (1970) reviews

research indicating that range cows require 49% more energy than

housed cattle. This work suggests an activity factor of about 1.6

for range cattle. He also points out that the NRC requirements for

dairy cattle (NRC, 1971) are 16% greater than requirements for beef

cattle (NRC, 1970) which are presumably on pasture. This increase

suggests an activity factor of about 1.25. The activity factor for

grazing cows in this model was-generally estimated at 1.4.,

Net energy for gain of cows is calculated by the same formula

used by the NRC (1970) to calculate NEG for heifers.

j NEG=(0.05603 X ADG + 0.01265 X ADG2) (W075

NEG is daily net energy for gain in megacalories,

ADG is average daily gain in kilograms,

W is animal weight in kilograms.

OFor all calf gains the NRC steer'formula for net energy is used:

NEG=(0.05272 X ADG + 0.0684 X ADG2) (W0"75

These net energy computations are made on a monthly basis in the

program. All of the variables used in the equations can be changed

at monthly intervals.

Because of the wide availability of and ease of determination of

TDN values, the most convenient means of expressing nutritional cost

is probably cost per unit of TDN. Thus, it is desirable to convert net

energy values (a convenient system for expressing nutrient intake in

terms of animal weight and gain) to TDN values (a convenient system for

assigning costs to each unit of nutrient.intake). The disadvantage of

the TDN system is that the efficiency with which a unit of TDN is

converted to energy for maintenance, gain, milk production, etc.

declines as the quality of the food source declines. For example, a

cow requires fewer units of TDN to maintain a constant body weight on

a concentrate ration than if grazing a frosted grass pasture.

In theory, net energy requirements for maintenance and gain do not

vary with ration quality as do metabolizable energy (ME) or TDN re-

quirements. The NRC (1970) has published efficiency-of-energy-

utilization relationships for converting ME to NE. This ME value can

be converted to TDN by assuming 3.6155 Mcal of ME/kg of TDN. TON

requirements for maintenance and gain can be calculated from the





TDNM is kilograms of total digestible nutrients required for


TDNG is kilograms of total digestible nutrients required for gain,

NEM is net energy for gain in megacalories,

NEG is the net energy for gain in megacalories,

MDFk is the maintenance efficiency factor from figure 3 for

month k,

GEFk is the gain efficiency factor from figure 3 for month k.

Since NEM and NEG are different for cows and calves there is, of

course, a different set of equations for determining TDN in each of

these two animal types.

The efficiency factors for net energy conversions for maintenance,

gain, and milk production are derived from the graphs in figure 3. The


graphs of the relationships for maintenance and gain are adapted from

NRC (1970) data. These relationships also correspond closely to that

used by the ARC (1965) in England. The efficiency factor is plotted

against a hypothetical "Feed Quality Index" (FQI) the values of which

range from 1 to 10. A working definition of "Feed Quality Index" is

shown in table 2. A "Feed Quality Index" allows the program to make

monthly adjustments for feed quality. The selection of the appropriate

index value for a particular feed source usually requires some sub-

jective evaluation by the experimenter. The relationships between

feed quality, especially forage quality, and the .efficiency of ME

conversion to NE needs more study by nutritionists. Another

possibility suggested by Harris (1973) was to measure feed quality as

Mcal ME/kg of dry matter. This is the approach used by the ARC (1965).

If we assume that cow's milk contains 0.156 kg TDN/kg milk (NRC,

1970), then the TDN required daily for lactation can be determined as




TDNMP is the kilograms of total digestible nutrients for milk


DMY is cow milk yield per day in kilograms

EFMP is the efficiency factor (figure 3) for ME conversion to NE

during milk production.

Neville (1971) estimated that Hereford cows on a 40% concentrate ration

required 0.30 kg TDN per kg of 3.4% fat corrected milk produced. NRC

(1971) estimates for dairy cattle are 0.33 kg TDN per kg of 3.5% fat

milk produced. This latter figure represents a conversion efficiency

of 51%. To derive the graph for the milk conversion efficiency factor

Figure 3. Assumed relationships between feed quality and efficiency of
ME conversion to NE.










Feed quality index Forage rations Concentrate rations


2 Low quality

3 No concentrates

4 Medium quality


6 20% concentrate

7 High quality 40% concentrate

8 60% concentrate

9 80% concentrate

10 Cow's milk

in figure 3, it was assumed that a cow on a 20% concentrate ration is

50% efficient when converting TDN from feedstuffs to milk TDN. This

assumption appears consistent with the data cited above. Furthermore,

it was assumed that the slope of the milk efficiency curve (figure 3)

is the same as that of the maintenance efficiency curve. The major

justification for this assumption is that calorimetric studies show

metabolizable energy is used with similar degrees of efficiency for

both maintenance and milk production in lactating animals (NRC, 1971).

The curves published by the ARC (1965) correspond closely to the curves

in figure 3.

No provision is made in the model for additional energy due to

gestationother than the energy required to maintain the seasonal

weight increase, much of which is due to the weight of the fetus and

fetal membranes. This assumption is based on the observation of Brody

(1945) that there is generally no increase in nutrient intake of

mammals during pregnancy. A possible explanation for this phenomenon

may be that the mother reduces her activity while pregnant and saves

energy for growth of the fetus or that fetal gain is accomplished at

the expense of a loss in maternal body tissue.

Using the above relationships one can calculate the daily TDN

required by the cow for maintenance, growth, reproduction, and lacta-

tion. TDNCOW is determined by:


with TDMCW and TDNGCW coming from NRC equations for heifers as previous-

ly described for TDNM and TDNG

TDN requirements for calf maintenance and growth are calculated

using the equation:


where TDNMCLF and TDNGCLF are derived from NRC equations for steers as

described above for TDNM and TDNG.

The net TDN harvest per day by both cow and calf are described as




MILKTDN=DMY X 0.156 kg TDN/kg milk,

MILKTDN represents the amount of the calf's TON requirements met by

its dam's milk. DMY is the daily milk yield as described previously.

Monthly TDN requirements for cow and calf are determined by multiplying

NETTDN by 30.417, the average number of days per month in a non-leap


The TDN requirements for cows may be filled either from pasture

or from supplement. The TDN available from pasture in the kth month




PTDNk is the available pasture TDN in the kth month,

AUM is the animal unit months of grazing available in the kth


TDN/AUM is the TDN assumed to constitute an animal unit month of


PSRk is the pasture stocking rate (in acres per animal unit during

the kth month.
The supplement required during the kth month is:



NETTDNk is the monthly NETTDN described above.

In calf grazing programs, no provision was made for supplementation.

Thus, TDN harvested from grazing is simply TDNM plus TDNG.

Model II: Herd Efficiency Estimator

Model II determines the inventory of all animals that comprise a

herd, including brood cows, replacement heifers, weanling calves,

stocker.calves, and slaughter animals. It provides for death losses

and culling of breeding stock. This phase of the model is diagrammed

in figure 2.

Using data from Model I, the Herd Efficiency Estimator determines

the TDN requirements for the herd and acreage requirements and costs

for production of that TDN. It also assigns a value to each animal

sold from the herd and computes total herd sales. Thus by using the

cost data shown in tables 3, 8, and 10, it is possible to compute net

returns for the herd.

The inventory of animals in the herd is determined as follows

beginning with the(brood cowherd.

3 3 3

COWSk is the number of breeding age cows in the present or kth


COWS. is the number of breeding age cows in the herd during the
previous or jth year,

BRTH. is the number of bred replacement heifers transferred to the

herd at the end of the jth year,

CULLS. is the number of cows culled during the jth year,

CD. is the number of cows which died during the jth year.


WR is the weaning rate or the percent of the cow herd weaning


CONCR is a constant culling rate of 5% to allow for the culling of

old, sick, crippled, or poor producing cows.

All replacement breeding stock (BRTH) is assumed to be produced in

the herd and atstable herd size is determined by:



RHK. is the replacement heifers kept during the previous or the

.th year,

CULLS is the number of cows culled,

CD is the number of cows died,

BRD is the number of bred replacement heifer death losses.

This equation is a simplified representation of the equations used when

herd size is stabilized. The DYNAMOmodel used in this-_study-was._a...

modified version of a program used to analyze herd expansion policies

and involves a feedback loop to allow for expansion of cow numbers

until some specified steady state herd size is reached. In the current

study, the herd size was set at 1000 cows and as each new set of data

was specified,-the program was allowed to run for seven time periods in

order to stabilize the animal inventories. This explains the presence

of the information feedback loop between "Cow Herd" and "Replacement

Heifers Kept" as shown in figure 2.

In allocation of nutrients 'to replacement heifers, Model II assumes

that from 12 to 24 months of age a replacement heifer consumes 80% as

much TDN as the mature cow in her same size category. Once they are

transferred into the breeding herd and calve at 24 months of age, all

cows, regardless of age, are assumed to require the same amount of

nutrients. This assumption is consistent with the data of Cruz (1961)

who reported that the nutrient requirements of 800 pound young growing

beef heifers during their first lactation were approximately the same

as for mature lactating cows weighing 900 to 1100 pounds.

