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Ribeye area as an indicator of muscling in beef cattle

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Ribeye area as an indicator of muscling in beef cattle
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Huffman, Randall Dale, 1964-
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English
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vii, 101 leaves : ill. ; 29 cm.

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Beef ( jstor )
Breeding ( jstor )
Calves ( jstor )
Cattle ( jstor )
Fat thickness ( jstor )
Fats ( jstor )
Heifers ( jstor )
Regression coefficients ( jstor )
Steers ( jstor )
Ultrasonography ( jstor )
Animal Science thesis Ph. D
Beef cattle -- Anatomy ( lcsh )
Dissertations, Academic -- Animal Science -- UF
Muscles ( lcsh )
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bibliography ( marcgt )
non-fiction ( marcgt )

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Thesis:
Thesis (Ph. D.)--University of Florida, 1991.
Bibliography:
Includes bibliographical references (leaves 95-100).
General Note:
Typescript.
General Note:
Vita.
Statement of Responsibility:
by Randall Dale Huffman.

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University of Florida
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Copyright [name of dissertation author]. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
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AA00004750_00001 ( sobekcm )

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RIBEYE AREA AS AN INDICATOR OF MUSCLING IN BEEF CATTLE


By

RANDALL DALE HUFFMAN

















A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA


1991













ACKNOWLEDGEMENTS


I would like to express sincere gratitude to Dr. Roger West, chairman, and

Dr. Dwain Johnson, Dr. Don Hargrove, and Dr. Ramon Littell, members of my

supervisory committee, for their guidance and assistance throughout my graduate

program and in the preparation of this manuscript.

I also extend appreciation to Dr. Fred Leak, Dr. Tim Marshall, Dr.

Saundra TenBroeck, Dr. David Prichard and Mr. Don Wakeman for their

assistance, suggestions, and friendship during my graduate program.

There are numerous people who assisted in all phases of my graduate

program: Mr. Larry Eubanks and the crew of the Meat Laboratory; Jerry Wasdin

and the crew at the Pine Acres Research Unit; Janet Eastridge, Debbie Neubauer,

and Ana Zometa of the Meat Science Laboratory; and Mary Beth Forte,

secretary. My sincere thanks goes out to these individuals for their extensive

assistance in data collection and preparation.

Special thanks are expressed to fellow graduate students too numerous to

mention individually--you know who you are! I am indebted for your friendship,

support, and assistance throughout my five years at the University of Florida. I

will always have many fond memories of UF because of you.







I am sincerely grateful to my parents, JoAnn and Dale, who were the most

influential forces in my pursuit of this degree. I probably would have stopped

short of this degree if it weren't for them. For that encouragement and support I

will be forever endebted. I am also thankful to my two very supportive sisters,

Shari and Emily, and my brother-in-law Dennis.

Finally, I express my deepest gratitude to Laura, my wife, for believing in

me and not giving up.













TABLE OF CONTENTS



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

ABSTRACT ................................................. vi

CHAPTERS

1 INTRODUCTION ...................................... 1

2 THE RELATIONSHIP OF RIBEYE AREA TO MUSCLE-TO-
BONE RATIO, LEAN PERCENTAGE AND RETAIL YIELD
AT DIFFERENT FAT TRIM LEVELS ...................... 9

Introduction ........................................... 9
M materials and Methods .................................. 12
Carcass Selection ................................... 12
Carcass Fabrication ................................. 14
Statistical Analysis .................................. 17
Results and Discussion .................................. 18
Im plications .......................................... 35

3 RIBEYE AREA AND FAT THICKNESS GROWTH DURING
THE EARLY LIFE OF BEEF CALVES .................... 38

Introduction .......................................... 38
Materials and Methods .................................. 41
Experimental Procedure ............................. 41
Statistical Analysis .................................. 45
Results and Discussion .................................. 46
Sex Condition ..................................... 49
Fram e Size ....................................... 63
Breed Group ...................................... 73
Im plications .......................................... 91

4 SUMMARY AND CONCLUSIONS ........................ 92







REFERENCE LIST ..................................... 95

BIOGRAPHICAL SKETCH .............................. 101













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

RIBEYE AREA AS AN INDICATOR OF MUSCLING
IN BEEF CATTLE

By

Randall Dale Huffman

December, 1991

Chairperson: Roger L West
Major Department: Animal Science

This study was undertaken to assess the usefulness of ribeye area (REA) as

a measurement of muscularity in beef cattle and to monitor growth of REA over

time. The first study utilized 54 steers selected to represent six, 22 kg carcass

weight ranges and three REA ranges. Cutability end points were defined as retail

yield at 2.54, .64, and 0 cm fat trim, muscle/bone ratio, fat-free muscle/bone ratio,

and separable lean. Significant correlations existed between REA and carcass

cutability. REA alone explained from 12% to 20% of the variation in cutability.

REA, plus the other yield grade variables, explained from 28% to 38% of the

variation in carcass cutability, depending on the cutability end point. Although not

different (P>.05), carcasses classified as "average," "above average," or "below

average" for REA did show a trend for "above average" carcasses to have greater

cutability than "below average" carcasses. In stepwise regression with other







carcass measurements and some individual muscle and bone weights, REA was

included in all equations predicting cutability (R2=.53 to R2=.65). Part two of

this study provided a look at cattle growth from a very young age to slaughter.

Serial measurements of weight, ultrasound REA and fat thickness, and REA / 45.4

kg of live weight (REACWT) were regressed on age, and growth coefficients were

evaluated. This study suggested that when evaluating growth preweaning, cattle of

different sex condition should be evaluated separately. Frame size played a role

in preweaning growth, as larger framed cattle had faster weight gain and REA

growth than small frame cattle; however, REACWT was not different among

frame sizes. Cattle of predominantly Angus breeding (80% to 100%) had slower

(P<.05) weight gain and REA growth to weaning than did breed groups

comprised of 20% to 100% Brahman breeding. Breed groups were not different

(P>.05) for REACWT. This suggests that for evaluating REA in cattle up to

weaning, REACWT may be a valid variable to utilize across frame sizes and breed

groups. Postweaning, REA growth was not different among frame sizes or breed

groups. In conclusion, REA is moderately associated with cutability, and REA on

a relative live weight basis is the best method to assess REA growth.













CHAPTER 1
INTRODUCTION



Animals of all species vary considerably in composition as a result of their

stage of growth, nutritional history, and genetic base (Topel and Kauffman, 1988).

This variation in carcass composition provides a challenge for animal scientists

and livestock producers to identify those animals which will produce the most

"optimum" carcass composition. But how is "optimum" composition defined?

Traditionally, the U.S. beef industry has relied on a strong market for high quality

(high fat) beef, and this has helped to define "optimum" carcass composition.

During the last decade, the link between diet, maintenance of health and the

development of chronic disease has become increasingly questioned. Advice from

national health organizations has influenced consumers to modify their diets by

decreasing consumption of excess calories, fat, saturated fatty acids, and

cholesterol (Call, 1988). Consumers became more health conscious and promptly

demanded leaner meat products, thus modifying the definition of "optimum"

carcass composition. In addition to consumer demands for more healthful meat

products, the 1990s appear to be the decade of environmental awareness, where

the industry will be forced to improve efficiency and eliminate unnecessary waste.

Although this is not a major concern to the livestock and meat industry yet,









animal agriculture will eventually feel pressure from concerned consumers and

will have to respond by producing animals more economically and more efficiently

than ever before. Many management practices influence the efficiency of animal

growth and there is much room for improvement. Currently, the beef industry

produces more than 5 billion pounds of waste fat trim annually (Byers et al.,

1988). To address this wastefulness and to become more economically efficient,

the industry may again be forced to redefine "optimum" carcass composition.

May (1985) reported that from 1980 to 1984 the percentage of USDA

Yield Grade 1 and 2 beef carcasses increased (30.6% to 45.3%), while the

percentage of USDA Yield Grade 3, 4, and 5 beef carcasses decreased (69.4% to

54.6%). This trend probably continued through the late 1980s as well. Topel

(1986) projected that the ideal carcass in the year 2000 will have the following

characteristics: weight, 320 kg; age, 20 mo; muscle percentage, 73; ribeye area, 97

cm2; fat thickness at the 12th rib, .25 cm; percentage kidney pelvic and heart fat, 1;

and marbling score, practically devoid. Some meat scientists may disagree with

these predictions; however, changes must occur or the livestock and meat industry

will eventually lose market share to competing protein sources. Current trends

and predictions emphasize the need for accurate and precise methods to identify

animal and carcass composition, so that the ever-changing definition of "optimum"

carcass composition will be better understood. Because carcass composition

continues to be an area of interest, so too do the methods used to determine

composition. The most accurate method of determining carcass composition







3
would be to conduct a chemical analysis of the whole carcass (Hankins and Howe,

1946). Obviously this method has many drawbacks and is not applicable to an

industry situation. Consequently, much research has been done to develop

simplified techniques that are accurate and reliable across large groups of animals

and that can be applied to industry situations. Many techniques have been

described which involve chemical analysis of part of the carcass, which render

them impractical for today's high-speed beef slaughter plants (Griffin et al., 1989).

Therefore, methods that can predict carcass composition without destroying the

carcass have been widely studied. One such technique was adopted in 1965 by

USDA and is currently the basis for USDA Yield Grades for Beef. This

technique was developed by Murphey et al. (1960) and was designed to predict

the percentage of boneless retail cuts from the round, loin, rib, and chuck from

162 carcasses using the following equation: % boneless retail cuts = 51.34 5.78

(fat thickness, in.) .462 (% kidney, pelvic, and heart fat) .0093 (carcass weight,

lb) + .74 (ribeye area, sq. in.). The simple correlation coefficient between the

actual and the predicted yields were highly significant (r = .91). This original

equation has been modified slightly (USDA, 1965) and has been reevaluated by

many other researchers (Abraham et al., 1968; Brackelsberg and Willham, 1968;

Cross et al., 1973; Powell and Huffman, 1973; Abraham et al., 1980). All of these

researchers found the factors utilized in the USDA Yield Grade equation to be

useful predictors of carcass composition; however, numerous published reports

dispute the usefulness of ribeye area in equations that predict cutability. Cole et









al. (1960) found that ribeye area only accounted for 18% of the variation in

separable carcass lean and that carcass weight alone was more useful in predicting

separable carcass lean than the multiple regression including both carcass weight

and ribeye area. Ramsey and coworkers (1962) found that when ribeye area was

omitted from yield grade calculations, the resulting yield grades were more closely

related to separable lean and fat than when ribeye area was included. Other

researchers have also concluded that ribeye area should not be utilized in the

yield grade equation (Epley et al., 1970). Despite this discrepancy in the

literature, ribeye area remains in the USDA Yield Grade equation and is the only

direct measurement of carcass muscling.

Research is being conducted on instrument grading of carcasses and ribeye

area is considered one of the variables that should be studied (NCA, 1990). Also,

beef cattle breed associations are currently collecting data to determine expected

progeny differences (EPDs) for carcass traits, and ribeye area is one of the traits

of interest (Cundiff, 1991). Real-time ultrasound will play an important role in

both instrument grading and carcass EPDs. Topel and Kauffman (1988) report

that recent developments in ultrasound technology have led to new interest in

developing ultrasound techniques to predict carcass composition. Stouffer et al.

(1959) first reported on the use of ultrasound for measurement of carcass traits.

