BEEF CATTLE MANAGEMENT SYSTEMS
FOR THE SOUTHEAST: AN APPLICATION OF COMPUTER MODELING
HINES FINLAYSON BOYD
A DISSERTATION PRESENTED TO THE GRADUATE COUNCIL OF
THE UNIVERSITY OF FLORIDA
IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE
DEGREE OF DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
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
TABLE OF CONTENTS
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
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
IV ANALYSIS OF BEEF RESEARCH UNIT DATA.FROM FIVE
BREED GROUPS ........................................... 44
Beef Research Unit Data and Assunptions........... 44
Results of Beef Research Unit Analysis............ 49
Biological components.............. 49
Economic components................ 49
V ANALYSIS OF BEEF CATTLE MANAGEMENT SYSTEMS FOR THE
COASTAL PLAINS ......................................... 53
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
Forage and feeding systems........... 86
Factors Affecting Profitability ..................... 86
Cow size............................. 86
Milk yield........................... 87
Culling and management practices..... 89
Forage and feeding systems........... 89
VI RESEARCH RECOMMENDATIONS AND APPLICATIONS OF RESULTS.... 91
Recommendations for Additional Research ............. 91
Applications of Results............................. 92
VII SUMMARY AND CONCLUSIONS................................. 95
APPENDIX A............................................. 100
APPENDIX B........................... ................... 123
BIOGRAPHICAL SKETCH.............; ....................... 141
LIST OF TABLES
1 MILK YIELD FACTOR......... .............................. 27
2 ASSUMED RELATIONSHIPS BETWEEN FEED QUALITY INDEX AND
RATION QUALITY. ........................................ 33
3 PRODUCTION RATE AND COST SUMMARY FOR PASTURES AND CROPS. 40
4 NON-FEED VARIABLE COSTS. (S/YEAR)....................... 41
5 CATTLE PRICE STRUCTURE AND PRICE ASSUMPTIONS............ 42
6 ANIMAL PRODUCTION CHARACTERISTICS AND COST-PRICE
ASSUMPTIONS, BEEF RESEARCH UNIT DATA ................... 48
7 MEASURES OF PRODUCTION EFFICIENCY, BIOLOGICAL
COMPONENTS, BEEF RESEARCH UNIT DATA ..................... 50
8 MEASURES OF PRODUCTION EFFICIENCY, ECONOMIC
COMPONENTS, BEEF RESEARCH UNIT DATA. ($)................ 51
9 PRODUCTION CHARACTERISTICS OF COWS AND CALVES,
COASTAL PLAINS DATA ..................................... 58
10 VALUE RANGES FOR FIVE SYSTEMS, BIOLOGICAL COMPONENTS.... 66
11 VALUE RANGES FOR FOUR SYSTEMS, COST COMPONENTS.......... 72
12 VALUE RANGES FOR FOUR SYSTEMS,. PROFIT COMPONENTS......... 75
13 FACTORS AFFECTING PRODUCTION EFFICIENCY AND
PROFITABILITY, UNIFORM COW.SIZE AND MILK LEVEL.......... 82
14 SUMMARY OF FORAGE AND FEED SYSTEM RANK FOR EFFICIENCY
COMPONENTS.......... ................................... 100
15 PASTURE BUDGET: CLOVER-GRASS.......................... 100
16 PASTURE BUDGET: RYEGRASS-CLOVER-COASTCROSS BERMUDA.... 101
17 PASTURE BUDGET: RYE-RYEGRASS-CRIMSON CLOVER........... 101
18 PASTURE BUDGET: MILLET.................. ............. 101
19 RATION COMPOSITION AND COSTS........................... 102
20 BREEDING COSTS......................................... 102
21 ASSUMPTIONS USED IN ANALYSIS OF COASTAL PLAINS
SYSTEMS ................................................ 103
22 ACREAGE REQUIREMENTS, 1000 BROOD COW HERD.............. 104
23 ACREAGE REQUIREMENTS, 1000 BROOD COW HERD, UNIFORM
WEANING RATE .......................................... 105
24 POUNDS BEEF SOLD PER ACRE.............................. 106
25 POUNDS BEEF SOLD PER ACRE. UNIFORM WEANING RATE....... 107
26 POUNDS TDN PER POUND BEEF SOLD......................... 108
27 INDEXED COST PER POUND TDN CONSUMED.................. 109
28 INDEXED COST PER POUND BEEF SOLD...................... 110
29 INDEXED COST PER POUND BEEF SOLD. UNIFORM WEANING
RATE.............. ..................................... ll
30 INDEXED NET RETURNS PER 1000 BROOD COW HERD, HIGH-
HIGH PRICE STRUCTURE................................... 112