The calves which enter the sale inventory are determined as follows:



FC is the number of feeder calves,

CALFW is the number of calves weaned (cows X weaning rate) and,

RHK is the number of calves kept as replacement heifers.
4' --- -- C
The program allows three options for the sale of calves'. They

may be sold at weaning, they may be grazed for several months and sold

as stockers, or they may be sold at the end of a feedlot phase as fat

slaughter cattle.

By using cost and price estimates and information generated by

Model I, the Cow Efficiency Estimator (Model II) also determines the

TDN requirements, acreage requirements, and net returns for the herd.

Most of these calculations are straightforward and can be followed in

the program printout shown in Appendix B. The TDN requirements, costs

and animal weights for each phase of the production cycle for an in-

dividual animal are obtained from Model I and entered as data in Model

II. Estimates of cattle prices and TDN production per acre for the

different pastures and crops (table 3) are entered directly into Model

II. Adjustments are made by the program for early culling of non-

pregnant cows and cows which lose calves between pregnancy testing and

the end of the calving season.

Sources of Information

The University of Florida Beef Research Unit program was used as

a prototype beef production unit for this study. From the program,

extensive data were available on cow weight, fertility rates, calf

survival, weaning weights, and calf gain. Reliable and comprehensive

data on pasture fertilization and stocking rates were also available.

The assumptions used in the Beef Research Unit analysis are detailed

in Chapter IV.

Data from the Beef Research Unit program also heavily influenced

the assumptions used in the Coastal Plains study. Experiment station

data from Florida, Georgia, Alabama, and Mississippi were also used

in the Coastal Plains assumptions.

Cost and Price Assumptions

Input prices used in the cost budgets are primarily those prices

existing at the time the final analyses for this study were done in

1975 and early 1976. Table 3 summarizes costs for pastures and crops.

Pasture costs include labor and all equipment costs, including depre-

ciation and repairs. Cost per pound of TDN for each pasture program

is determined by dividing the pasture costs (tables 15 18, Appendix

A) by the TDN harvested by grazing from each acre of pasture. This

estimate of grazed TDN is determined by using the animal data outlined

in the footnotes of table 3. These data, including stocking rates, are

S based on numerous experiment' station reports from Florida, Alabama, and

Georgia and on data from well-managed operations in the same area. The

data were used in Model 1 to calculate animal TDN requirements for the

periods indicated. Thus by using known animal production response

and pasture stocking rates, it was possible to estimate the unit cost



Stocking Rate Cost per TDN Cost
System Description or Yield TDN/Acre Acre per Lb.

units/acre, lbs $ $

I-III Clover-grassa 0.77 Cows 3660 36.78 0.0100

IV Clover-grassa 1.67 Cows 5152 36.78 0.007

II Ryegrass-Clover- 1.75 Yearlings 5518 57.80 0.0105

I Rye-Ryegrass- 1.75 Yearlings 2452 76.78 0.0313

I Milletd 3.25 Yearlings 3565 73.25 0.0205

I-V Corn (Silage)e 12 Tons 6000 204.00 0.0340

I-V Corn (Grain)e 60 Bushels 2898 120.00

aBased on 1050 lb cow giving 11 Ibs milk/day; see table 15 for cost.

bBased on yearling with 530 lb initial weight gaining 1.7 Ibs/day from
February 1-May 31, then 1.3 Ibs/day, June 1-September 30; see table 16
for cost.
Based on yearling with 394 Ibs initial weight, gaining 1.7 Ibs/day,
145 grazing days; see table 17 for cost.
dBased on yearling with 569 lb initial weight, gaining 1.3 Ibs/day,
100 grazing days; see table 18 for cost.
eBased on corn silage at 25% TDN as fed; ground ear corn, 70 Ibs/bushel,
69% TDN as fed; see table 19 for cost.
Assumptions for Systems III also apply to Beef Research Unit.


Brood Replacement Feeder
Item Cows Heifers Yearlings

Veterinarian and Medicines

Worming (twice) 3.50 2.00 2.00
Vibrio Vaccine 0.80 0.80 ----
Other Vaccines ---- 1.00 1.50
Insecticides 0.50 1.00 1.00
Vet Fees 1.00 1.00 1.00
Miscellaneous 0.50 6.30 0.50 6.55 1.00. 6.50


Minerals 1.00 1.00 1.00 1.00 1.00 1.00

Miscellaneous Expenses 3.00 3.00 3.00

Breeding Costsb 10.31 10.31

20.61 20.86 10.50

aBranding, tagging, weighing, etc.
From table 20.
cHeifers in Coastal Plains Systems III-V are assumed to consume as a
pasture supplement 1000 lbs/year (5 lbs/day for 200 days) of Ration
A, table 19 at a cost of $49.01.


Weight High- High- Low-
Rangea Highb Lowc Highd
lbs $/lb $/lb $/lb


At Weaning 324-592 0.50 0.50 0.32

At Feedlot 792-1101 0.50 0.40 0.44

At Slaughter 896-1161 0.50 0.39 0.50

Cull Cows 850-1200 0.33 0.33 0.33

aSee table 10.
bCalf prices high at weaning, high
price structure examined for the
CCalf prices high at weaning, low
dCalf prices low at weaning, high

at slaughter. (This is the only
Beef Research Unit data.)
at slaughter.
at slaughter.

of TDN for use in subsequent models to.compare animals of different

production characteristics.

The costs of mixed rations are shown in table 19 (Appendix A).

The NRC (1970) TDN values for the ration ingredients were used to

determine TDN costs. Breeding costs are shown in table 20 (Appendix A)

and variable costs for non-feed items are included in table 4.

x It is important to note that no interest charges, land rent, or

overhead items are included in the analysis done here. Such costs can

vary tremendously between operations and are not essential to the

comparisons which were made in this study. Consequently, they were

omitted. A list of common overhead items is shown in table 40, Appendix

A. The effect of their inclusion in analyses is discussed in Chapter


Cattle prices were varied in this study. The price ranges used

here and shown in table 5 were selected so as to be consistent, not

only with historical market behavior, but also with cost assumptions.

In other words, these prices would allow a rational producer of suf-

ficient size and management ability to make an acceptable return on

his investment.


Data from the University of Florida Beef Research Unit near

Gainesville provided a means of comparing the production efficiency

of five breed groups of cattle of different size, milk yield, growth

rate, fertility level, and carcass composition. Data from the five

breed groups were analyzed using the two computer models described

in Chapter III. Various measures of production efficiency were

determined at weaning and at slaughter. The measures of production

efficiency included pounds of beef per acre, pounds of TDN per pound

of beef produced, cost per pound of beef produced, net returns per

1000-cow herd, net returns per pound of beef sold, and net returns per


Beef Research Unit Data and Assumptions

The Beef Research Unit project at the University of Florida was

unique in that the foundation females were typical of the commercial

cattle in Florida during the late 1940's and early 1950's. Five

breeding systems were compared for improving productivity on clover-

grass pastures. The systems included: 1) upgrading to Angus, 2). up-

grading to Hereford, 3) Hereford-Angus crisscross, 4) Brahman-Angus

crisscross and 4) Hereford-Santa Gertrudis Crisscross. The sires used

in the program came mostly from the USDA Beef Cattle Research Station

at Brooksville, Florida. They were top sale bulls, were used one or


two years, and then returned to Brooksville. As representatives of

their respective breeds, the bulls were of better than average growth

potential and came from the better milking dams that have been culled

rigorously for reproductive failure.,

For a period of five years, beginning in 1952, the foundation

females were mated to bulls of four breeds including Angus, Brahman,

Hereford, and Shorthorn. At the end of this period (1957) the young

females were assigned to the systems indicated above on the basis of

breed composition to move the program along as rapidly as possible.

The breeding season initially was restricted to a period of 90

days beginning in early March. The length of the season was gradually

shortened to 65 days by 1965.

In the BRU model the average calving data was set at January 1

and the average weaning data at September 30. Cows were palpated

for pregnancy at weaning with all nonpregnant cows being culled from

the herd. In addition, cows whose calves died before weaning were

culled along with an assumed 5% of the lower producing cows. All cull

cows were replaced with pregnant heifers. Steer calves were placed in

the feedlot at weaning and fed for a period of 18 days to an average

USDA grade of high good. For the purposes of this study, it was assumed

that surplus heifers were fed also.

Initially heifers were bred to calve first at three years of age.

Beginning with the 1958 calf crop, one-half of the heifers were bred

to calve at two years of age and one-half bred to calve at three years

of age. This practice was continued until 1968 after which all heifers

were bred first as yearlings. Calving at two years was assumed in this

analysis. None of the calves were creep-fed when with the cow.