Since that time there has been a proliferation of new equipment and improved

techniques. Campbell and Herve (1971) found that ultrasonically determined

cross-sectional area measurements of the longissimus in the lumbar region can be








5
used to predict total muscle in live beef steers as accurately as prediction methods

based on measurements of anatomical dissection. Kempster and Owen (1981)

reported high correlations between ultrasonic measurements of cattle and carcass

composition using several different types of ultrasound units. Simm (1983)

conducted an exhaustive review of the literature concerning the use of ultrasound

to predict carcass composition. In general, he found that ultrasonically measured

muscle areas are the best predictors of dressing percentage, lean:bone ratio, and

weight of retail cuts, while ultrasonic fat measurements are the best predictors of

lean and fat percentages of the carcass. Stouffer et al. (1961) reported that

operator proficiency was crucial for obtaining reliable ultrasound estimates. Simm

(1983) also found operator proficiency was important in obtaining accurate

estimates. Simm (1983) concluded that marked improvements in the accuracy of

ultrasound were unlikely, since correlations between ultrasonic measurements and

carcass composition are often as high as correlations between actual

measurements of the carcass and carcass composition. Although improvements in

ultrasound equipment have occurred since the publication of that review in 1983,

no literature has addressed how those improvements may have increased the

accuracy and/or precision of ultrasonic measurements for predicting carcass

composition.

Several studies using more sophisticated ultrasound units have been

published in recent years. Bailey et al. (1986) studied the relationship of

ultrasonic estimates to carcass composition and muscle distribution and concluded









that for young, Holstein-type bulls that were of similar weight, the accuracy was

too low to justify the commercial use of ultrasonic scans and linear body

measurements. Miller et al. (1988) reported that ultrasound measurements of fat

and ribeye area may be used to predict percentage carcass fat with reliable

precision and accuracy (R2 = .83, rsd = 2.61). Faulkner et al. (1990) reported on

the usefulness of ultrasound 12th rib fat thickness for prediction of cow

composition. They found real-time ultrasound was a very accurate and precise

method of predicting fat measurement in the carcass and combined with live

weight and hip height was an accurate and precise method of estimating

percentage of fat, kilograms of fat, kilograms of fat-free lean, and percentage of

bone. An area that has not been thoroughly studied has been the use of

ultrasound to relate how ribeye area and fat thickness measurements change over

time. McLaren et al. (1989), working with swine, studied ribeye area and fat

growth and examined prediction equations for estimated body composition and

carcass characteristics based on serial real-time ultrasound measurements of loin

eye area and backfat thickness. They concluded that carcass characteristics of

market weight barrows and gilts can be predicted with reasonable accuracy by

early serial weight and ultrasonic measures of backfat and loin eye area. They

stated that this technique might prove valuable to seedstock swine producers

wishing to make early selection decisions. Little research of this type has been

published on beef cattle. Harada et al. (1989), working with Japanese Black bulls,

concluded that ultrasound estimates of fat thickness, ribeye area, and marbling









score at 20 and 40 mo of age could be predicted by the use of ultrasound

estimates at 14 mo of age. Turner et al. (1990) reported on the heritability of

ultrasonic measurements in Hereford bulls. They found that ultrasound fat

thickness and ribeye area were less heritable than carcass data traits and that

ribeye area measurements should be adjusted for age, weight, and fat thickness

effects.

The effects of frame size and breed on growth have been well documented;

however, little work has been done on the effect of frame size on ribeye area

changes over time. The concept of frame size, which is indicative of mature size,

is part of the basis for the USDA feeder cattle grading system (USDA, 1979).

Tatum et al. (1986) stated that cattle of large potential mature size (both among

and within breeds) normally grow faster, attain a given degree of maturity at older

ages, and begin to fatten at heavier weights than their smaller contemporaries.

From their study of the effect of feeder cattle frame size on absolute growth rate

and changes in carcass composition, Tatum et al. (1986) concluded that feeder

cattle frame size classification was indicative of differences in absolute growth rate

and slaughter weight at a specified level of fatness. Huffman et al. (1990)

reported that steers of 1/2 and 3/4 Brahman breeding had faster weight gains and

smaller ribeye areas than Angus steers. It is well documented that cattle of

predominantly Brahman breeding produce carcasses with smaller ribeye areas

than their contemporaries of predominantly Bos taurus breeding (Peacock et al.,

1982; Luckett et al., 1975; Crockett et al., 1979; Young et al., 1978; and Lopes,









1986); however, information on how Brahman breeding affects ribeye area

changes over time is lacking.

The literature is inconclusive concerning the effectiveness of ribeye area in

predicting carcass cutability. However, assuming that it is a useful measurement,

little work has been done to study how ultrasound technology can be utilized at an

early age to evaluate ribeye area growth and to make early selection decisions. In

general, this dissertation will address two major areas. The first study was

designed to evaluate the relationship between ribeye area and carcass cutability in

a subset of the current cattle population that represents a controlled range of

carcass weight and ribeye area. The second study was designed to examine the

changes that occur over time in ribeye area and fat thickness from a very young

age to slaughter and how sex condition, breed type, and frame size may be

related.













CHAPTER 2
THE RELATIONSHIP OF RIBEYE AREA TO MUSCLE-TO-BONE
RATIO, LEAN PERCENTAGE AND RETAIL YIELD AT DIFFERENT
FAT TRIM LEVELS


Introduction


The U.S. beef industry recently established a Value Based Marketing Task

Force (Cattlemen's Beef Board, 1990) whose primary objective was to "improve

efficiency of beef production by decreasing trimmable fat by 20% and increasing

lean by 6% by 1995, while maintaining taste qualities." How will this be

accomplished? During the late 1980s, retailers reduced fat trim on beef retail

cuts from 1.3 to .4 cm (Cross et al., 1986), which resulted in a 27% reduction in

fat in the retail case (Savell et al., 1990). These findings show promise for

reaching the goal of reducing trimmable fat by 20% in the next 4 years, but how

will the industry accomplish the goal of increasing lean by 6%?

Many beef cattle breed associations are collecting data needed to estimate

expected progeny differences (EPDs) for ribeye area for beef cattle sire

summaries, so producers will have an objective tool to use for selection of cattle

with more muscle (Cundiff, 1991). Additionally, research is being conducted on

instrumental methods to appraise value of live animals and carcasses, and the

cross-sectional area of the longissimus at the 12th 13th rib interface (ribeye area)









is considered one of the variables that should be assessed in this value

determination (NCA, 1990). Questions have been raised concerning the

effectiveness of ribeye area alone, or in combination with other carcass

measurements, as a tool to predict carcass cutability. Cole et al. (1960) reported

that ribeye area was associated with only 18% of the variation of percent

separable carcass lean, and that carcass weight alone was more useful in

predicting separable carcass lean than the multiple regression including both

carcass weight and ribeye area. Ramsey et al. (1962) found that when ribeye area

was omitted from yield grade calculations, the resulting yield grades were more

highly related to separable lean and fat than when ribeye area was included.

Epley et al. (1970) reported that ribeye area contributed little predictive value in

estimating percent retail cuts of the four major primals. Other researchers,

however, have found that ribeye area contributes significantly to multiple

regression equations designed to predict carcass cutability (Pierce and Hallet,

1961; Brungardt and Bray, 1963; Hedrick et al., 1965; Abraham et al., 1968; Cross

et al., 1973; Powell and Huffman, 1973; and Abraham et al., 1980). Despite the

conflicting findings on the effect of ribeye area on cutability, ribeye area remains

one of the independent variables in the USDA Yield Grade equation (USDA,

1965). Since 1965, USDA Yield Grades for beef carcasses have been the basis

for estimating carcass cutability, and ribeye area is the only direct measurement of

muscling used in the yield grade equation. This equation was developed from a

representative sample of the U.S. cattle population in the 1960s, including









carcasses from all classes of sex condition and also from a wide range in carcass

weight, fatness, and muscling. This broad sample allowed for accurate prediction

of cutability (Hedrick, 1968), which was measured as percentage boneless retail

cuts with 1.27 cm of subcutaneous fat.

Several measurements of cutability have been addressed in the literature.

Berg and Butterfield (1966) suggest that when genetic comparisons of lean

content are desired, muscle/bone ratio should be the end point evaluated. This is

based on the fact that fat tissue is of low value and the level of fatness can readily

be controlled environmentally. These authors point out that the market

requirement at any particular time or locality would define the amount of fat

desired. Many authors have assessed the amount of lean, as a percentage of

carcass weight, which can be physically and/or chemically separated from fat and

bone (separable lean). The end point for the yield grade equation is retail yield

(lean and fat) of boneless subprimals trimmed to 1.27 cm of subcutaneous fat.

Retail yield can be expressed at various levels of fatness. As packers and retailers

reduce the amount of fat on boxed subprimals and retail cuts to .4 cm or less,

measurements of muscle, such as ribeye area, may become more important in

predicting cutability.

The current study was designed to evaluate the relationship between ribeye

area and cutability in a subset of the present cattle population that represents a

controlled range of sex class, carcass weight, and ribeye area. It is proposed that

this subset accurately reflects typical beef carcasses (USDA, 1977), where








12
assessment of the relationship between ribeye area and carcass cutability is most

crucial. The specific objectives of this study were: (1) to assess the relationship

between ribeye area and various carcass cutability end points in a population of

carcasses where, within specified carcass weight ranges, ribeye area varied; (2) to

determine if differences in cutability exist between carcasses classified as having

"above average," "average," or "below average" ribeye areas, relative to the USDA

cutability equation; (3) to determine if fat trim level has an affect on the

relationship between ribeye area and cutability; and (4) to develop the optimal

prediction equation for carcass cutability from carcass and individual muscle

measurements.


Materials and Methods


Carcass Selection


Figure 2-1 shows the distribution of carcasses (n=54) selected to represent

six weight ranges (1 = 227 to 249, 2 = 250 to 272, 3 = 273 to 295, 4 = 296 to

318, 5 = 319 to 340, and 6 = 341 to 367 kg) and three ribeye area classifications

(1 = below average, 2 = average, and 3 = above average). Carcasses originated

from crossbred steers in three different feeding trials; however, steers were of

similar age and pre-slaughter management treatments. Steers were produced at

University of Florida beef research units and placed in the feedlot after weaning

and were fed comparable rations until they reached pre-assigned slaughter end

points based on ultrasonic fat thickness measured at the 12th rib. Slaughter end











RIBEYE AREA, CM


250 272 295 318 341 363 386
CARCASS WEIGHT, KG


Figure 2-1. Number of carcasses selected for each ribeye area
and carcass weight range.


40
227








14
point varied between trials from .9 to 1.3 cm of ultrasound subcutaneous fat. Fat

thickness of the live animal was monitored monthly for the first 60 d of the

feeding period and every 2 wk thereafter. Steers were removed from the feedlot

when they reached their pre-assigned slaughter end point and were transported to

either a commercial packing facility or the University of Florida Meat Laboratory

for slaughter.

After routine slaughter procedures, carcasses were chilled for 24 h at 0 to

2 C, ribbed, and graded for USDA quality and yield grade factors by University

of Florida personnel. Within each weight range approximately three carcasses

were selected for each of the three ribeye area classifications. Average ribeye

area was based on the USDA Yield Grade "short cut" adjustment for ribeye area.

Ribeye area was assumed to be average if it was within 3.23 cm2 of the calculated

average for the particular hot carcass weight. Above and below average ribeye

areas spanned a range from 3.23 cm2 to 16.13 cm2 above and below the calculated

average within each weight range.