31 INDEXED NET RETURNS PER 1000 BROOD COW HERD, LOW-
HIGH PRICE STRUCTURE.. ....................... ..... .. 113
32 INDEXED NET RETURNS PER 1000 BROOD COW HERD, HIGH-
LOW PRICE STRUCTURE.......... .......................... 114
33. INDEXED NET RETURNS PER POUND BEEF SOLD, HIGH-HIGH
PRICE STRUCTURE......................................... 115
34 INDEXED NET RETURNS PER POUND BEEF SOLD, LOW-HIGH
PRICE STRUCTURE........................................ 116
35 INDEXED NET RETURNS PER POUND BEEF SOLD, HIGH-LOW
PRICE STRUCTURE........................................ 117
36 INDEXED NET RETURNS PER ACRE, HIGH-HIGH PRICE
37 INDEXED NET RETURNS PER ACRE, UNIFORM WEANING RATE,
HIGH-HIGH PRICE STRUCTURE.............................. 119
38 INDEXED NET RETURNS PER ACRE, LOW-HIGH PRICE
STRUCTURE................ ............................. 120
39 INDEXED NET RETURNS PER ACRE, HIGH-LOW PRICE
STRUCTURE............ ................................ 121
40 BUDGET: OVERHEAD AND FIXED EXPENSES FOR 1000 BROOD
COW OPERATION... ......... ............................ 122
LIST OF FIGURES
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
BEEF CATTLE MANAGEMENT SYSTEMS
FOR THE SOUTHEAST: AN APPLICATION OF COMPUTER MODELING
HINES FINLAYSON BOYD
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:
III. Individual animal
IV. Sub-systems of individual animals (e.g. digestive 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.
REVIEW OF LITERATURE
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
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.
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
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
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
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.
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
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.
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
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
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
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.
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
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-
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=(MCW X PMCW X .01) + CGk) X CWFk
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
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:
SDMY =DMYFM X MYFk
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
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.
TABLE 1. MILK YIELD FACTOR.
Month of Lactation Milk yield factor1
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
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=DMY X 0.165 X EFMP
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.
TABLE 2. ASSUMED RELATIONSHIPS BETWEEN FEED QUALITY INDEX AND RATION
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:
TDNCOW=TDNMCW + TDMGCW + TDNMP
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:
TDNCLF=TDNMCLF + TDNGCLF
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
NETTDN=TDNCOW + TDNCLF MILKTDN N
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=AUMk X TDN/AUM X PSRk
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:
SUPPLY =NETTDNk PTDNk
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.
COWSk=COWS. + BRTH. CULLS. CD.
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.
CULLS=COWS X (100-WR-CONCR) X .01
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:
Y- BRTH =RHK.=CULLS. + CD. + BRD.
RHK. is the replacement heifers kept during the previous or the
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
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
TABLE 3. PRODUCTION RATE AND COST SUMMARY FOR PASTURES AND CROPS
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
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.
TABLE 4. NON-FEED VARIABLE COSTS ($/YEAR).
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
TOTAL NON-FEED COSTS
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.