The period covered by the present report was the last nine years

of the trial (1964-1972). The data from all age groups of dams (2

years and older) are included. Average production performance for

the period was adversely affected by disastrous flooding during one

calving season which lowered survival rate of calves during that

year and calving rate during the following year.

The cattle were maintained on clover-grass pastures for approx-

imately nine months. During the winter months, cowswere fed a corn

silage ration with a protein supplement. Since the herd was dispersed

before milk yield data was obtained for each group, milk yields were
estimated using relative weaning weights and data from equivalent

breed groups under similar conditions. Steer calves were placed in a

feedlot immediately after weaning and fed for approximately 180 days on

a moderately high energy ration. For this study, feed prices were

based on a grounrear corn ration. Cows were weighed every three months.

Weaning weights were obtained about August 20 although calves were

usually not separated from their dams until late September. All steers

were weighed prior to slaughter. The assumptions used in the Beef

Research Unit analysis were:

1) Gain of the average cow in the herd.was 36.5 Ibs/year.

/ 2) Average birth weight of all calves was 65 Ibs.

3) The Feed Quality Index Indices from January through December were,

respectively, 5, 5, 7, 7, 7, 5, 5, 4, 3.S. 3.3, 3, and 5 for cows.

4). Pasture production capacities from January through December were,

respecitvely, 0.0, 0.6, 0.9, 1.0, 1.1, 1.2, 1.2, 1.0, 0.8, 0.4, 0.0,

i 0.0 AUM's of grazing.

/ 5) One animal unit month (AUM) of grazing supplied 600 lbs TDN in

grazed forage, where an AUM is the monthly requirements of a 1050

Ib cow giving 11.0 Ibs milk/day to a 350 lb calf.

6) The cow weight factors (factors by which mature cow weight was

multiplied) from January through December were, respectively

1.10, 1.00, 0.95, 0.96, 0.97, 0.98, 0.99, 1.00, 1.02, 1.04, 1.07,

and 1.09.

7) Replacement heifers were supplemented for 200 days with 5 Ibs/day

of Ration A (table 19, Appendix A) and consumed 80% as much

pasture TDN as their mature dam.

8) Death loss rates were 2% for cows, 1% for feedlot yearlings, and

1.5% for replacement heifers.

9) The activity factor was 1.4 for cows and calves on pasture and 1.1

for calves in the feedlot.

10) Pasture costs and TDN production were as shown in table 3.

v 11) Pasture stocking rates were 1.3 acres per animal unit.

12) Nutrient requirements not fulfilled by grazing were supplied with

a corn silage ration supplemented with protein (table 19, Appendix


13) Feed costs were $.010/lb TDN consumed from pastures, $.039/lb

TDN for the cow wintering ration, and $.069/lb TDN for the feedlot

ration (tables 3 and 19).

14) Animal non-feed costs were $20.61/year per cow and $20.86/year per

replacement heifer, including breeding costs, veterinary expenses,

medicine, and minerals (table 4).

15) Non-feed costs for animals in the feedlot were $0.88/month.

16) The value of calves sold was $0.50/lb at weaning and at slaughter;

cull cows sold for $0.33/lb.

Production data for five breed groups were assembled by taking the

simple average of data collected from 1964 through 1972 at the Univer-

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Results of Beef Research Unit Analysis

Biological Components

Measures of biological efficiency for herds of the five breed groups

of Beef Research Unit cattle are shown in table 7. In spite of a wide

variety of cow sizes, milk yields, and fertility levels, there is very

little difference in the indicators of biological efficiency examined


The average of each measure of production efficiency was assigned

a value of 1.0 and used as the basis of indexing the data from each

breed group. These index values are shown in parentheses in table 7.

In no case did the difference between any two breed groups exceed 3.5".

Economic Components

Several measures of economic efficiency are shown in table 8. The

breed groups showed only minor differences in cost per pound of beef

sold. However, the profit components did indicate some differences.

The highly fertile Angus-Hereford cross ranked first in all three

measures of profitability. In general, the straightbred Angus ranked

second (except in net returns per 1000-cow herd), the Angus-Brahman

cross third, the straightbred Hereford fourth, and the Hereford-Santa

Gertrudis cross last.

What were the production factors (table 16) influencing these

rankings? Cow size seemed to show no relationship to profitability,

except that it lowered the rank of the small Angus cattle, especially

at weaning, in net returns per 1000-cow herd. This measure of returns,

however, is probably not a very good indicator of economic efficiency

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since most producers are likely to be constrained by land rather than

by cow numbers. The best measures of profitability, net returns per

pound of beef sold and especially net returns per acre, did not appear

to indicate any relationship between cow size and profitability.

Note that cost per pound of beef sold was approximately the same

for all breed groups. Thus differences in profitability must have

been due to factors which affect income rather than factors affecting


Income per pound of beef sold was influenced by the value of the

calf -- primarily carcass quality and dressing percent. Table 6

shows that that Angus and Angus-Hereford crosses had the highest carcass

value chiefly due to their higher carcass grade. Income per pound of

beef sold was also higher in a herd where most of the beef came from

calf sales rather than from low-priced cull cows. Consequently, herds

with high fertility levels would have fewer cull cow sales and more

calf sales. This seemed to be the primary factor affecting net returns

per pound and net returns per acre. :In these two measures of profit-

ability the breed groups ranked almost exactly as they ranked in

weaning percent (table 16).

In summary, the net returns per acre for the Angus-Hereford cross

were 9.6% higher at weaning and 8.6% higher at slaughter than the

average of the five breed groups. The Angus-Hereford cross had a 7.2%

advantage at weaning and a 4.9% advantage at slaughter over its nearest

competitor, the straightbred Angus. Most of the differences in profit-

ability between breed groups appeared to be due to fertility levels.


The ultimate objective of this work was to compare alternative

systems of beef production in the Coastal Plains of the southeastern

United.States. The general design of the Coastal Plains beef study

is illustrated in figure 4. Five hypothetical forage production and

feeding systems were selected for study. Animals with different

assumed production characteristics were examined within each forage

and feeding system. Finally, the effects of three market conditions

were evaluated for all combinations of forage feeding systems and

animal production characteristics.

Coastal Plains Data and Assumptions

Forage and Feeding Systems

The five hypothetical forage and-feeding systems analyzed here

and the characteristics assumed for each system are described below.

System I: pasture to annual forage to feedlot. After separation

from their calves on September 30, cows were assumed to graze on

surplus grass during October and November. From December through

February they were fed a silage ration. From March through May, which

included the breeding season, pastures were predominantly clover. The

clover went dormant in early June and cows grazed primarily grass until

the end of the production year in September. After weaning, calves

received a corn silage ration during October and November and gained



I .
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0.3 lbs/day. From December through May, calves were grazing a rye-

ryegrass-clover pasture on which they gained 1.5-1.8 lbs/day. Gains

here were dependent on growth potential as reflected in cow size.

From June through September, calves gained 1.2-1.5 Ibs/day on millet.

They were then placed on a feedlot ration (table 19, Appendix A) for

60 days and gain.>2.2-2.5 lbs/day. System I is presently a popular

system of beef production in the southeastern United States.

System II: perennial pasture to topseeded perennial grass to feed-

lot. Brood cows in this system were handled exactly as assumed in

System I. Calves were placed on a corn silage ration (table 19,

Appendix A) after weaning, from October through January. They were

assumed to gain 0.3 Ibs/day during their first two months on this ration

then 0.9-1.2 lbs/day during December and January. In February through

May they gained 1.5-1.8 lbs/day, the same as in System I. From June

through September, calves remained on these pastures, which were now

predominantly- Coastcross bermuda grass, and gained 1.1-1.4 Ibs/day.

After leaving Coastcross bermuda pastures at the of September, calves

were placed in the feedlot for 60 days where they gained'2.2-2.5 Ibs/day.

Such a program as System II is not now commonly practiced in the

southeastern United States. However, recent work by Utley, Marchant,

and McCormick (1976) in Georgia suggests that such a program is feas-


System III: perennial pasture to feedlot. Cows were managed and

fed exactly.as assumed in Systems I and II. The calves were placed in

the feedlot immediately after weaning, where they were assumed to gain

0.5 Ibs/day during their first month there. Gains then increased to

2.3-2.6 Ibs/day from November through May. The total feeding period

was 240 days. These animals weighted slightly less at slaughter than

those in Systems I and II. Programs such as System III have been

popular systems in the past, though the cow-calf operations and the

feedlot phase usually occur at separate locations with calves under

different ownership. This system was employed at the University of

Florida Beef Research Unit.

System IV: drylot/perennial pasture to feedlot. This is a semi-

confinement system with brood cows maintained on limited pasture and

in a drylot when pasture is inadequate r not available, and with

weaned calves going directly into the feedlot. Simulation runs of

Model I indicated that, during most months, much more forage was

available then was consumed by the cattle. Actually, much of the

forage in the late summer and fall months was forage which had

accumulated during rapid summer growth. In an attempt to utilize

forage more efficiently, the effect of increasing the stocking rate

more than two-fold to 1.67 animals units/acre was simulated. At this

stocking rate, all or nearly all of the forage produced during June,

July, and August was utilized with little or no supplementation required.