Carcass Fabrication


One side of each carcass, the side that had more bone after splitting, was

weighed, trimmed of hanging tender, heart fat, channel fat, and other trim

(thymus gland, tendinous edge of diaphragm and spinal cord). The side was then

ribbed between the 12th and 13th ribs, quartered and weighed as outlined by

USDA (1990). Sides were fabricated into wholesale cuts (Koch and Dikeman,









1977), trimmed to have not more than 2.54 cm of subcutaneous fat, and the

components weighed. The wholesale cuts were further fabricated into boneless

subprimals trimmed to .64 cm of subcutaneous fat. Weights of exposed

intermuscular fat, trimmed subcutaneous fat, lean trim, and bone plus heavy

connective tissue were recorded. Any intermuscular fat encountered during this

phase of fabrication was kept separate and was combined with other

intermuscular fat during the latter stages of fabrication. Wholesale cut fabrication

procedures were in accordance with Institutional Meat Purchase Specifications

(IMPS) for Fresh Beef (USDA, 1990). The IMPS boneless subprimals obtained

from the forequarter were: IMPS #107--rib oven prepared (further fabricated into

IMPS #112A--ribeye roll, lip on); IMPS #114--shoulder clod; IMPS #116A--

chuck roll; IMPS #116B--chuck tender; IMPS #120--brisket, boneless, deckle off;

IMPS #121E--skirt steak; and IMPS #117--foreshank. The IMPS boneless

subprimals obtained from the hindquarter were: IMPS #176--strip loin; IMPS

#182--sirloin butt; IMPS #189B--full tenderloin; IMPS #193--flank steak; IMPS

#167--knuckle; IMPS #168--top round; and IMPS #170A--bottom round, heel

out.

The following boneless IMPS subprimals were completely trimmed of all

subcutaneous fat, and individual muscles were separated and completely trimmed

of all intermuscular fat: IMPS numbers 112A; 114; 116A; 120; 176; 182; 189; 167;

168; and 170A. The "bridging" and "planing" techniques were followed as outlined

in IMPS (USDA, 1990) to distinguish between intermuscular and subcutaneous








16
fat. Intermuscular fat, subcutaneous fat less than .64 cm, lean trim, and individual

trimmed muscles were separated, weighed, and recorded. Lean trim removed

during this phase of fabrication was kept separate from both hindquarter and

forequarter lean trim.

Lean trim from the forequarter, lean trim from the hindquarter, lean trim

from boneless subprimals and intermuscular fat were kept separate and were

ground two times, mixed thoroughly, subsampled, vacuum packaged and frozen for

subsequent lipid analysis. Lean trim subsamples were thawed overnight in an 8

to 10" C cooler, then ground finely and mixed prior to moisture and lipid analysis

by the oven drying and soxhlet methods, respectively (AOAC, 1985).

Retail yields were calculated at three subcutaneous fat trim levels: 2.54 cm,

.64 cm, and 0 cm. For each subcutaneous fat trim level, successively leaner

chemical fat percentages were used to calculate lean trim yields. Retail yield at

2.54 cm included IMPS boneless subprimals with not more than 2.54 cm

subcutaneous fat and lean trim adjusted to 25% chemical fat. Retail yield at .64

cm included IMPS boneless subprimals trimmed to .64 cm subcutaneous fat and

lean trim adjusted to 20% chemical fat. Retail yield at 0 cm trim included IMPS

boneless subprimals with all subcutaneous fat removed (with intermuscular fat

intact), and lean trim adjusted to 10% chemical fat.

Muscle/bone ratio was calculated by two methods. First, muscle/bone

ratio was calculated by adding defatted retail muscles to lean trim that had all

"knife separable" fat removed and then dividing this value by total bone weight.









Secondly, fat-free muscle/bone ratio was calculated by adding defatted retail

muscles to lean trim adjusted to 0% chemical fat and then dividing by total bone

weight. It should be noted that defatted retail muscles contained intramuscular

fat. Separable lean was calculated by adding defatted retail muscles to lean trim

that had been adjusted to 5% chemical fat.

Additional measurements were made to assess the usefulness of various

parts of the carcass in predicting cutability of the whole carcass. These included

biceps femoris weight/femur weight ratio, longissimus weight, longissimus length,

circumference of longissimus at the 12th rib, and circumference of longissimus at

its widest point.


Statistical Analysis


Means, standard deviations, simple correlations, regression coefficients and

standard partial regression coefficients were computed using SAS (1985). Single

and multiple regression models were utilized to predict cutability end points using

traditional carcass measurements. The General Linear Model procedure was

utilized to determine if cutability differed among carcasses classified into three

groups based on ribeye area. Stepwise regression was used to establish the best

model for predicting cutability using carcass measurements, individual muscle

measurements, and part-whole relationships of the carcass.









Results and Discussion


Table 2-1 shows mean values for carcass characteristics and cutability end

points evaluated in this study. Coefficients of variation (CV) were much greater

for carcass measurements (12.3% to 23.3%) than for carcass cutability end points

(3.58% to 8.42%). The variability in ribeye area and hot carcass weight was

established as a result of the selection of carcasses. The carcass selection criteria

placed no restrictions on adjusted fat over the ribeye, and adjusted fat over the

ribeye was variable, .38 cm to 1.52 cm, even though steers were assigned to be

slaughtered when ultrasound fat thicknesses measured either .9, 1.0, or 1.35 cm.

When compared with other experiments designed to assess cutability prediction,

the range in adjusted fat thickness in this study was smaller (Ramsey et al., 1962;

Abraham et al., 1980; May et al., 1990) or comparable (Crouse et al., 1975;

Crouse and Dikeman, 1976). Variability relative to the mean (CV) increases as

fat in the cutability end point decreases. This may be due to the fact that the

means are getting smaller while variability is remaining constant, thus increasing

CV. Additional cut fabrication, and consequent increased chance of cutting error,

required to attain the lower fat end points, may also be a contributing factor.

Simple correlation coefficients (r) between carcass measurements and

carcass cutability are presented in Table 2-2. Ribeye area was correlated with (P

< .01) each of the carcass cutability end points (r = .35 to .45). Correlations for

ribeye area with various measures of cutability are similar to previously published

values: r = .43 for separable lean (Cole et al., 1960), r = .45 for retail yield at .94









TABLE 2-1. MEAN CARCASS AND CUTABILITY CHARACTERISTICS


Mean SD Min. Max. CV,%c


Measurement
Carcass measurements
Ribeye area, cm2
Hot carcass weight, kg
Adjusted fat over the eye, cm
Estimated KPH fat, %
Marbling scorea
USDA yield grade
Carcass cutability endpoints
Muscle/bone ratio
Fat-free muscle/bone ratio
Retail yield at 2.54 cm, %b
Retail yield at .64 cm, %b
Retail yield at 0 cm, %b
Separable lean, %b


9.0
38.7
.24
.50
68.6
.45


.33
.32
2.6
2.7
2.8
2.7


57.0
228.2
.38
1.0
170.0
1.5


3.5
3.2
66.0
60.4
51.2
49.9


92.0
367.0
1.52
3.0
520.0
3.5


5.2
4.7
79.5
73.2
63.3
61.8


12.3
13.3
23.3
23.8
20.4
16.7


7.9
8.4
3.6
4.0
6.6
4.9


a Marbling scores are as follows; 100-199 = practically devoid, 200-299 = traces,
300-399 = slight, 400-499 = small, 500-599 =modest.
b Calculated on a percentage of side weight basis.
c CV% = coefficient of variation.


73.2
290.6
1.03
2.1
336.7
2.7


4.2
3.8
72.7
66.8
57.4
55.7

















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cm fat trim (Brungardt and Bray, 1963), r = .41 for retail product (Crouse and

Dikeman, 1976), and r = .42 for percent boneless wholesale cuts trimmed to .64

cm (May et al., 1990). Hot carcass weight appeared to have no correlation with

retail yield or separable lean and only a slight correlation (r = .25, P < .05) with

fat-free muscle/bone ratio. Adjusted fat over the ribeye was positively correlated

with muscle/bone ratio (r = .27, P < .05), but was not significantly correlated

with fat-free muscle/bone ratio. This may be partly explained by the fact that the

muscle value used in the muscle/bone ratio calculation contained fat that could

not be removed with a knife, whereas the muscle value in the fat-free

muscle/bone ratio calculation had all physical and chemical fat removed.

Adjusted fat over the ribeye was negatively associated with retail yield at both .64

cm and 0 cm fat trim levels (r = -.41 and r = -.43, P < .05), showing that as

carcass fat increases, retail yield at these fat trim end points decreases. Adjusted

fat over the ribeye was negatively related (r = -.48, P <.01) to separable lean.

These correlations are not as high as reported by other authors: r = -.76 for

separable lean (Ramsey et al., 1962), r = -.82 for major boneless subprimals

(Abraham et al., 1980), and r = -.52 for percent boneless wholesale cuts trimmed

to .64 cm (May et al., 1990). The lower correlations found in this study might be

explained by the narrower range in adjusted fat over the ribeye of the carcasses

when compared to other studies. Steers in this study were slaughtered at similar

fat thicknesses, therefore diminishing the variability in carcass fat thickness.

Estimated kidney, pelvic, and heart fat showed a negative relationship (r = -.45








22
to -.34) with retail yield. These relationships show a decreasing trend as fat trim

end point decreases. Separable lean was also significantly correlated (r = -.31)

with estimated kidney, pelvic, and heart fat. As expected, USDA Yield Grade

was negatively associated (P < .01) with retail yield at all three fat trim end

points, and the relationships appeared to be stronger when cuts were trimmed to

.64 cm or less. Separable lean had the greatest correlation with USDA Yield

Grade (r = -.59, P < .01). USDA Yield Grade was not correlated with (P>.05)

muscle/bone ratio. Marbling score was related to retail yield at .64 cm and 0 cm

fat trim end points (P <.05) and to separable lean (P < .01). This is in

agreement with May et al. (1990) who reported a correlation of r = -.39 between

retail yield at .64 cm and marbling score. The simple correlation between

marbling score and adjusted fat thickness was .47; therefore, carcasses with higher

marbling scores tended to be fatter and therefore had lower yields at higher levels

of marbling.

Correlations of individual muscle weights and measurements are presented

in Table 2-2. Circumference of the longissimus at the 12th 13th rib interface (r =

.31, P < .05), and longissimus weight (r = .29, P < .05) were correlated with fat-

free muscle/bone ratio. Longissimus length showed no correlation with carcass

cutability. Weight of the biceps femoris, one of the heaviest muscles in the

carcass, was significantly correlated with each of the six cutability end points. The

femur, one of the heaviest bones in the carcass, was positively correlated with

separable lean. When these two values were used to develop a ratio, significant







23
positive correlations were obtained for all cutability end points. Lunt et al. (1985)

reported that the biceps femoris/femur ratio was useful in predicting cutability as

measured by percentage separable lean.

Table 2-3 presents multiple linear regression information using

independent variables of the USDA Yield Grade equation to predict each of six

cutability end points. Each of the four yield grade variables were forced into the

models. All models presented are significant (P < .01).

Ribeye area contributed (P < .01) to both muscle/bone ratio and fat-free

muscle/bone ratio models. Standardized partial regression coefficients (b1) show

ribeye area to be the most important independent variable in these two models.

The b1 coefficients are smaller for separable lean (P<.01) and retail yield (P<.05)

than for muscle/bone ratio, thus suggesting that ribeye area is more useful in

predicting muscle/bone ratio end points. The b1 coefficients do show, however,

that ribeye area was still the most important independent variable in the models

predicting separable lean and retail yield. Crouse et al. (1975) reported that when

carcass weight was held constant, ribeye area was a very useful predictor of yield

of retail cuts; however, when carcass weight was allowed to vary, ribeye area's

usefulness diminished greatly. In this study, hot carcass weight was held relatively

constant in relation to ribeye area.