TABLE 5. CATTLE PRICE STRUCTURE AND PRICE ASSUMPTIONS.
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.)
of TDN for use in subsequent models to.compare animals of different
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
ANALYSIS OF BEEF RESEARCH UNIT DATA FROM
FIVE BREED GROUPS
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,
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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sity of Florida Beef Research Unit. Table 6 shows the data used in the
Results of Beef Research Unit Analysis
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".
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.
ANALYSIS OF BEEF CATTLE MANAGEMENT SYSTEMS
FOR THE COASTAL PLAINS
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
u w =
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.^ 0 J
8 i ^
z z H
= s "
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.
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.
TABLE 9. PRODUCTION CHARACTERISTICS OF COWS AND CALVES, COASTAL
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.
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.
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 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.
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-
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.
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.
-- -- High-High Price Structure
---- High-Low Price Structure
.1.0 ---- Low-High Price Structure
Cost tf Gain
200 400 600 800 1000 120
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
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
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
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.
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
TABLE 10. VALUE RANGES FOR FIVE SYSTEMS, BIOLOGICAL COMPONENTS.
1 I1 II1 IV V
Low Hiah Low High Low High Low High Low High
CALF WEIGHTS (L8S)
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
TDN/L BEEF PRODUCED (LBS)
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
TDN CONSUMED BY HERD (TONS)
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
ACRES/1000 COW HERD
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
LBS SEEF SOLD/ACRE
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
CALF GAINS (LBS/DAY)
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
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
I II III IV V
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
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.
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,
TABLE 11. VALUE RANGES FOR FOUR SYSTEMS, COST COMPONENTS.
GAIN COSTS ($/LB)
COST/LB TDN ($)
COST/LB BEEF SOLD
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
.2635 .2555 .2828
.3017 .3105 .3247
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.
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
TABLE 12. VALUE RANGES FOR FOUR SYSTEMS, PROFIT COMPONENTS.
I II III IV
Low Hgh Low g Low High Low High
(HIGH-HIGH PRICE STRUCTURE)
NET RETURNS/1000 COW HERD
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
NET RETURS/LB BEEF SOLD
At Weaning .1759
At Feedlot .1833
At Slaughter .1678
At Weaning 58.39
At Feedlot 76.68
At Slaughter 74.32
NET RETURNS/1000 COW HERD
At Weaning 25416
At Feedlet 109270
At Slaughter 145970
NET RETURNS/LS BEEF SOLD
At Weaning .0691
At Feedlot .1466
At Slaughter .1673
At Weaning 22.95
At Feedlet 61.99
At Slaughter 74.3:
NET RETuRNS/1000 COW HERD
At Weaning 64660
At Feedlot 88900
At Slaughter 80100
NET RETURNS/L3 BEEF SOLD
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
(LDW-HIGH PRICE STRUCTURE)
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
(HIGH-LO PRICE STRUCTURE)
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
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,
S M LVL S M LVL S M L VL S M LVL
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.)
I II III IV
S M LVL S M L VL S M L VL SM L VL
S M L VL S ML VL S M LVL S M L VL
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
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
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.
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
TABLE 13. FACTORS 4AFFCTING PRODUCTION EFFICIENCY AND P?0'I-TABILITY, UNIFOP'l COW SIZE ,Do
\. 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
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.
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
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
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
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.
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
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.
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
TABLE 14. SUMMARY OF FORAGE AND FEED SYSTEM RANK
System Number and Feed Type
Life Stage I II III IV V
Cow-calf Pasture Pasture Pasture & Drylot Drylot
Stocker Annual Permanent -- -- -
Finishing Feedlot Feedlot .Feedlot Feedlot Feedlot
(Highest = 1)
Requirements 1 3 2 4 5
Lb Beef/Acre 5 3 4 2 1
Beef 2 1 3 4 5
Cost/Lb TDN 3 4 2 1 a/
Sold 3 4 2 1 a/
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
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