To allow for reduced grazing activity, the activity factor was reduced

from 1.4 to 1.25. Note in table 3 the increase in TDN/acre in the same

type pasture with an increased stocking rate. This increase in TDN/

acre occurred primarily because forage was grazed at its most nutri-

tious stage when it had its maximum TDN value for the animals. TDN

yields were probably also enhanced by a reduction in waste and tramp-

ling. Cows in this system were managed the same as assumed in Systems

I through III except that they received a corn silage supplement when

pastures were inadequate to meet their needs. Calves were placed in

the feedlot after weaning and gained exactly as assumed in System III.

System V: drylot to feedlot. Brood cows in System V were assumed

to be confined exclusively in a drylot where they were fed a corn

silage ration (table 19, Appendix A). After weaning on September 30,

calves were placed in a feedlot and were assumed to gain exactly as

those in Systems III and IV. The activity factor for all animals,

including brood cows, was 1.1.

Note that Systems I and II involve a stocker phase in which calves

are grazed on a forage between weaning and the feedlot. In Systems

III through V, calves are weaned from their dams and placed directly

into a feedlot.

Animals Production Characteristics

The major animal production characteristics used in the study

are outlined below. The assumed values for each characteristic are

shown in table 9.

Cow size

Because of the great variations in cow weight due to factors such

as season and pregnancy status, weight alone may not be a good indica-

tor of cow size. It is obvious, nevertheless, that if pregnancy status

and condition, which are usually associated with season, are held

constant, then weight would be a good measure of cow size. The cow

weight factor in table 21 (Appendix A) is an attempt to allow for

seasonal weight changes caused by factors such as pregnancy status and

body condition. If the cow weight factor accounts for environmental

variation in weights then the cow weights shown in table 8 would

reflect mature genetic cow size. These weights were selected to approx-

imate different cow sizes commonly found in the southeastern United

States. The weights fall within the ranges reported by Warwick (1971)

for British-type cows.


Mature Milk Calf Birth to In Pregnancy Calf
Cow Wt. Yielda Birth Wt. Weaning Feedlotc Rate Survival
lbs lbs/day lbs lbs/day Ibs/day % %

850 7 55 1.1 2.2 92 95
850 9 55 1.3 2.2 91 95
850 11 55 1.5 2.2 90 95
G50 13 55 1.7 2.2 89 95

950 8 62 1.4 2.3 93 95
950 10 62 1.6 2.3 92 95
950 12 62 1.8 2.3 91 95

1050 9 70 1.5 2.4 89 95
1050 11 70 1.7 2.4 88 95
1050 13 70 1.9 2.4 87 95

1200 10 80 1.6 2.5 84 95
1200 12.5 80 1.9 2.5 82 95
1200 15 80 2.1 2.5 80 95

aMilk yield during first month of lactation.
bSee text for interim gains between weaning and feedlot.
cGains for Systems I-II; add 0.1 lbs/day for Systems III-V.

As shown in table 9, cows were grouped into four size categories --

"small," "medium," "large," and "very large." These groupings were

intended to represent the genetic size of the cow and, as such,

influenced the growth potential of that cow's calf. Cow size was

an independent variable in the study.

Birth weights were assumed to be proportional to cow size. Calf

birth weights were 6.5% to 7.0% of dam weight.

Milk yield

In this study milk yield was assumed to vary with stage of lactation

and cow size. The decline in milk yield during lactation has been

reported by Dickey (1971); Rutledge, Robison, Ahlschwede, and Legates

(1971); and Melton, Riggs, Nelson, and Cartwright (1967). Data from

the first two studies were used to estimate the rate of decline in milk

yield assumed in this study and shown in table 1.

While the relationship of milk yield to cow size is well recognized

in dairy cattle (Preston and Willis, 1970), the relationship between

body size and milk yield in beef cattle has not been studied critically.

It is reasonable, however, to believe that the positive relationship

between cow size and milk yield would apply in beef cattle also. Such

a positive relationship is assumed in this study. The assumed average

daily milk yields for the entire 8 month lactation ranged from 5.7 to

12.1 lbs/day and are consistent with those yields reviewed in Chapter

II. Assumed milk yields during the first month of lactation are shown

in table 9. They represent milking levels of "low," "moderate," and

"high," including a "very high" level for "small" cows only. Milk

yield in this study was an independent variable within each cow size

grouping but was assumed to be somewhat dependent on cow size.

Fertility rates

Pregnancy rates used in this study are shown in table 9. Note that

pregnancy rate varied with both cow size and milk yield. The effects of

increased milk production in lowering reproductive performance has been

recognized by animal husbandman (Willham, 1972).

The assumed relationship between cow size and pregnancy rate. is

also consistent with the views of animal husbandmen in the southeastern

United States but is more difficult to defend. The most fertile size

group, the 950 pound group, would be representative of the highly fer-

tile Angus-Hereford cross. The smallest 850 pound group would most

likely include a small straight-bred Angus herd, or perhaps an Angus-

Jersey cross at the highest milk level in this group, and would gen-

erally not be as fertile as the Angus-Hereford cross. As cattle get

larger, in the 1050-and 1200-pound groups, they tend to become less

fertile. Butts (1972) cites data supporting this assumption.

In this study, pregnancy rate was a variable which depended on

both cow size and milk yield. Calf survival was assumed constant across

all production characteristics and forage-feeding systems.

Calf gain

Calf gains are summarized in table 9 and were detailed previously

in the description of forage and feeding systems. Pre-weaning gains

were assumed to be correlated with cow size and milk yield. The pos-

itive effects of milk yield on weaning weight are well documented.

Research by Gifford (1949), Gifford (1953), and Drewry, Brown and

Honea (1959) has suggested that calf size and gains influence milk

yield. Thus, if calf gains and milk yield are positively correlated

and if calf gains and milk yield as positively correlated and if calf

gains are positively correlated with cow size, as assumed here and

suggested by Cartwright (1970), then it logically follows that cow

size and milk yield are positively correlated. Such a positive

correlation between cow size and milk yield has been assumed above.

Weaning weight was assumed to be approximately proportional to cow

size, thus implying a similarly shaped growth curve for all cow sizes

up to weaning. Slaughter weights, however, did not increase in pro-

portion to cow size, implying that, after weaning, large cattle

tended to mature more slowly than smaller cattle. While difficult

to document, this assumption seems consistent with field observations.

Furthermore, if this assumption were not invoked, slaughter weights of

large calves which showed the same calf weight to cow weight ratios as

those of small calves would be unrealistically high.

Market characteristics

A major goal of this study was to present comparisons of alter-

native beef production systems which would be meaningful and useful to

beef producers. Since most beef producers are motivated by profit, the

profitability of these alternative beef systems must be compared. The

production model used here is designed to estimate costs for the

different systems. Determining profits, however, requires an estimate

of the market value of the animal. Since beef prices are highly

variable, it was necessary to make some assumptions that would allow

the comparison of beef system profitability over a wide range of mar-

ket conditions.

First it was assumed that beef prices will generally exceed

production costs and be maintained at a level that will provide pro-

ducers with an incentive to remain in the beef cattle business. Next,

in order that profitability at various stages of the calf's life cycle

could be assessed, three historically evident price structures were



High-high price structure. Under this price structure, prices were

high at weaning and remained high until slaughter.

High-low price structure. This price structure resulted in high

prices at weaning but low prices at slaughter. Such a situation

existed with calves weaned in the fall of 1973. Since such calves

will usually be sold later at a loss -- a loss not anticipated at

the time of purchase -- it is apparent this price structure will be

short-lived when it does exist.

Low-high price structure. This price structure, with low prices

at weaning and high prices at slaughter existed through most of 1974

and 1975. It is most likely to occur during parts of the liquidation

phase of the cattle cycle.

Figure 5 gives a hypothetical illustration of these three price

structures and their relationship to an estimated cost of gain curve.

The prices assumed in the study were shown in table 5.

General assumptions

For the Coastal Plains analyses, the production year was assumed

to start on October 1 immediately after weaning. At weaning time, all

cows were pregnancy tested and those which were not pregnant were

culled. Also, at this time, an additional 5% of the herd, including

cows which were sick, crippled, old, or very poor producers were culled.

A 90-day breeding season beginning in mid-March was used. The

average calving date was assumed to be February 1 and weaning occurred

eight month later on September 30.

All heifers were bred to calve at two years. In Systems I and II,

heifers were managed as stocker calves from weaning until the bred

heifers were transferred into the brood cow herd at two years of age.


U .30

-- -- High-High Price Structure
---- High-Low Price Structure

.1.0 ---- Low-High Price Structure
Cost tf Gain

200 400 600 800 1000 120

Weight (ibs)

Figure 5. Hypothetical price-cost curve for three price structure.