Hot carcass weight was not a significant variable in any of the models

examined. Griffin et al. (1989), using the same independent variables to predict

yield of major boneless subprimals at different fat trim levels, found very similar











TABLE 2-3. MULTIPLE REGRESSION EQUATIONS AND STANDARD
PARTIAL REGRESSION COEFFICIENTS FOR PREDICTING CARCASS
CUTABILITY END POINTS FROM CARCASS MEASUREMENTS

ba Independent variableb
and
End point Intercept b1 REA HCW ADFOE KPH R2 pc

Muscle/bone 2.6 b .02" -.002 .52* .01 .28 .0023
ratio b1 .62 -.24 .37 .02

Fat-free 2.2 b .02" -.002 .41' -.01 .30 .0014
muscle/bone b1 .66 -.21 .31 -.02
ratio

Retail yield, 71.8 b .14' -.01 -.79 -2.3" .35 .0002
2.54 cm, %d bI .49 -.20 -.07 -.43

Retail yield, 68.0 b .14' -.02 -3.0' -1.8' .37 .0001
.64 cm, %d b1 .47 -.23 -.26 -.32

Retail yield, 57.8 b .15' -.02 -3.35' -1.46' .36 .0002
Ocm, %d b1 .49 -.23 -.28 -.26

Separable 56.2 b .14" -.01 -4.1" -1.2 .38 .0001
lean, %d b1 .46 -.20 -.35 -.22
* -D nD **_K=D nl


-- '-.J,


- A U.


a b = parameter estimate, b1 = standard partial regression coefficient
b REA = ribeye area, HCW = hot carcass weight, ADFOE = adjusted fat over the ribeye,
KPH = estimated kidney, pelvic, and heart fat.
c P = significance level for the overall regression model
d Calculated as a percentage of side weight








25
b values for hot carcass weight: yield at 2.54 cm fat trim, b = -.009; and yield at

.64 cm fat trim, b = -.0109.

Adjusted fat over the ribeye has often been reported as the best single

indicator of cutability (Powell and Huffman, 1973); however, in this study adjusted

fat over the ribeye was not the most important variable in predicting cutability. In

the muscle/bone ratio and fat-free muscle/bone ratio models, adjusted fat over

the ribeye gave b' values that were half as large as the b1 values for ribeye area.

Adjusted fat over the ribeye was significant in the models predicting retail yield at

.64 cm fat trim (P < .05, b' = -.26), retail yield at 0 cm fat trim (P < .05, b1 =

-.28), and percentage separable lean (P < .01, b' = -.35). As would be expected,

adjusted fat over the ribeye became more important as fat percentage in the

cutability end point decreased.

Kidney, pelvic, and heart fat was also included in the models presented in

Table 2-3. It had no significant influence on the prediction of muscle/bone ratio,

fat-free muscle/bone ratio or the percentage of separable lean. Kidney, pelvic,

and heart fat was a factor (P <.01) in the prediction of retail yield at 2.54 cm fat

trim and also was a significant factor in the prediction of retail yield at the

trimmer cutability end points; however, as the amount of fat in the cutability end

point decreased, the importance of kidney, pelvic, and heart fat diminished.

The R2 values reported in Table 2-3 are substantially smaller than those

reported by other authors. Crouse and Dikeman (1976), exploring the

determination of retail product yield in beef, reported an R2 of .69 for an







26
equation containing USDA Yield Grade variables of hot carcass weight, adjusted

fat thickness, ribeye area and kidney, pelvic, and heart fat. Abraham et al. (1980)

evaluated the usefulness USDA Yield Grades and reported R2 = .80 for an

equation containing yield grade variables. May et al. (1990) reported slightly

lower values for predicting retail yield at .64 cm subcutaneous fat trim (R2 = .59).

Murphey et al. (1960) analyzed data of the original study from which the USDA

Yield Grade was derived and reported simple correlation coefficients between the

actual and predicted retail yield were highly significant (r = .91). Hedrick (1968)

stated that when the USDA Yield Grade equation was applied to a more

homogenous group of carcasses than was used in the 1960 study, the relationships

are likely to be lower than originally reported. Griffin et al. (1989) presented

multiple regression equations containing the yield grade variables that had lower

R2 values, (R2 = .38 for predicting retail yield with 2.54 cm subcutaneous fat trim

to R2 = .49 for predicting retail yield with .64 cm of subcutaneous fat trim) more

similar to those reported in Table 2-3.

Figures 2-2 through 2-7 provide a graphical representation of the linear

regression of cutability on ribeye area. All simple regression models were

significant (P <.05) for predicting each of the cutability end points. Each of the

regression lines are rather similar with R2 values ranging from R2 = .12 for retail

yield at .64 cm fat trim to R2 = .20 for fat-free muscle/bone ratio. These data

are in agreement with Cole et al. (1960), who reported that when ribeye area was

used alone to predict separable lean from the carcass, only 18% of the variation












MUSCLE/BONE


5.4

5.2

5.0

4.8

4.6

4.4

4.2

4.0

3.8

3.6

3.4
50.0


70.0 80.0
RIBEYE AREA, CM 2


90.0


100.0


Figure 2-2. Linear regression of muscle/bone ratio on
ribeye area.


MUSCLE/BONE RATIO 3.23 + REA(.014)
2
R2 .14
.







'_^---^r ^."


*'" ..


60.0












FAI
5.0

4.8

4.6

4.4

4.2

4.0

3.8

3.6

3.4-

3.2

3.0
50.0


60.0


70.0 80.0
RIBEYE AREA, CM 2


90.0


100.0


Figure 2-3. Linear regression of fat-free muscle/bone ratio on
ribeye area.


--FREE MUSCLE/BONE

FAT-FREE MUSCLE/BONE 2.68 + REA(.016)
2
R .20


S*












RETAIL YIELD, %
80.0 1


RETAIL YIELD, 2.54 cm % 65.16 + REA(.10)
2
R2 .13


^-i-






: i i *


60.0


70.0 80.0
RIBEYE AREA, CM 2


90.0


100.0


Figure 2-4. Linear regression of retail yield at 2.54 cm of
subcutaneous fat trim on ribeye area.


75.0 h


70.0 F


65.0
50


.0


I I I I












RETAIL YIELD, %


75.0


70.0 k


65.0 I


60.0
50.


.0


60.0


70.0 80.0
RIBEYE AREA, CM 2


90.0


Figure 2-5. Linear regression of retail yield at .64 cm of
subcutaneous fat trim on ribeye area.


RETAIL YIELD, .64 cm, % 59.13 + REA(.10)
2
R2 .12











mR*


*


100.0












RETAIL YIELD, %


65.0


60.0


70.0 80.0
RIBEYE AREA, CM2


90.0


Figure 2-6. Linear regression of retail yield at 0 cm of
subcutaneous fat trim on ribeye area.


60.0 I


55.0 I


RETAIL YIELD, 0 cm % 49.05 + REA(.11)
2 .
R .14



"







a


fl II


50.0


100.0


;n













SEPARABLE LEAN, %

SEPARABLE LEAN, % 47.1 + REA(.12)
2
R 2 .15


.*

-


60.0


i I
70.0 80.0
2
RIBEYE AREA, CM


90.0
90.0


100.0


Figure 2-7. Linear regression of separable lean percentage
on ribeye area.


65.0-




60.0-




55.0-




50.0-


45.0 -
50.0









could be explained. Much of the current literature in this area fails to provide

information regarding the usefulness of ribeye area as a single regressor for

predicting cutability. The single linear regressions were included in this

manuscript to gain a better understanding of the usefulness of ribeye area in

explaining the variation that exists in cutability.

Table 2-4 gives least squares means for carcass cutability end points for

each of the specified ribeye area classifications. These classifications were based

on the USDA Yield Grade "short cut" method for determining ribeye area

adjustment, which utilizes the relationship between ribeye area and hot carcass

weight. A carcass which would have a preliminary yield grade adjustment for

ribeye area of plus or minus .2 would be considered average, an above average

carcass would represent an adjustment of -.2 to -.45, and a below average carcass

would represent an adjustment of +.2 to +.45 to the preliminary yield grade.

This was examined to determine if a carcass that is generally considered as "above

average" for muscling (ribeye area) is actually different in cutability from a carcass

that is generally considered "below average" for muscling. Although there appears

to be a tendency for the above average group to have higher cutability, no

significant differences were found between classification groups. A greater range

in ribeye area in the carcass population might provide the opportunity to detect

differences between these classification groups; however, in a population selected

to represent the majority of "typical" carcasses, using the ribeye area/weight

relationship to segregate carcasses into cutability groups appears to be ineffective.










TABLE 2-4. LEAST SQUARES MEANS FOR CARCASS CUTABILITY
END POINTS BY RIBEYE AREA CLASSIFICATION WITH ADJUSTED
FAT OVER THE RIBEYE AS A COVARIATE

Ribeye area classification
End point below average above SE P-valueb

Muscle/bone ratio 4.1 4.1 4.3 .07 .12
Fat-free
muscle/bone ratio 3.8 3.8 4.0 .07 .09
Retail yield, 2.54 cm, %a 72.4 72.5 73.2 .62 .41
Retail yield, .64 cm, %a 66.5 66.6 67.1 .60 .29
Retail yield, 0 cm, %2 57.1 57.3 57.9 .61 .21
Separable lean, %a 55.4 55.3 56.2 .58 .18


a Calculated as a percentage of side weight.
b P-value for the overall least squares model.









Table 2-5 presents models to predict cutability generated from stepwise

regression. All carcass measurements, including individual muscle and bone

measurements, were considered as candidate variables. The level for entry into

the model was P < .15 and 12 variables were considered. Ribeye area was the

only carcass measurement that entered into all six of the models. A model

containing ribeye area, biceps femoris weight, and biceps femoris/femur ratio had

an R2 value of .56 for predicting muscle/bone ratio. A slightly different model

was obtained for predicting fat-free muscle/bone ratio (R2 = .58), the only

difference being the substitution of femur weight for biceps femoris weight.

Models for estimating retail yield end points were all different however, each used

ribeye area, estimated kidney, pelvic, and heart fat, and biceps weight.

The results of this study indicate significant, but low relationships exist

between carcass characteristics and carcass cutability. These results are in general

agreement with much of the current literature. Possible explanations for the lack

of predictability of carcass cutability may stem from the fact that the variation in

carcass cutability is relatively low within a population of typical slaughter cattle.


Implications


This study presents a unique look at the usefulness of ribeye area in

equations designed to predict beef carcass cutability. Although current literature

on this subject is not in full agreement, the results presented from this study

indicate that within a population of carcasses that represent the majority of















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"typical" slaughter cattle, where variation in carcass weight and ribeye area were

controlled, ribeye area was as valid as any other carcass measurement in

predicting beef carcass cutability. However, only 12% to 20% of the variation in

cutability could be explained by ribeye area alone, and there were no statistical

differences in cutability between carcasses classified as "above average," "average,"

or "below average" for ribeye area. Biceps femoris weight, femur weight and the

ratio of these two variables proved valuable as predictors of cutability. Therefore,

programs aimed at determining beef carcass value should incorporate ribeye area

along with other carcass variables into prediction equations. If feasible, major

muscle and/or bone weights could greatly enhance the predictive value of

regression equations designed to predict cutability.












CHAPTER 3
RIBEYE AREA AND FAT THICKNESS GROWTH DURING
THE EARLY LIFE OF BEEF CALVES


Introduction


Animal scientists and cattlemen are faced with the task of identifying

individual breeding cattle that will perform to a specified level for a given trait.