In Systems III and IV, heifers held for breeding were transferred into

the brood cow herd when they were weaned. From this time until they

were two years old, it was assumed that they consumed 80% as much TDN

as mature cows plus received a supplement of Ration A (table 19,

Appendix A) at the rate of 5 lbs/day for 200 days out of the year.

Surplus heifers not held for breeding were fed out along with the

steers. All animals within each system were slaughtered at the same

time. Thus, slaughter occurred at an age-constant rather than a

weight-constant basis.

The cow weights shown in table 9 were assumed to represent mature

genetic cow size. There was no cow gain other than the seasonal

weight fluctuations indicated by the cow weight factors in table 21

(Appendix A).

The following are additional general assumptions:

1) An animal unit month (AUM) of grazing supplied 600

Ibs of grazable TDN; where an AUM is the monthly

requirements of a 1050 Ib cow giving 11 Ibs of milk/

day to a 350 lb calf.

2) The nutrient requirements'of the cow not furnished by

grazing were supplied by the corn silage ration shown

in table 19 (Appendix A).

3) Feed costs are shown in table 3 and non-feed costs in table 6.

4) Annual death losses were 2% for cows, 1% for yearlings, and

1.5% for replacement heifers.

5) The activity factor was 1.1 for calves in the feedlot.

It was 1.4 for grazing animals in Systems I through III,

1.25 in System IV and 1.1 in System V.

6) Pasture costs and TDN production are summarized in table 3,


feedlot ration composition and costs are shown in table

19 (Appendix A).

7) The market value of calves and cows is outlined in

table 5.

Additional assumptions and the systems to which these assump-

tions apply are summarized in table 21 (Appendix A). Cow weight

factor is the factor by which the mature cow weight shown in table 9

is multiplied to simulate seasonal weight fluctuations. A stocker

supplement factor equal to one indicates that stocker calves are fed a

corn silage ration during that month. Uses of the feed quality index

for both cows and stockers have been described previously (Chapter III).

TDN costs for various pasture programs and rations have been developed

in table 3. The other items in table 21 are self-explanatory.

Results of Coastal Plains Analysis

The assumptions outlined above were used as input data for the

two simulation models in the manner described in Chapter III. Since

the results included both biological and economic components they have

been reported here as biological, cost, and profit components.

Results have been reported by cow size, milk level, and feeding

system. Estimates were included for three stages of calf development --

at weaning time, at the end of the stocker phase (System I and II only),

and at slaughter when the feedlot phase was complete.

Biological Components

The biological components of major interest include acreage re-

quirements for a 1000-cow herd, pounds of beef sold per acre, and

pounds of TDN per pound of beef sold. The high and low values of these

items for each forage and feeding system are shown in table 10. Addi-

tional biological components are also included in table 10. Table 10




1 I1 II1 IV V

Low Hiah Low High Low High Low High Low High

At Weaning 324 592 324 592 324 592 324 592 324 592
At Feedlot 762 1122 732 1101
At Slaughter 396 1274 S66 1253 '829 1161 829 1161 329 11i61

To Weaning 4437 6562 4437 6562 4437 6562 3967 3933 3589 5437
Stocker Phase 3437 5246 3342 5197
In Feedlot 813 1132 792 1136 2384 3494 2384 3494 2384 3494

At Weaning 10.54 12.09 10.52 12.03 10.33 12.14 9.34 10.55 8.71 9.S2
4t Feedlot 10.14 10.46 10.23 10.39
At Slaughter 3.73 10.19 9.86 10.25 8.61 9.29 7.94 8.57 7.39 8.01

At Weaning 2222 3225 2211 3217 2231 3225 1995 2916 !905 2672
A; Feedlot 3377 4381 33:8 4363
At Slaughter 3649 4635 3392 4613 3028 3993 2792 36So 2602 3452

To Weaning 1107.4 1553.9 1087.9 1515.9 1115.5 1589.5 712.9 1020.2 578.8 S54.6
To Feedlot 1570.8 2019.6 1484.9 1922.6
To Slaughter 1758.3 2201.9 1667.5 :098.4 1712.6 2195.8 1310.0 1629.4 1175.9 1471.0
To Slaughter 1570.8 2019.6 1484.9 1922.6 1113.5 1589.5 712.9 1020.2 578.S S54.6
(Buy Grain)

To Weaning 332.0 393.1 337.9 403.3 329.6 354.3 515.7 499.4 653.2 71-.7
To Feedlot 411.8 427.2 424.3 442.8
To Slaughter 413.0 426.0 425.3 440.6 391.6 410.6 524.8 538.7 31.0 059.4
To Slaughter 450.4 476.4 465.3 490.5 540.9 631.9 842.7 968.9 1006.1 1213.7

Weaning Phase 1.1 2.1 1.1 2.1 1.1 2.1 1.1 2.1 1.i 2.1
Stocker Phase, I 1.5 1.8 1.5 1.8
Stuck=r Phase 1.2 1.5 1.1 1.4

Feedlot Phase 2.2 2.5 2.2 :.5 2.3 2.6 2.3 2.6 2. 2.6

is designed primarily to provide an overall comparison of forage and

feeding systems.

Acreage Requirements

A point often overlooked in discussions of beef production

efficiency is that larger cows require more land. The increase in

acreage requirements with cow size (table 22, Appendix A) was most

dramatic in cow-calf operations. At weaning, table 22 showed a 6% -

7% increase in acreage requirements for each 10% increase in cow size.

Milk yield also had an effect on acreage requirements. Increasing

milk yield caused a moderate increase in acreage requirements.

The primary analysis shown in table 22 assumed that fertility

levels varied with cow size and milk yield (table 9). To eliminate

fertility as a variable, model runs were made assuming a constant

pregnancy rate of 92% for all cow sizes and milk levels. This tech-

nique aids in interpreting the results. The above conclusions about

cow size and milk yield were also valid when fertility levels were

held constant (table 23, Appendix A).

The most dramatic change in acreage requirements occurred between

systems, especially for cow-calf operations. Though acreage require-

ments differed very little for Systems III, there was a significant

reduction in acreage requirements for Systems IV and V. These last

two systems included the production of large amounts of corn silage to

feed cattle. Since silage produces high levels of TDN per acre, this

reduction in acreage requirements was to be expected.

In determining acreage requirements at slaughter, it was assumed

that all feed, including grain, was grown by the herd owner. The

purchase of grain would, of course, reduce acreage requirements as

illustrated in table 10.


Pounds beef sold per acre

Cow size had no discernible effect on pounds of beef sold per

acre except for a slight increase at weaning time (table 24, Appendix

A). This increase at weaning was not noticeable when weaning rates were

held constant (table 25, Appendix A). The analysis in table 24 assumed

that the larger, less fertile cows were culled and sold when they failed

to re-breed. The increase in pounds of beef sold per acre at weaning

was due to the sale of a higher proportion of the larger cows.

Increasing milk yield tended to increase beef produced per acre

atweaning time. By slaughter, however, the inverse relationship was

true. Since calves from all milk levels at a given cow size were

assumed to gain at the same rate after weaning, the lighter calves

from the dams with lower milk levels had less body weight to maintain

than their heavier counterparts from the good milking dams. Thus the

gains of the lighter calves from weaning to slaughter were more


Systems IV and especially System V produced most beef per acre

because the predominant source of feed was corn silage. Of the

pasture systems, System II was slightly more productive than Systems

I and III.

Pounds TDN per pound beef sold

At weaning larger cow sizes resulted in a slight decrease in TDN

consumed per pound of beef produced (figure 6). At the end of the

stocker phase and at slaughter, however, those differences between

large and small cows disappeared.

Since nutrients are lost by cycling them through the cow to the

calf in the form of milk, many believe that more TDN is required per

unit of beef sold from heavy milking cows. Figure 6 showed exactly





Cow Size




Cow Size

Figure 6. Pounds TDN per pound of beef sold for four cow
milk levels. (Cow size: S=850 lbs, M=950 Ibs,
VL=1200 Ibs; Milk yield: open line=low, solid
Source: table 26, Appendix A.)

sizes and two
L=1050 Ibs,

the opposite to be true. (The same phenomenon occurred at uniform

weaning rates also.) There is an energy cost for maintaining a cow

before parturition. In this study the heavier milking cows produced

more pounds of calf at weaning to help pay for this pre-parturition

energy cost. However, there was more postweaning weight to maintain

at the same post-weaning gain levels. Thus the advantage for the

heavier milking cows disappeared by slaughter since post-weaning gains

of their calves were less efficient.

TDN per pound of beef sold decreased in Systems IV and V. These

two were more intensive than the more conventional pasture systems

(I-III). The average feed quality index (table 21, Appendix A) was

higher and the activity factor was lower, reducing the TDN requirements

for the two systems. In table 10, the pounds of TDN per animal and

TDN consumed by the herd were reduced in Systems IV and V for the same


While System V was consistently the most efficient system biolog-

ically, its TDN sources (primarily corn silage) were very expensive

compared to the conventional pasture systems. It was a uniformily

unprofitable method of beef production. Consequently, System V was

not included in the report of the economic analysis to follow.

Since cost and price levels are highly variable with time, all

economic components were indexed. The highest value of a given com-

ponent was assigned a value of 1.000. Thus, each component was

indexed against its highest value. This indexing technique makes the

data easier to interpret and should extend the time over which this

study will maintain its validity.

Cost Components

The range of values for several cost components is shown in table 11.

Cow maintenance costs and heifer maintenance costs were those deter-

mined by Model I, and used as input data for Model II. Gain costs were

also derived from Model I data. Cost per pound of TDN and cost per

pound of beef sold were computed by Model II.

Cost per pound TDN consumed

Cow size and milk level seemed to have little or no effect on cost

per pound of TDN consumed (table 27, Appendix A). The forage and

feeding system, however, had a sizable effect on cost per pound of TDN.

System II was the cheapest throughout. Inexpensive gains were

achieved by grazing stockers and replacement heifers on topseeded

Coastcross bermuda pasture which provided a very economical but high

quality source of TDN. For example, there was a 20% to 30% advantage

for System II stockers over System I stockers which grazed more expen-

sive summer and winter annuals on prepared seedbeds.

As expected, System IV had the highest unit TDN cost. Much of the

TDN for the cow-calf operation was supplied by expensive corn silage.

Cost per pound of beef sold

Cow size had little effect on cost per pound of beef sold except

at weaning. Here there was a small tendency toward increased costs

for small cows, primarily at lower milk levels (figure 7). Higher

milk levels tended to decrease costs per pound of beef produced,

especially in light cows. At uniform weaning rates (table 29) the de-

crease was also apparent in larger cows.

Cost per unit of beef produced was lowest in System II. System I

produced the next cheapest beef. System IV had the highest cost per

pound of beef produced.

Costs per pound of beef produced were affected very little by

weaning rate (tables 28 and 20, Appendix). This is not surprising since,







Stocker Phase
Feedlot Phase


To Weaning
To Feedlot
To Slaughter


At Weaning
At Feedlot
At Slaughter



High Low

118.79 83.51

High Low

118.79 83.41

High Low High

118.79 90.29 148.00

116.44 166.26 79.31 113.65 132.52 167.80 139.30 197.01





.2929 .1671 .2016
.5338 .4202 .5270







.3395 .4360 .3395 .4360







.0256 .0291

.0379 .0391

.2635 .2555 .2828

.3017 .3105 .3247




Cow Size



Cow Size

Figure 7. Indexed cost per pound of beef sold for four cow sizes and
two milk levels. (Cow size: S=850 lbs, M=950 Ibs, L=1050 Ibs,
VL=1200 Ibs; Milk yield: open line=low, solid line=high;
Source: table 28, Appendix A.)

in the herd management policies used in this study, non-pregnant cows

were sold as soon as they weaned their last calf. This policy produced

additional pounds of beef to substitute for the fewer pounds of calf

beef resulting from low fertility levels.

Profit Components

The beef producer usually will evaluate the success of his opera-

tion by its profitability. There are several ways to assess profit-

ability. The three components of profitability reported here include

net returns per 1000-cow herd, net returns per pound of beef sold, and

net returns per acre.

The ranges of values for each of these components are shown in table

12. The three different price structures (table 5) are included.

Returns per 1000-cow herd

Returns per 1000-cow herd are indexed in tables 30-32 (Appendix A).

In cow-calf operations (i.e., at weaning) this component tended to

increase as cow size increased, especially at low prices (table 31).

An exception was System IV where returns appeared to parallel fertility

levels. The high costs of cow maintenance and especially replacement

heifers maintenance offset the additional income due to size. By

slaughter time, however, there was no advantage for larger cows. Re-

turns tended-to parallel fertility levels.

Increasing milk yield increased net returns per 1000-cow herd at

weaning, especially in small cows and at low prices. At slaughter these

returns also tended to increase with higher milk yields in small cattle.

In large cattle, however, the returns declined slightly at slaughter

due to a decrease in fertility levels.

At both weaning and slaughter, System II with its low production

costs produced the highest net returns for a 1000-cow herd. System I



Low Hgh Low g Low High Low High



At Weaning 64660 110530 71930 124100 61510 110040 54420 93470
At Feedlot 139820 174460 161830 204830
At Slaughter 145970 174700 168980 204960 114930 140200 91540 123620


At Weaning .1759
At Feedlot .1833
At Slaughter .1678


At Weaning 58.39
At Feedlot 76.68
At Slaughter 74.32


At Weaning 25416
At Feedlet 109270
At Slaughter 145970


At Weaning .0691
At Feedlot .1466
At Slaughter .1673


At Weaning 22.95
At Feedlet 61.99
At Slaughter 74.3:


At Weaning 64660
At Feedlot 88900
At Slaughter 80100


At Weaning .1739
At Feedlot .1251
At Slaughter .0999


At Weaning 53.39
At Feedlot 52.19
At Slaughter 46.17

.2190 .1936 .2376 .1673 .2180
.2182 .2277 .2603
.1976 .2087 .2352 .1420 .1662

81.17 66.12 89.69. 35.14 80.20
91.65 9S.69 112.50
89.93 94.63 108.94 72.13 88.93


60343 32680 76650 22:60 59870
136670 132480 168180
174700 168980 205960 114930 140200

.1018 .0889 .1253 .0606 .1008
.1707 .1927 .2134
.1976 .2087 .2352 .1420 .1662

38.93 30.04 50.57 19.96 37.66
71.70 50.37 92.12
89.95 94.63 108.94 72.13 88.93


110530 71930 121100 61510 110040
111480 112920 14500
95520 105320 129950 33990 67400

.2190 .1956 .2376 .1673 .2150
.1390 .1694 .1821
.1080 .:412 .1456 .0765 .0791

81.17 66.12 89.69 55.14 80.20
58.41 73.44 78.53
32.09 65.64 70.22 46.52 32.93

.1256 .1832

.1063 .1333

7S.27 106.15

78.64 109.66

15180 34320

91540 1:3620

.0413 .0680

.1063 .1333

21.:9 3S.98

75.64 109.60

54420 93470

35240 31710

.1256 .1852

.0667 .0410

75.27 106.13

44.03 63.14

had the second highest returns followed by System III and then System


Net returns per pound of beef sold

Net returns per pound of beef sold are indexed in tables 33-35

(Appendix A). Any effect of cow size on these returns seemed to be

associated with the lower fertility of larger cows except when

weanling calf prices were low (table 34). Large cows showed an

advantage here only because cull cow prices were assumed to remain

at 334 per pound while calf prices dropped from 504 to 394 per

pound (table 5).

At weaning, higher milk yields resulted in increased returns per

pound of beef sold in Systems I through III. This was especially true

in smaller cows and at low cow prices. In System IV increased.milk

yield was an advantage for small cows but a disadvantage for larger

cows due to the substantial drop in fertility suffered by the larger


At slaughter, net returns per pound of beef sold declined as

milk yield increased. This decline appeared to be associated with

a corresponding decline in fertility.

System II showed the highest returns per pound of beef produced

at weaning and at slaughter. It was followed in rank by System I,

System III, and System IV. These systems ranked the same as they did

in net returns per 1000-cow herd and cost per pound of beef sold.

The spread between systems widened as the cattle got bigger and less

fertile. Remember that the cost per pound of beef produced (figure 7).

was about the same for both large and small cattle. Thus a herd which

produced many higher-priced calves and few cheaper cull cows would be

more profitable per unit of beef produced. The difference between systems


was also more pronounced at low prices.

Net returns per acre

Land is a major constraint for most beef producers. They have a

limited amount of land which can be devoted to beef production. Further-

more, land values have increased substantially in recent years. Con-

sequently, one of the most important measures of profitability for most

beef producers is net returns per acre. In assessing net returns per

acre, this study assumed that all feed, except minerals and protein

supplement, was produced on the ranch. Net returns per acre is shown

in figure 8 and indexed in tables 36 through 39 (Appendix A).

Examination of data for Systems I through III in figures 8 and 9

suggests that most differences between cow size and returns per acre

were due to fertility. In general there may have been a slight

advantage for the 950-pound cow. The small 850-pound cow also appear-

ed to be at a disadvantage at weaning. With low prices (table 38)

there was an advantage for larger cattle at weaning only, especially

in System II where heifer development costs were low. This advantage

for larger cattle at low prices occurred primarily because cull cow

prices were held at 334 while substantially lowering calf prices from

504 to 394 per pound.