Numerous traits have been evaluated over the years; however, carcass traits have

received a considerable amount of attention during the past decade due to

consumer demands for leaner meat products. Historically, carcass trait

information has been difficult to obtain on breeding cattle because of the

tremendous expense involved in collecting carcass data on progeny of individual

animals. However, during the last decade, the advent of real-time ultrasound has

provided the opportunity for the measurement of ribeye area and fat thickness on

the live animal at a relatively low cost and with reliable accuracy.

The area of cattle growth and development has been of interest to those

involved in animal production for decades, and complete understanding of the

complexities of the bovine growth curve has yet to be attained. Butterfield (1964)

stated that all organisms, except the most simple, undergo changes of form due to

differential growth rates of their constituent parts, and the early works of

Hammond (1921), Palsson (1932), and Huxley (1932) all described developmental









changes that occur in young, growing ruminant animals. The classical work of

Butterfield (1964), through the use of individual muscle dissection, established

"standard muscle groups", where muscles were grouped according to their relative

postnatal growth. The muscles surrounding the spinal column were classified as

average-developing muscles because their weight in relation to that of total

carcass muscle remained virtually unchanged during post-natal life. Berg and

Butterfield (1966) reported that major changes in the musculature of cattle occur

in the first 6 to 8 months of life. According to the body growth gradient theory,

Huxley (1932) stated that the cross-sectional area of the longissimus muscle at the

last rib was the best method to estimate the degree of muscle development. Since

those early days, numerous other researchers have proven the usefulness of

longissimus muscle area measurement in estimating muscle development (Hedrick

et al., 1965; Powell and Huffman, 1973; and Abraham et al., 1980). Therefore, a

measurement made at weaning (about 7 to 9 mo of age) of the longissimus dorsi

(ribeye area) has the potential to be a reliable predictor of total carcass muscle.

Growth of the longissimus after weaning should be relative to the growth of other

muscle groups of the carcass, since the longissimus muscle was in the group

classified as average developing by Butterfield (1964).

Understanding when to obtain and how to utilize ultrasound information

has become an area of great importance; however, little work has been published

on this subject. Harada et al. (1989), working with Japanese Black bulls,

concluded that ultrasound fat thickness and ultrasound ribeye area at 20 mo and









at 30 mo of age could be accurately predicted from ultrasound estimates of fat

thickness and ribeye area at 14 to 16 mo of age. Turner et al. (1990) suggested

that ultrasound measurements should be taken as close to 365 d of age as

possible. From an economical standpoint, however, cattlemen would prefer

obtaining ultrasound measurements early in the growth cycle so that selection

decisions could be made before bulls reach a year of age and incur added

expenses associated with feeding and management. Ultrasound measurements of

ribeye area have the potential to be more accurate on lighter weight cattle, before

the image of the ribeye becomes large and difficult to capture with the ultrasound

equipment. Additionally, if cattle are in good condition (> 10 mm), fat thickness

measurements may be less accurate. Turner et al. (1990) reported that ultrasound

technicians participating in the BIF certification consistently underestimated

actual carcass fat thickness as the animals got fatter. To address the problem of

when ultrasound measurements should be taken, information on how

ultrasonically determined muscle and fat measurements change over time and how

these changes are related to weight changes would be useful.

Berg and Butterfield (1966) found that the amount of fat on cattle is under

a high degree of environmental (management) control. Body composition can

vary greatly in the percentage of fat, depending on stage of growth and plane of

nutrition. Fat thickness is best utilized for describing changes in fatness within

populations of cattle that are of similar age and have been under similar

management.









Frame size and/or breed type may have an effect on the growth rate of

ribeye area and fat thickness. Frame size has been shown to have an influence on

cattle growth (BIF, 1990). In general, research shows that small frame cattle tend

to grow at a slower rate, whereas large frame cattle tend to exhibit faster growth

(Tatum et al., 1986). Huffman et al. (1990) found breed type had a significant

effect on weight gain and ribeye area size.

Very little data exist showing the changes that occur over time in ribeye

area and fat thickness from a very young age to slaughter, and how breed type

and/or frame size may be related. Development of growth curves for ribeye area

and fat thickness, both measured by ultrasound, would prove valuable in

understanding how to utilize ultrasound data on young breeding cattle. Therefore,

the objectives of this study were: 1) to develop and describe growth curves for

weight, ultrasound ribeye area, ultrasound ribeye area / 45.4 kg live weight, and

ultrasound fat thickness in cattle; and 2) to determine what effects sex condition,

frame size, and breed type have on these growth curves.


Materials and Methods


Experimental Procedure


One hundred and ninety five steer (n = 99) and heifer (n = 96) calves

were used in the preweaning phase of this study. These calves were from cows of

five breed groups [Angus (A), Brahman (B), 3/4A:1/4B, 1/2A:1/2B, and Brangus

(5/8A: 3/8B) and sires of six breed groups (the five breed groups of dams and









1/4A:3/4B)]. Fifteen separate calf breed percentages were represented ranging

from 100% Angus to 100% Brahman; however, for simplification of analysis and

interpretation, calves were classified into five "breed groups" as follows; BG 1 =

81% to 100% Angus, BG 2 = 61% to 80% Angus, BG 3 = 41% to 60% Angus,

BG 4 = 21% to 40% Angus, and BG 5 = 0% to 20% Angus. The number of

calves in each breed group and their distribution are displayed in Table 3-1.

Calves were born on the University of Florida's Pine Acres Research Unit, Citra,

from December, 1988 to May, 1989.

Beginning in February, when the oldest calves were about 2 months of

age, two Beef Improvement Federation (BIF) certified ultrasound technicians

obtained ultrasound images approximately every 4 to 6 wk until weaning. Calves

born early in the season (December to February) were weaned in September, and

calves born late (March to May) were weaned in October. This allowed for four

to seven pre-weaning measurements per calf, depending on the age of the calf.

After weaning, calves were allotted to three different experiments, not

associated with this study, where nutritional treatment was the area of interest.

For this reason some postweaning measurements were not obtained and some

animals were not utilized in the postweaning data set. Heifers were only utilized

in the preweaning period. Fifty-six of the steer calves were utilized in the

postweaning measurements. After weaning, steer calves were maintained on

bahiagrass pasture for approximately 75 d, then placed in the feedlot. Steer

calves were fed a finishing ration for no less than 98 d. Postweaning weight and











TABLE 3-1. DISTIRBUTION OF CALVES BY FRAME GROUP AND
BREED GROUP.
Breed group
Frame group BG1 BG2 BG3 BG4 BG5
Steers
FG1 7 2 2 0 0
FG2 9 4 6 2 1
FG3 3 7 10 9 6
FG4 1 4 5 5 8
FG5 0 0 2 6 0
Heifers
FG1 21 5 6 3 0
FG2 7 5 16 7 1
FG3 0 3 3 9 9
FG4 0 1 0 0 1









ultrasound measurements were taken every four weeks until all steers were

slaughtered. Steers were removed from the feedlot and slaughtered when they

reached either .9 or 1.3 cm of ultrasound fat thickness determined at the 12th -

13th rib interface. This allowed for four to eight postweaning weight and

ultrasound measurements, depending on when slaughter occurred.

Hip height was determined at weaning and was used with age to calculate

frame size as described by the Beef Improvement Federation (BIF, 1990). In this

study, frame size ranged from .96 to 7.03. To study the influence of frame size on

growth, calves were grouped into frame size groups which attempted to cover the

range represented, while keeping numbers of calves within classification groups as

even as possible. Five frame size groups were created for steers (FG1 = <3,

FG2 = 3 to 4, FG3 = 4 to 5, FG4 = 5 to 6, FG5 = >6) and four for heifers

(FG1 = <3, FG2 = 3 to 4, FG3 = 4 to 5, FG4 = >5). Table 3-1 shows the

distribution of calves by frame group and breed group.

An Aloka 210-DX B-mode scanner equipped with a UST-5021 probe was

used to obtain cross-sectional images of the longissimus dorsi at the 12th 13th rib

interface. This probe operates at 3.5 Mhz with an image refreshing rate (frame

rate) of 10 or 20 frames/s. Dynamic, or "real-time" ultrasound images were

recorded on a VHS video cassette recorder and stored for subsequent analysis.

All preweaning ultrasound scans were taken using the single-screen mode.

Because of the size of the ribeye at weaning, a desirable image in the single-

screen mode could not be obtained; therefore, the split-screen mode had to be








45
utilized. The split-screen mode required the use of a calibrated probe guide that

allows the operator to freeze the left screen that contains half of the desired

picture, and then "match" the right screen to complete the desired picture. As

suggested by Simm (1983), all recorded scans were interpreted by one individual,

a BIF certified technician. Animorph, a video image analysis system, was used to

measure fat thickness and ribeye area from the ultrasound recordings. This

system allows the user to "grab" a single frame from the video tape, thus allowing

an interface with the computer. A trackball was then used to measure fat

thickness at a point, laterally from the spine, three-fourths of the distance across

the longissimus muscle. The trackball was used to trace the area of the

longissimus muscle (ribeye area). Duplicate scans of each animal were measured,

and when the first two values differed by more than 10%, a third measurement

was taken. A mean was computed on the two closest measurements.


Statistical Analysis


All analyses were done separately for preweaning and postweaning

measurements because calves were treated similarly prior to weaning and all one-

hundred and ninety five calves were utilized, however; after weaning calves were

allotted to three different experiments where nutritional treatment was the area of

interest. For this reason some postweaning measurements were not obtained. All

heifers were utilized preweaning. Postweaning measurements were utilized from

fifty-six (n=56) steer calves that were backgrounded for 75 d and then placed in









the feedlot. Because of the repeated measurements on each animal, random

coefficient regression analysis, as described by Gumpertz and Pantula (1989) and

Littell (1990), was used. Linear and quadratic models were fitted to the data with

age as the independent variable and weight, ultrasound ribeye area, ultrasound

ribeye area/45.4kg live weight (REACWT), and ultrasound fat thickness as

dependent variables. Estimates of the intercept and coefficients for the linear and

quadratic terms were obtained for each calf. A new data set was then constructed

which contained estimates of these regression parameters for each calf. Using

estimates of the regression parameters as dependent variables, analysis of variance

procedures were employed to test for differences between steer and heifer calves.

Sex condition was found to have a significant effect on all regression coefficients

except for the quadratic weight term and the linear and quadratic fat thickness

terms. Because of the sex effect, further analyses was conducted separately for

steers and heifers. Analysis of variance procedures were then utilized to

determine the effects of frame size and breed type on the dependent variables.

Least squares means were computed and mean separations were performed and

considered significant at P <.05.


Results and Discussion


Table 3-2 presents means and standard deviations for age, weight, ribeye

area, REACWT, and fat thickness at each measurement time. Table 3-2 shows

that preweaning weight and ribeye area increased over time for both sexes. Steers

































* I I a a







I a a a a







* a a a
* I a a I


0%



0%
eq


I0 f -O 4 )i^
l) | r 0 | .l
tt. 2 < : 2 o z Q c,
ua 4
Z 0 -: Cr.


u








<2







BE
Q


7
2e
w>


II

4)


4)












-




cJ*


0I




0 4)
Zu


II U
-8
C. II
<<-t



* .0 Ii









were heavier and had slightly larger ribeye areas at each measurement period

than heifers. Ribeye area expressed relative to body weight, REACWT, showed a

decreasing trend through the preweaning period and heifers had REACWT values

that were as large as or larger than steers at every measurement period.

Preweaning fat thickness showed little change and was very similar between sexes.

Postweaning, steer weight increased up to about 490 kg and then leveled off.