In System IV where TDN costs were higher (table 27, Appendix A)

there was a disadvantage for larger cattle, even at low prices. Note

in figure 7 that System IV was the only system in which increasing

cow size beyond 950 pounds tended to increase cost per unit of beef


At weaning, there was an advantage for increased milk yield at any

price structure. The advantage was more pronounced at uniform weaning

rates (figure 9). Thus in the assumptions used in this study,



Cow Size



Cow Size

Figure 8. Indexed net returns per acre at high-high price structure
for four cow sizes and two milk levels. (Cow size: S=850
Ibs, M=950 Ibs, L=1050 Ibs, VL=1200 Ibs; Milk yield: open
line=low, solid line=high; Source: Table 36, Appendix A.)




Cow Size



Cow Size

Figure 9. Indexed net returns per acre at high-high price and uniform
weaning rate for four cow sizes and two milk levels. (Cow
size: S=850 Ibs/ M=950 Ibs, L=1050 Ibs, VL=1200 Ibs; Milk
yield: open line=low, solid line=high; Source: table 37
Appendix A.)


increasing milk yield even offset the effects of lowered fertility due

to higher milk yields.

At slaughter, however; the advantages of higher milk yield

disappeared. In fact, the slight differences tended to favor the

lighter milking cattle, especially in System IV. Most of the declines

due to increased milk yield resulted from the reduced fertility

assumed to be associated with a higher milk yield.

At weaning, with a uniform weaning rate (figure 9) System IV

had the highest net returns per acre. The advantage over other feeding

systems was greatest with heavy milking small cows and least with large

cows. When fertility levels were variable (figure 8) the larger, less

fertile cows in System IV lost their advantage to comparable cows in

System II.

At weaning, System II had an advantage over Systems I and III.

There was very little difference between Systems I and III.

With low prices at weaning, System IV maintained a slight advantage

over Systems I and III for 850- and 950-pound cows only. It lost its

advantages elsewhere. System II, with its low cost per pound of beef

sold (figure 7) always showed the highest net returns per acre at low

price (tables 38 and 39, Appendix A).

At the end of the stocker phase (i.e., at entrance to the feedlot]

System II had an 18% to 20% advantage over System I at all fertility

levels. This advantage was increased at low price levels-

At slaughter, Systems IV and II were very similar for 850 and 950-

pound cows at high price levels (figure 8). However, with larger cows

and especially with lower prices (table 39, Appendix A), System II had

the highest returns per acre. System II was always better than System

I and III by 20% to 30% -- mostly'due to cheap stocker gain. Systems I

and III were similar for all cows at low prices and for 850-and 950-cows

at high prices. System I had a slight advantage for 1050-and 1200-

pound cows at high prices.

In general, the systems ranked IV, II, I, III for net returns per

acre. System IV tended to lose its advantage to System II, especially

at slaughter, as cow size increased. This change in rank occurred

primarily because of the higher cost of maintaining a larger cow with

a lower fertility level on the expensive TDN of System IV.

Fertility, culling policy, and other factors

The effects of fertility and culling policy on production efficiency

and profitability were examined by holding cow size and milk level

constant. The assumptions of System I were applied to a 950-pound

cow giving 10 pounds of milk per day during the first month of lac-

tation. A 92% pregnancy rate was used as a standard against which to

compare other fertility levels and culling policies.

Pregnancy rate

The effects of reducing the pregnancy rate to 86% and 80% are shown

in table 13 (management factors B and C). Reducing pregnancy rate

reduced acreage requirements per 1000-cow herd since there were fewer

cows to maintain after weaning time (all open cows were culled at wean-

ing) and also fewer weaned calves to feed. Thus, within the limited

pregnancy rates studied here, beef production per acre actually in-

creased due to the sale of a larger number of heavy cull cows.

While the biological components appeared to favor decreased preg-

nancy rates, the opposite was true for the economic components. Costs

per pound of beef produced increased and net returns per acre decreased

as pregnancy rate dropped. Reducing the pregnancy rate from 92% to

80% reduced net returns per acre by 17.5% at weaning and 13.7% at


\. Standard System. 92%

B. .Decrease Pregnancy to 8616

C. Decrease Pregnancy to 0';

0. Cuil Open Cows After Calv-
Ing Season Instead of at

E. Cull Open Cows After
Calving Season Instead of
at Weaning; 830 Pregnancy

F. Cull 150 of Cor Herd
Instead of all Open
Cows; 80. Pregnancy
G. Cull 135 of Cow Herd
Instead of all Open
Cows; SO Prergancy

H. Cull 15% of Cow i'erd
Instead of all Open Cows;
86% Pregnancy Rate; 3%
Increase in Cow Death

1. Increase Slaughter Price
by 25c; Stocker Price by

J. Increase Slaughter Price by
S;; Stocker Price by 3O

K. Include $45.000 Overhead
Expenses in Costs


Acres/1000 Cows
Seef/Acre (Ibs)
Cost/Lb ($)
Profit/Acre ($)

Acres/1000 Cows
Beef/Acre (Ibs)
Cost/Lb (5)
Profit/Acre ($)

Acres/1000 Cows
Seef!Acre (lbs)
Cost/Lb ($)
Profit/Acre (3)

Acres/1000 Cows
8eef/Acre (lbse
Cost/Lb (S)
Profit/Acre (S)

Acres/1300 Cows
Beef/Acre 1lbs)
Cost/Lb (0)
Profit/Acre (S)

Acres/1000 Cows
Beef/Acre (Ibs)
Cost/Lb (5)
Profit/Acre (5)
Acres/l10O Cows
Beef/Acre (lbs)
Cost/Lb ($)
Profit/Acre (5)

Acres/1000 Cows
Beef/Acre (Ibs)
Cost/Lb (S)
Profit/Acre (S)

Acres/1000 Cows
8eef/Acre (Ibs)
.Cost/Lb ($)
Profit/Acre ($)

Acres/1000 Cows
Beef/Acre (1bs)
Cost/Lb ()
Profit/Acre ($)

Acres/1000 Cows
Beef/lcre (Ibs)
Cost/Lb (S)
Profit/Acre (S)

At wearing At feedlot At Slaughter

1306.8(l.0 00?173.1(.CCO0) 2092.4(1.000)
361.4(1.000) 417.S(1.0001 418.3(1.000)
.2233(1.000) .2463;1.000) .2714(1.0001
76.44(1.000) 84.25(1.000) 58.45(1.000)

1278.5(0.978) 1748.3(0.933) 1930.5(0.923)
371.2(1.027) 418.7(1.002) 419.4(1.001)
.2324(1.118) .2469(1.002) .2694(0.993)
69.BS(0.914) 78.59(0.033) 82.90(0.937)

1250.2(0.9S7) 1623.9(0.S67) 1769.3(0.845)
381.3(1.053) 419.7(1.005) 420.3(1.003)
.2363(1.034) .2477(1.006) .;670(0.034)
63.03(0.825) 71.06(0.885) 76.33(0.863)

1391.4(1.063) 1957.(l1.J45) 2177.1(1.040)
3.s9.4(0.939) 399.8k0.557) 402.3(0.961)
.2410(1.056) .2540(1.031) .2732(1.023)
67.48(0.383) 77.53(0.920) 32.26(0.030)

1411.5(1.080) 1735.1(0.953) 1929.7(0.922)
337.8(0.035) 381.8(0.914) 383.1(0.920)
.2604(1.141) .2644(1.073) .2624(1.041)
47.74(0.625) 59.13(0.702) 64.04(0.720)

1487.6(1.138) 02:S.3(1.033) 2237.7(1.069)
291.6(0.807) 359.9(0.561) 366.2(0.034)
.2735(1.193) .2736(1.110) .2961(1.091)
49.7710.651) 63.77(0.757) 69.43(0.785)
1487.6(1.138) 1980.3(1.037) 2171.3(1.038)
274.3(0.739) 342.3(0.820) 349.3(0.S35)
.2907(1.273) .2839(1.153) .3050(1.124).
41.11(0.538) 56.34(0.669) 62.31(0.704)

1513.2(1.159) 2023.2(1.083) 2227.6(1.065)
277.7(0.768) 346.3(0.329) 353.5(0.844)
.2922(1.280) .2848(1.156) .3060(1.127)
41.66(0.545) 37.04(0.677) 63.36(0.716)

1306.8(1.000) 1373.1(1.000) 2097.4(1.000)
361.4(1.000) 417.3(1.000) 318.9(1.000)
.2293(1.000) .2463(1.000) .2714(1.000)
76.44(1.000) 87.34(1.039) 96.92(1.096)

1306.8(1.000) 1373.1(1.000) 2092.4(1.000)
361.4(1.000) 417.3(1.000) 418.8(1.000)
.2283(1.000) .2463(1.000) .2714(1.000)
76.44(1.000) 94.11(1.117) 105.39(1.192)

1306.8(1.000) 1873.1(1.000) 2092.4(1.000)
361.4(1.000) 417.8(1.000) 418.8(1.000)
.3236(1.417) .3038(1.233) .3227(1.190)
42.00(0.349) 60.23(0.715) 67.75(0.756)

aValues in parentheses are indexed against standard system, Factor A.



Culling practices

Management factors A, B, and C assumed that all non-pregnant cows

were culled as soon as their last calf was weaned. This practice would

entail pregnancy testing cattle at weaning time. Many producers do

not perform this test but may cull non-pregnant cattle as soon as they

are identified at the end of the calving season. This would result in

non-pregnant cows being maintained for approximately 6 months after

calving, as is assumed for management factors D and E. By comparing

factors D and E to their counterparts, A and C, the effects of delayed

culling can be assessed.

Delaying the culling of open cows for 6 months increased acreage

requirements and reduced beef production per acre. Costs per pound of

beef produced rose and net returns per acre were reduced. Where preg-

nancy rate was maintained at 92%, failure to remove open cows until

6 months after weaning reduced net returns per acre by 11.7% at

weaning. The reduction was even more drastic at the 80% pregnancy rate.

Another common practice among beef producers is to cull a certain

proportion of the cow herd regardless of fertility status and calving

history. Usually no production records are kept in such herds. Thus

open cows may remain in the herd for an entire year or more without

weaning a calf. Management factors F, G, and H reflect such manage-

ment practices. Here open cattle were assumed to remain in the herd

for one year after weaning their last calf. Each year 15% of the cow

herd was culled regardless of fertility status.

Comparing management factors F and G to their counterparts B and C,

there was a significant increase in acreage requirements per 1000-cow

herd and a reduction in beef produced per acre. At weaning, costs per

pound of beef rose by 18% to 24%. Net returns per acre were drastically

reduced. Factor G with an 80% pregnancy rate was 46.2% less profit-

able than A, at weaning, compared with only a 17.5% reduction for C,

where the pregnancy rate was also 80% but culling was practiced as

soon as an open cow weaned her last calf.

The culling of only 15% of the herd annually may result in an

increase in death loss as old cows are over-looked at culling time.

The effect of increasing the death loss rate from 2% to 5% is shown in

management factor H. The increase in acreage requirements at weaning

occurred because the program allotted additional acreage for the grow-

ing of replacement heifers to replace dead cows. Note that the addi-

tional death losses resulted in a substantial reduction in net returns

per acre.

The Beef Research Unit data discussed previously suggested that

carcass quality may affect profitability. Since increasing carcass

quality presumably has no effect on production costs, the improved

carcass would obviously increase profit if this quality were rewarded

by the markets. Factors H and I represent an increased animal value,

such as might occur with increased carcass quality or yield grade.

A 5% increase in slaughter price (factor I) resulted in a 9.6% increase

in net returns per acre, while 10% increase in slaughter price yielded

a 19.2% increase in net. returns per acre at slaughter. Naturally, the

effect of this increase in slaughter price will depend on the profit

margin. The smaller the profit margin, the greater the percent increase

in profit.

Table 40 lists overhead items and fixed expenses which might

be common to a 1000-cow ranching operation. These items had been

omitted in this study since they can vary greatly from ranch to ranch

and because it was not necessary to include them for the comparisons

made here. The effects of their inclusion, however, are illustrated

in management factor K. For a cow-calf operation the overhead items

in table 40 would increase cost per pound of beef produced by 41.7%

and reduce returns per acre by 45.1%. If they represented the over-

head costs of a conception to slaughter ranching operation, cost per

pound would be increased by 19.0% and net returns per acre would be

reduced 23.4% by their inclusion in the analysis.

Factors Affecting Biological Efficiency

Cow size

Except for the increase in acreage requirements, there were no

substantial effects on biological efficiency with changes in cow size.

Beef produced per acre and TDN per unit of beef produced were affected

very little by changes in cow size.

Milk yield

Increasing milk yield resulted in a moderate increase in acreage

requirements and an increase in beef produced per acre at weaning,

Because the calves from heavy milking cows were larger at weaning,

they tended to gain less efficiently from weaning to slaughter. Con-

sequently, by slaughter, beef produced per acre was slightly decreased

and TDN per unit of beef produced was increased for herds with

heavier milking dams.

An important point concerning the effects of milk yield on bio-

logical efficiency emerges from an examination of the data on TDN per

unit of beef produced at weaning. Contrary to popular belief, TDN per

unit of beef decreased as milk yield increased. The heavier milking

cow weaned a heavier calf. Thus, for her production year, which ended

at weaning, the heavy milking cow had more pounds of calf to offset

her pre-parturition TDN costs.


In this study, all non-pregnant cows were culled at the very

beginning of the production year, immediately after they had weaned

their previous year's calf. A heifer calf was kept to replace each

culled cow. Because of this management practice, acreage requirements

were reduced and beef production per acre increased slightly as weaning

rate declined (table 13). However, if open cows.were allowed to

remain in the herd after weaning their last calf, acreage requirements

increased and beef production per acre decreased as fertility declined.

Forage and feeding systems

Table 14 summarizes the rankings of the five forage and feeding

systems for efficiency. System V was consistently the most efficient

system biologically. It was always followed-in rank by System IV.

All of the TDN for System V was produced.by corn or corn silage. Much

of the TDN from System IV came from the same sources. Corn produces

a high yield of TDN per acre. Consequently, it is not surprising that

acreage requirements were low and beef production per acre was high in

these two systems.

TDN was also utilized more efficiently in these two systems .as

shown by the data on TDN per pound of beef produced. Corn and corn

silage have high feed quality indices, meaning that they are converted

to net energy more efficiently. Furthermore, animals in Systems IV

and V were more confined, requiring less energy for incidental activity.

Factors Affecting Profitability

Cow size

In general, this study consistently indicated that cow size alone.

had little or no effect on profitability. The exception was returns

per 1000-cow herd, which is probably not a practical measure of profit-

ability. As cow size increased returns per 1000-cow herd increased,

while returns per pound of beef and returns per acre remained about

constant. Any differences in the latter two can be explained by

differences in fertility associated with cow size.

Milk yield

Increasing milk yield always decreased costs and increased returns

at weaning. Generally the decline in fertility assumed to be associated

with increased milk yield was offset so that there was a net advantage

at weaning for increased milk yield. Excessive drops in fertility

would, of course, negate this advantage.

The advantage for increased.milk yield did not persist for the

herd in which calves were maintained until they were ready for

slaughter. Calves from heavy milking cows weighed more at weaning.

Since they were assumed to gain at the same rate as their smaller

counterparts from light milking cows of the same weight, these heavier

calves did not gain as efficiently.

These results point out a well recognized discrepancy between the

cow-calf producer and operator who grows out the calves. Because

of increased feed efficiency and compensatory growth, the calf grower,

under favorable feed price conditions, generally prefers the lighter

calves. However, heavy calves are more profitable for the cow-calf

producer. This study suggests that if a producer intends to maintain

his calves through a stocker phase or until slaughter, he might strive

for a moderate level of milk production in his brood cow herd.


Fertility is without doubt the major factor determining the profit-

ability of beef production. In fact, it was the only animal production



System Number and Feed Type

Life Stage I II III IV V
Cow-calf Pasture Pasture Pasture & Drylot Drylot
Stocker Annual Permanent -- -- -
Forage Forage
Finishing Feedlot Feedlot .Feedlot Feedlot Feedlot

(Highest = 1)

Biological Components

Requirements 1 3 2 4 5

Lb Beef/Acre 5 3 4 2 1

Beef 2 1 3 4 5

Cost Components

Cost/Lb TDN 3 4 2 1 a/

Cost/Lb Beef
Sold 3 4 2 1 a/

Profit Components

Cows 2 1 3 4 a/

Beef Sold 2 1 3 4 a/

Returns/Acre 3 2b/ 4 1 a/

low, and at slaughter if

a/System V always unprofitable; not ranked.
b/System II ranks first at weaning if prices are
prices are low or cows are large.

character examined in this study which consistently showed a substantial

effect on profitability. Increasing fertility always increased profit-


Culling and management policies

In table 13 culling policies were shown to have a dramatic effect

on profitability. It is very important to pregnancy test brood cows

at weaning time, to cull them from the herd immediately, and to

replace them with a heifer. This practice avoids a winter feed bill

for a non-productive cow, reduces production costs, and generates income

from the sale of a large animal. The practice is especially important

in herds with low fertility levels. Much of the profit reducing

effect of lowered fertility can be offset by culling open cows at

weaning time.

Forage and feeding system

Forage and feeding systems were major factors influencing profit-

ability. (See table 14 for a summary of feeding systems.) System II,

which included a topseed permanent pasture for growing out calves,

produced the cheapest beef and had the highest returns per unit of

beef sold. However, System IV, in which cows were stocked at 1.67

animals per acre and supplemented with corn silage, usually produced

the highest returns per acre unless cattle prices or fertility levels

were low. Smaller cows with low maintenance requirements did well

in System IV, particularly if calves are maintained until slaughter.

System IV was more sensitive to cow size than System II, especially at


This study suggests that Systems II and IV might be advantageous

production systems for beef producers. Thus far, it appears that the

use of similar systems has been limited to university experiment station

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