Ribeye area of the steers was increasing even at the last measurement period, and

REACWT declined until leveling off around 7.2 to 7.7 cm2/45.4 kg, after about 60

d on feed. Fat thickness increased up to about .9 cm and then appeared to level

off. These phenomena were due to steers being removed from the feedlot and

slaughtered when half reached .9 and the other half reached 1.3 cm of outside fat.

Littell (1990) pointed out the difficulties associated with analysis of

repeated measurement data using conventional multivariate and univariate

techniques. Traditionally, repeated measurement data have been analyzed as

"split-plot in time" experiments with individual animals being treated as main-plot

units and the measurements on the animals at particular points in time treated as

the sub-plot units. These techniques present unique problems associated with the

correlation structure and the validity of using such techniques on unbalanced data

is questionable. Additionally, these methods overlook the regression on time, or

as it applies to this study, age. Gumpertz and Pantula (1989) and Littell (1990)

proposed utilizing the Random Coefficient Regression Model to analyze repeated

measures data. This method entails developing regression curves for treatment








49
groups by fitting a regression curve to each experimental unit, and then averaging

the coefficients of the curves over the units. Treatment groups can then be

compared by applying typical analysis of variance procedures to the group means

of the coefficients. This method has been employed in this study to describe and

compare differences that exist in the growth curves of cattle of different sex

condition, frame size, and breed group.


Sex Condition


Table 3-3 presents regression coefficients for weight between steers and

heifers. Weight gain was linear (P<.0001) during the preweaning phase and

steers gained faster (P<.0001) than heifers (.9816 kg/d vs. .8968 kg/d). Figure 3-

1 displays this relationship graphically and provides the regression equations used

to plot these lines. Steers and heifers had similar weights at approximately 30 d

of age; however, steers exhibited faster (P<.0001) growth to weaning. The

postweaning weight gain coefficient for steers is presented in Table 3-3 and the

predicted growth curve is presented graphically in Figure 3-2. The linear

relationship between age and weight is higher for steers postweaning versus

preweaning (1.5215 kg/d vs. .9816 kg/d). A quadratic curve best explains weight

gain in steers postweaning (Figure 3-2). Steers gained weight at a very rapid

rate, during the feedlot phase, from about 300 d of age to 450 d of age. This was

expected since steers were receiving a high energy diet ad libitum and were

slaughtered at constant fat end points of .9 cm or 1.3 cm of subcutaneous fatness.












TABLE 3-3.


REGRESSION COEFFICIENTS BY SEX CONDITION
FOR WEIGHT CHANGES WITH AGE.


Sex condition
Regressiona Steers Heifers P-value
Preweaning. n 99 97

linear .9816 .014 .8968 .014 .0001

quadratic .00068 .0002 .00085 .0002 .4317

Postweaning, n 56

linear 1.5215 .023 N/A

quadratic .0050 .0005 N/A

a Indicates the linear and quadratic regressions of weight on age.








51





250

SSTEERS
200 HEIFERS
200



150



100



50 -



0 1I I
0 50 100 150 200 250

AGE, d

Figure 3-1. Preweaning weight gain by sex condition. Equations
are as follows: steers, weight=23.34 + age(.982), and heifers,
weight=22.30 + age(.897).














600


STEERS

500





S400





300





200 I
200 250 300 350 400 450 500

AGE, d

Figure 3-2. Postweaning weight gain of steers. Equation
as follows: weight=396.68 age(1.90) + age (.005).









Most cattle reach these endpoints while still in the phase of rapid growth.

Huffman et al. (1990) reported on steers of Brahman and Angus breeding and

found average daily gains of 1.69 kg/d for steers fed to .83 cm of subcutaneous fat

to 1.62 kg/d for steers fed to 1.31 cm of subcutaneous fat.

Table 3-4 presents regression coefficients for ribeye area of steers and

heifers. As with weight, steers exhibit faster linear ribeye area growth than heifers

in the preweaning phase (P<.0155). Quadratic curves appear to fit the

preweaning data and are presented graphically in Figure 3-3. Figure 3-3 shows

that steers and heifers had very similar ribeye area measurements at about 30 d of

age. Steers appeared to grow faster than heifers from about 30 to 150 d of age,

and then growth slowed slightly so that steers and heifers had similar ribeye areas

at weaning. Table 3-4 shows linear ribeye area growth in steers is much more

rapid postweaning vs. preweaning. Figure 3-4 shows that steer ribeye area growth

followed weight gain during the postweaning period. Steers were experiencing

rapid weight gain because they were on a high energy diet fed ad libitum, and

were slaughtered when they attained either .9 or 1.3 cm of outside fat, before

muscle development plateaued.

To account for the positive correlation between weight and ribeye area, a

variable was created, REACWT, to assess ribeye area on a relative body weight

basis. Table 3-5 presents regression coefficients by sex condition for REACWT

change with age. During the preweaning phase, the linear response was not

different (P>.05) between steers and heifers; however the quadratic regression












TABLE 3-4. REGRESSION COEFFICIENTS BY SEX CONDITION
FOR RIBEYE AREA CHANGES WITH AGE.

Sex condition
Regressiona Steers Heifers P-value
Preweaning, n 99 97

linear .1390 .004 .1251 .004 .0155

quadratic -.0003 .00006 .00005 .00006 .0013

Postweaning, n 56

linear .2399 .006 N/A

quadratic .0005 .0002 N/A

a Indicates the linear and quadratic regressions of ultrasound ribeye area on age.















45

-- STEERS
40 HEIFERS


35


< 30 -/


25 -
2/
20


15


10
0 50 100 150 200 250

AGE, d

Figure 3-3. Preweaning ribeye area growth by sex condition. Equations
are as follows: steers, ribeye area=9.54 + age(.204) age (.0003),
and heifers, ribeye area=11.94 + age(.135) age (.00005).
















100 i I i 1

STEERS
90


80


70 -


Z 60 -


50 -


40 -

30 I
200 250 300 350 400 450 500

AGE, d

Figure 3-4. Postweaning ribeye area growth of steers. Equation
is as follows: ribeye area=32.667- age(.096) + age (.0005).












TABLE 3-5. REGRESSION COEFFICIENTS BY SEX CONDITION
FOR RIBEYE AREA/45.4 KG LIVE WEIGHT CHANGES WITH AGE.

Sex condition
Regressiona Steers Heifers P-value
Preweaning, n 99 97

linear -.0187 .0011 -.0210 .0011 .1286

quadratic .000006 .00002 .000095 .00002 .0097

Postweaning, n 56

linear -.0033 .0011 N/A

quadratic -.00009 .00002 N/A

a Indicates the linear and quadratic regressions of ultrasound ribeye area/45.5 kg live
weight on age.








58
was different (P<.05) and is expressed graphically in Figure 3-5. This illustrates

clearly that REACWT favors lighter weight cattle, which was a concern expressed

by Turner et al. (1990). Heifers showed a greater rate of decline in REACWT

than steers. Apparently, the growth impetus for ribeye area as a function of

weight is higher in steers than in heifers. Heifers were growing rapidly and ribeye

area was increasing; however, a greater percent of the weight must have been

directed toward growth of other tissues, such as fat or organs associated with the

reproductive tract. Postweaning the linear response was not different (P>.05)

between sexes. Figure 3-6 displays the quadratic response of REACWT on age in

steers. During the postweaning phase, REACWT only ranged from approximately

7 to 8 cm2/45.4kg with the peak corresponding to the period shortly after steers

were placed on feed.

Table 3-6 presents regression coefficients for outside fat thickness between

steers and heifers. Preweaning, there were no differences between the sexes for

fat thickness; however, there was a tendency (P=.0979) for heifers to deposit fat

more rapidly than steers (.0007 cm/d vs .0006 cm/d). Although the difference in

these growth coefficients is small, it may explain, in part, why REACWT declines

at a faster rate in heifers than in steers. As expected, postweaning fat deposition

was rapid for steers (Figure 3-7). Steers increased rapidly in fat deposition soon

after being placed in the feedlot, at about 300 d of age.
















14 I 1

STEERS
HEIFERS

12 -




S10




8-





0 50 100 150 200 250

AGE, d

Figure 3-5. Preweaning change of ribeye area / 45.4 kg live
weight by sex condition. Equations are as follows: steers,
REACWT=12.10 age(.024) + age (.000006), and
heifers, REACWT=13.54 age(.046) + age (.0001).








60







12



STEERS


b0
1 10

It,





8






6 I
200 250 300 350 400 450 500

AGE, d

Figure 3-6. Postweaning change of ribeye area / 45.4 kg live
weight of steers. Equations is as follows: REACWT = .48
+ age(.044) age2(00007).












TABLE 3-6. REGRESSION COEFFICIENTS BY SEX CONDITION
FOR FAT THICKNESS CHANGES WITH AGE.

Sex condition
Regressiona Steers Heifers P-value
Preweaning, n 99 97

linear .0006 .00004 .0007 .00005 .0990

quadratic .000002 .0000009 .000002 .000001 .5952

Postweaning, n 56

linear .0038 .0001 N/A

quadratic .00002 .000003 N/A

a Indicates the linear and quadratic regressions of ultrasound fat thickness on age.















1.4


STEERS
1.2



6 1.0



0 .8



0.6



0.4



0.2
200 250 300 350 400 450 500

AGE, d

Figure 3-7. Postweaning fat thickness growth of steers
Equation is as follows: fat thickness= 1.60 age(.009)
+ age2 (.00002).









Frame Size


The linear effect of age on weight gain was different among frame groups

for both steers and heifers (Table 3-7, Figures 3-8 and 3-9). Smaller frame steers

(FG1 and FG2) grew slower (P<.05) than steers in the larger framed classes

(FG3 and FG4) and all of these groups increased in weight at a slower rate

(P<.05) than steers in FG5. This may be partly explained by the fact that the

large frame steers may weigh less in relation to their mature weight, and therefore

they experience faster growth. These results are in general agreement with

Thonney et al. (1981), who demonstrated that large frame Holstein steers grew

faster than small frame Angus steers. Apparently, the genes that affect growth

also affect frame size. Fitzhugh and Taylor (1971) have shown that mature size

exerts an influence on cattle growth and carcass composition via genetic

relationships to growth rate, maturing rate and weight at the onset of fattening.

Heifers showed the same trend in the preweaning phase with FG1 heifers having

the slowest (P <.05) rate of linear growth. Heifers in FG2 had slower growth

(P<.05) than heifers in FG4, and heifers in FG3 were intermediate and not

significantly different from heifers in FG2 and FG4. Quadratic equations for

weight gain of heifers by frame size classification are shown in Figure 3-9. The

largest frame heifers (FG4) start out heavier and grow at a slightly faster rate

than the other, smaller frame groups. It should be pointed out, however, that

coefficients from heifers in FG4 were calculated from measurements on two

animals and therefore inferences concerning this group should be made with










TABLE 3-7. REGRESSION COEFFICIENTS BY FRAME SIZE
CLASSIFICATION FOR WEIGHT CHANGES WITH
AGE IN STEERS AND HEIFERS.

Frame size classification
Regressiona FG1 FG2 FG3 FG4 FG5 RMSEC
Preweaning
Steers, n 11 22 35 23 8
linear .9064d .9118d .9859e 1.0192e 1.1508f .127
quadratic .0015 .0009 .0006 .0002 .0010 .002
Heifers, n 35 36 24 2 N/A
linear .8343d .9052e .9607ef 1.0738f N/A .117
quadratic .0013d .0010d .00003e .0007de N/A .0004
Postweaning
Steers, n 3 15 20 13 5
linear 1.5802 1.4889 1.4647 1.6433 1.4945 .235
quadratic .2200 .2530 .2400 .2377 .2184 .056
a Indicates the linear and quadratic regressions of live weight on age.
b Frame size calculated by the Beef Improvment Federation method where
smaller numbers equate to smaller frame scores, (FG1 = frame <3, FG2 =
frame 3-4, FG3 = frame 4-5, FG4 = frame 5-6, FG5 = frame >6).
C Standard errors may be calculated by RMSE / In, where RMSE = root mean
square error and n = the number of steers or heifers in each frame size
classification.
def Means within the same row with different superscripts differ (P< .05).








65






300

-FG1
-- -FG2
250 --- FG3
.--- FG4 .* .
....... FG5 -
200 -











50 -
5-- "







50
0 -----------------------




0 50 100 150 200 250

AGE, d
Figure 3-8. Preweaning weight gain of steers among frame size
classifications. Equations are as follows: FG1, weight= 17.06
+ age(.906); FG2, weight=21.89 + age(.912); FG3, weight=
3.24 + age(.986); FG4, weight=26.94 + age(1.010); FG5,
weight=26.06 + age(1.151).















300

FG1
250 FG2
--- FG3 -'
20...0 FG4 /




100 ,'
E ..' ,



50



50


0 ---- i -

0 50 100 150 200 250

AGE, d

Figure 3-9. Preweaning weight gain of heifers by frame size classification.
Equations are as follows: FG1, weight=36.18 + age(.502) + age
(.001); FG2, weight=33.06 + age(.644) + age2(.001); FG3, weight=
22.27 + age(.984) + age (.00003); FG4, weight=46.69 + age(.861) +
age (.0007.









caution. This will hold true for heifers from FG4 throughout this manuscript.

Unexpectedly, postweaning weight regression coefficients for steers were not

different among frame size classifications. The lack of sufficient animal numbers

in FG1 (n=3) and FG5 (n=8), postweaning, may be a contributing factor to the

reason no differences were detected. Tatum et al. (1986), who used USDA feeder

cattle grades to estimate frame size, reported that large frame steers grew at a

faster rate, during a 140 d finishing period, than small frame steers, while medium

frame steers were intermediate.

Significant differences were found for daily increases in ribeye area among

frame size groups of steers (Table 3-8 and Figure 3-10). Steers from FG1 and

FG2 had similar growth rates (P>.05) for ribeye area; however, ribeye area

growth was significantly slower for steers from FG1 and FG2 than for steers from

the other three frame size groups (FG3, FG4, and FG5). The later three groups

did not differ from each other (P>.05). Heifer calves showed a similar trend in

ribeye area growth (Table 3-8 and Figure 3-11). The two smaller frame groups

were not different (P>.05); however, they had significantly slower ribeye area

growth than heifers from FG3. Postweaning, steer ribeye area growth did not

differ among frame size classifications.

Table 3-9 shows that only slight differences in REACWT were found

among frame size groups. Figure 3-12 shows the linear regression of REACWT

on age in preweaning measurements of heifers. Heifers from FG3 showed a

slightly slower rate of decline in REACWT with increasing age, than FG1 and











TABLE 3-8. REGRESSION COEFFICIENTS BY FRAME SIZE
CLASSIFICATION FOR RIBEYE AREA CHANGES WITH AGE
IN STEERS AND HEIFERS.

Frame size classification
Regressiona FG1 FG2 FG3 FG4 FG5 RMSEc
Preweaning
Steers, n 11 22 35 23 8
linear .1194d .1230d .1446e .1476e .1606e .038
quadratic -.0001 -.0001 -.0003 -.0005 -.0004 .0007
Heifers, n 35 36 24 2 N/A
linear .1143d .1180d .1517e .1228de N/A .038
quadratic .000008 .00002 -.00021 -.00037 N/A .0004
Postweaning
Steers, n 3 15 20 13 5
linear .2200 .2530 .2400 .2377 .2184 .056
quadratic .0013 .0009 .0004 .0002 -.0003 .001
a Indicates the linear and quadratic regressions of ultrasound ribeye area on age.
b Frame size calculated by the Beef Improvment Federation method where smaller
numbers equate to smaller frame scores, (FG1 = frame <3, FG2 = frame 3-4, FG3
= frame 4-5, FG4 = frame 5-6, FG5 = frame >6).
C Standard errors may be calculated by RMSE / In, where RMSE = root mean
square error and n = the number of steers or heifers in each frame size
classification.
def Means within the same row with different superscripts differ (P< .05).








69






50

FG1
45 FG2
--- FG3 ,'
...... FG4 -
40 ...... FG5 .


35

.;' //
30 .,' /


25 .' .,
25 0,

20


15


10 I I I
0 50 100 150 200 250

AGE, d
Figure 3-10. Preweaning ribeye area growth of steers among
frame size classifications. Equations are as follows: FG1,
ribeye area=10.72 + age(.119); FG2, ribeye area= 12.50
+ age(.123); FG3, ribeye area=11.97 + age(.145); FG4,
ribeye area= 12.60 + age(.148); FG5, ribeye area=14.50 +
age(.161).








70






50

45 FG1


40 FG4 / .F'G


35


30 ..... Go
30
-'/
25 -


20 ,


15

10
0 50 100 150 200 250

AGE, d

Figure 3-11. Preweaning ribeye area growth of heifers among
frame size classification. Equations are as follows: FG1,
ribeye area=11.56 + age(.114); FG2, ribeye area= 12.70 +
age(.118); FG3, ribeye area=11.97 + age(.152); FG4, ribeye
area=14.20 + age(123).











TABLE 3-9. REGRESSION COEFFICIENTS BY FRAME SIZE
CLASSIFICATION FOR RIBEYE AREA/45.4 KG LIVE WEIGHT
CHANGES WITH AGE IN STEERS AND HEIFERS.

Frame size classification
Regressiona FG1 FG2 FG3 FG4 FG5 RMSEc

Preweaning
Steers, n 11 22 35 23 8
linear -.0198 -.0168 -.0197 -.0181 -.0193 .012
quadratic .00006 .00004 -.00002 -.00002 .000003 .0003
Heifers, n 35 36 24 2 N/A
linear -.0220d -.0235d -.0163e -.0130de N/A .009
quadratic .00009 .00013 .00005 -.00003 N/A .0001
Postweaning
Steers, n 3 15 20 13 5
linear -.0084 -.0040 -.0011 -.0045 -.0043 .011
quadratic .00008 -.00010 -.00012 -.00006 -.00015 .0003
a Indicates the linear and quadratic regressions ultrasound ribeye area/45.4 kg live
weight on age.
b Frame size calculated by the Beef Improvment Federation method where smaller
numbers equate to smaller frame scores (FG1 = frame <3, FG2 = frame 3-4, FG3
= frame 4-5, FG4 = frame 5-6, FG5 = frame >6).
c Standard errors may be calculated by RMSE / 4n, where RMSE = root mean
square error and n = the number of steers or heifers in each frame size
classification.
de Means within the same row with different superscripts differ (P<.05).















14

-FG1
-- -FG2
FG3
12 ......- FG4
bo
10


B 10










6 --I I I
0 50 100 150 200 250

AGE, d

Figure 3-12. Preweaning change of ribeye area / 45.4 kg live weight
in heifers, by frame size classification. Equations are as follows:
FG1, REACWT=12.52 age(.022); FG2, REACWT=12.63 age(.024);
FG3, REACWT=11.84 age(.016); FG4, REACWT=9.69 age(.013).









FG2 heifers. Ribeye area on a relative body weight basis, REACWT, may be a

useful variable for evaluating ribeye area in cattle of various frame sizes.

Fat thickness changes did not differ (P>.05) among frame size groups

(Table 3-10). Preweaning fat thickness measurement was relatively constant for

both steers and heifers (Table 3-2). Postweaning fat deposition in steers was

rapid (.0029 to .0055 cm/d) because they were on a high energy feedlot diet.

Frame size appears to be an important factor affecting preweaning weight

gain and growth of ribeye. Larger frame cattle grow at a more rapid rate than

smaller frame cattle. Some of this preweaning weight gain appears to come from

an increase in muscle (ribeye area). Growth curves for ribeye area and weight

gain are similar. Postweaning, frame size appears to be unimportant in describing

the differences in growth patterns of steers when slaughtered at constant levels of

fatness. The variable REACWT was not different among frame size groups, and

therefore may be an appropriate variable to use to evaluate ribeye area

measurements in cattle of various frame sizes.


Breed Group


The linear relationship of weight on age for steers was different (P <.05)

among breed groups (Table 3-11). The linear regression coefficients for BG1 and

BG5 were similar (P>.05), and were smaller (P<.05) than coefficients from BG2,

BG3, and BG4. This suggests that the two groups that are partially composed of

straightbred cattle, BG1 (81% to 100% Angus) and BG5 (81% to 100%











TABLE 3-10. REGRESSION COEFFICIENTS BY FRAME SIZE
CLASSIFICATION FOR FAT THICKNESS CHANGES WITH AGE
IN STEERS AND HEIFERS.

Frame size classificationb
Regressiona FG1 FG2 FG3 FG4 FG5 RMSEc

Preweaning
Steers, n 11 22 35 23 8
linear .0006 .0007 .0006 .0005 .0005 .0005
quadratic .000002 .000001 .000002 .000001 .000004 .00001
Heifers, n 35 36 24 2 N/A
linear .0007 .0007 .0009 .0008 N/A .0005
quadratic .000002 .000002 .000003 .000008 N/A .000008
Postweaning
Steers, n 3 15 20 13 5
linear .0055 .0038 .0039 .0038 .0029 .001
quadratic -.0000002 .00003 .00003 .000006 .000007 .00003
a Indicates the linear and quadratic regressions of ultrasound fat thickness changes on
age.
b Frame size calculated by the Beef Improvment Federation method where smaller
numbers equate to smaller frame scores (FG1 = frame <3, FG2 = frame 3-4, FG3
= frame 4-5, FG4 = frame 5-6, FG5 = frame >6).
C Standard errors may be calculated by RMSE / vIn, where RMSE = root mean square
error and n = the number of steers or heifers in each frame size classification.











TABLE 3-11. REGRESSION COEFFICIENTS BY BREED GROUP
FOR WEIGHT CHANGES WITH AGE IN STEERS AND HEIFERS.

Breed groupb
Regressiona 1 2 3 4 5 RMSEc
Preweaning
Steers, n 20 17 25 22 15
linear .8871d 1.0095e 1.0599e 1.0256e .8812d .123
quadratic .0011de .0016e .0012de .0006d -.0018f .001
Heifers, n 28 14 25 19 11
linear .8259d .9706e .9265ef .9247e .8679df .120
quadratic .0012d .0016d .0015d .0002e -.0013f .001
Postweaning
Steers, n 7 12 16 15 6
linear 1.5881 1.5619 1.5750 1.4904 1.2983 .230
quadratic .0100d .0091d .0054e .0017f -.0023fg .005
a Indicates the linear and quadratic regressions of weight on age.
b Breed groups were from known Brahman and Angus matings and were
segregated into groups based on the following percentages of Angus breeding; 1
= 100 81 % Angus, 2 = 80 61 % Angus, 3 = 60 41 % Angus, 4 = 40 21
% Angus, and 5 = 20 0 % Angus.
c Standard errors may be calculated by RMSE / "n, where RMSE = root mean
square error and n = the number of steers or heifers in each breed group.
defg Means within the same row with different superscripts differ (P<.05).









Brahman), had slower (P<.05) weight gain during the preweaning phase than

BG2, BG3, and BG4. Table 3-11 shows the quadratic regression coefficients for

steers are different (P<.05) among breed groups and the quadratic equations are

plotted graphically in Figure 3-13. The coefficient for BG2 is larger (P<.05) than

the coefficient for BG4, while BG1 and BG3 are intermediate and not

significantly different from BG2 and BG4. The coefficient for BG5 is negative

and smaller (P<.05) than all other breed groups and therefore the plotted line

from the equation takes a different shape (Figure 3-13). Calves from BG5 started

out at lighter weights than the other breed group; however, these steers grew at a

faster rate during the first 100 d of life. After this point, growth appeared to slow

somewhat for the BG5 calves and they eventually had the lightest weights at

weaning.

Preweaning heifer data, by breed group, showed trends very similar to

steers. The linear coefficient for preweaning weight gain for BG1 was

significantly smaller than coefficients for BG2, BG3, and BG4, while the

coefficient for BG5 was smaller (P<.05) than the coefficient for BG2. Quadratic

equations for heifers are different among breed groups. The coefficients show a

decreasing trend with increasing Brahman breeding. Coefficients from BG1, BG2,

and BG3 are similar (P>.05) and larger (P<.05) than coefficients from BG4,

which were larger (P<.05) than coefficients from BG5. These curves are plotted

in Figure 3-14. The curve for the group with the highest percentage Brahman

breeding (BG5) shows a very slight leveling at about 100 d of age, whereas the














300

BG1
250 BG2 2-
--- BG3 4/
...... BG4 / /
200 BG 5



200






50 -

0
0 -------------------
0 50 100 150 200 250

AGE, d

Figure 3-13. Preweaning weight gain of steers by breed group (BG).
Equations are as follows: BG 1, weight=37.85 + age(.606)
2 2
+ age (.001); BG 2, weight=40.71 + age(.577) + age (.002);
BG3, weight=34.73 + age(.752) + age (.001); BG4, weight=29.6,
+ age(.873) + age (.0006); BG5, weight=2.03 + age(1.363) age
(.002).















300

BG1
250 BG 2
BG3 /
*.-..- BG4 .
...... BG 5 0".
200- BG5, -


150


100



50


0 --------------------
0 50 100 150 200 250

AGE, d

Figure 3-14. Preweaning weight gain of heifers by breed group (BG).
Equations are as follows: BG1, weight=37.44 + age(.512) + age
2
(.001); BG2, weight=35.28 + age .598) + age (.002); BG3,
weight=40.67 + age (.514) + age (.0002); BG4, weight=24.21 +
age(.893) + age (.0002); BG5, weight=5.95 + age(123) age (.001).








79
curves for heifers in BG1, BG2, and BG3 all showed an upward trend during this

age period. Heifers from BG4 had a weight growth curve that was almost linear

during the preweaning phase.

Table 3-11 also shows growth coefficients for steers postweaning. Linear

coefficients for steers were not significant; however, there was a tendency (P=.12)

for the groups with lower percentage of Brahman breeding (BG1, BG2, and BG3)

to have a faster rate of growth during the postweaning phase than BG5. The

quadratic coefficients were different among breed groups of steers and the

equations are plotted in Figure 3-15. The intercepts of the curves are quite

different, with the higher percentage Angus calves weighing the most at weaning

and the higher percentage Brahman calves weighing the least. There was a

backgrounding period of 75 d after weaning, before the steers were placed in the

feedlot, during which time steers from BG1 and BG2 lost weight. Table 3-12

gives the regression coefficients for ribeye area changes with age among breed

groups. During the preweaning phase, steers and heifers from BG1 had the

slowest (P<.05) linear growth of ribeye area. The other four breed groups were

not statistically different; however, there appeared to be an increasing trend with

increasing percentage Brahman breeding. Figure 3-16 depicts the preweaning

linear trends of ribeye area growth in steers. Breed groups 2 through 4 all show a

similar (P>.05) relationship between ribeye area and age, while BG1 shows a

significantly slower (P<.05) rate of ribeye area growth. Figure 3-17 shows the

quadratic equations for heifer ribeye area growth by breed group, and again the








80






700

BG 1
600 BG2 /
-BG 3

500 BG5
----- BG 4


500 -

300 -



200- .


100
200 250 300 350 400 450 500

AGE, d

Figure 3-15. Postweaning weight gain of steers by breed group (BG).
Equations are as follows: BG1, weight=1039.2 age(5.61) + age
(.010); BG2, weight=865.2 age(4.73) + age (.009); BG3, weight
=416.4 age(2.05) + age (.005); BG4, weight=11.9 + age(.344)
2 BG, weight=380.3 + age(2.86) age(.002).
+ age (.002); BG5, weight=-380.3 + age(2.86) age (.002).











TABLE 3-12. REGRESSION COEFFICIENTS BY BREED GROUP
FOR RIBEYE AREA CHANGES WITH AGE IN
STEERS AND HEIFERS.

Breed group
Regressiona 1 2 3 4 5 RMSEc

Preweaning
Steers, n 20 17 25 22 15
linear .1077d .1401e .1470e .1461e .1550e .036
quadratic -.00016 -.00026 -.00027 -.00034 -.00054 .0007
Heifers, n 28 14 25 19 11
linear .1021d .1444e .1263e .1339e .1411e .038
quadratic .00007d .00009d .00006d -.0002e -.0004e .0004
Postweaning
Steers, n 7 12 16 15 6
linear .2723 .2604 .2246 .2366 .2106 .054
quadratic .00111 .00004 .00033 .00068 .00067 .001
a Indicates the linear and quadratic regressions of ultrasound ribeye area on age.
b Breed groups were from known Brahman and Angus matings and were
segregated into groups based on the following percentages of Angus breeding; 1
= 100 81 % Angus, 2 = 80 61 % Angus, 3 = 60 41 % Angus, 4 = 40 21
% Angus, and 5 = 20 0 % Angus.
c Standard errors may be calculated by RMSE / vn, where RMSE = root mean
square error and n = the number of steers or heifers in each breed group.
de Means within the same row with different superscripts differ (P<.05).















50

BG1
45 .- -
BG 2 .
--- BG3 ,3
40 --. BG4 ./
N..... BG5 .,

U 35 -


30 -


25 -


20


15

10 I
0 50 100 150 200 250

AGE, d

Figure 3-16. Preweaning ribeye area growth of steers among breed
groups (BG). Equations are as follows: BG1 ribeye area= 14.91
+ age(.108); BG2, ribeye area=11.91 + age(.140); BG3, ribeye area
=12.04 + age(.147); BG4, ribeye area=13.07 + age(.146); BG5,
ribeye area=9.66 + age(.156).








83





50


BG1 2
45
45 BG2 /

SBG3 /
40 ......- BG4 .'
.....- BG5 "/.'d"
35 -.

S30

m 25
20 ^- .




15 -

10 I
0 50 100 150 200 250

AGE, d

Figure 3-17. Preweaning ribeye area growth of heifers by breed
group (BG). Equations are as follows: BG1, ribeye area=13.00
+age(.080) + age (.00007); BG2, ribeye area= 12.80 + age
(.125) + age2(.00009); BG3, ribeye area=12.90 + age(.122)
+ afe (.000006); BG4, ribeye area= 10.87 + age(.1881 -
age (.0002); BG5, ribeye area=7.86 + age(.224) age (.0004).









group with the highest percentage Angus breeding (BG1) producing a dissimilar

ribeye area growth curve. Quadratic coefficients from BG4 and BG5 are negative

and smaller (P<.05) than coefficients from the other three breed groups. As was

the case with weight (Figure 3-14), curves from BG5 showed a leveling around

100 d of age while curves from the other groups showed an upturn. Postweaning,

there was a tendency (P = .13) for steers with a greater percentage of Brahman

breeding to have slower ribeye area growth.

Table 3-13 shows regression coefficients by breed group for REACWT. As

with the frame size analysis, no differences were noted among breed groups

during the preweaning phase. Differences among breed groups were significant

during the postweaning phase. The quadratic regression of REACWT on age in

steers is graphically displayed in Figure 3-18. Coefficients from BG1, BG2, and

BG3 were not different (P>.05); however, coefficients for REACWT from BG2

were more negative (P<.05) that those from BG4. The quadratic curve for BG5

takes a drastically different shape than curves from BG1, BG2, and BG3. The

reason for this difference is unknown.

Table 3-14 provides regression coefficients by breed group for fat thickness

changes with increasing age. As discussed in Table 3-2, there was very little

change in fatness during the preweaning phase. Figure 3-19 shows the range of

fat thickness change during the preweaning phase only spanned about .2 cm, and

therefore, any breed group differences were probably of little practical

significance. However, it should be noted that quadratic coefficients of heifers











TABLE 3-13. REGRESSION COEFFICIENTS BY BREED GROUP
FOR RIBEYE AREA/45.4 KG LIVE WEIGHT CHANGES WITH
AGE IN STEERS AND HEIFERS.

Breed group
Regression3 1 2 3 4 5 RMSEc

Preweaning
Steers, n 20 17 25 22 15
linear -.0231 -.0189 -.0182 -.0176 -.0148 .011
quadratic .00002 -.00003 -.000006 .00002 .00003 .0003
Heifers, n 28 14 25 19 11
linear -.0218 -.0212 -.0213 -.0223 -.0156 .010
quadratic .00013 .00012 .00007 .00010 .00002 .0001
Postweaning
Steers, n 7 12 16 15 6
linear -.0008 .0012 -.0040 -.0074 -.0033 .011
quadratic -.00013de -.00027d -.00014de -.0000008ef .0002 .0003
2 Indicates the linear and quadratic regressions of ultrasound ribeye area/45.4 kg live
weight on age.
b Breed groups were from known Brahman and Angus matings and were segregated
into groups based on the following percentages of Angus breeding; 1 = 100 81 %
Angus, 2 = 80 61 % Angus, 3 = 60 41 % Angus, 4 = 40 21 % Angus, and 5 =
20 0 % Angus.
c Standard errors may be calculated by RMSE / "n, where RMSE = root mean
square error and n = the number of steers or heifers in each breed group.
def Means within the same row with different superscripts differ (P<.05).














14

BG1
12 BG 2
--- BG3
...... BG 4
---BG4
S10- '.. BG5


8


S6-/


4

2 8 1
200 250 300 350 400 450 500

AGE, d

Figure 3-19. Postweaning change of ribeye area / 45.4 kg live
weight of steers by breed group (BG). Equations are as follows:
BG1, REACWT=-10.28 + age(.099) age (.0001); BG2,
REACWT=-24.22 + age(.188) age (.0003); BG3, REACWT=
-8.61 + age .097) age (.0001); BG4, REACWT=12.34 age
(.011) age (.000001); BG5, REACWT=30.21 age(.131) +
age (.0020).











TABLE 3-14. REGRESSION COEFFICIENTS BY BREED GROUP
FOR FAT THICKNESS CHANGES WITH AGE IN
STEERS AND HEIFERS.

Breed group
Regressiona 1 2 3 4 5 RMSEc
Preweaning
Steers, n 20 17 25 22 15
linear .0005 .0006 .0008 .0004 .0007 .0005
quadratic .000004 .000002 -.0000002 .000003 .000001 .00001
Heifers, n 28 14 25 19 11
linear .0006 .0009 .0008 .0007 .0009 .0005
quadratic .0000009d .000007e .000002d .000004de .0000009d .000008
Postweaning
Steers, n 7 12 16 15 6
linear .0044d .0044d .0041d .0034de .0023e .001
quadratic .00004d .00003d .00002d .000004e .000005e .00003
a Indicates the linear and quadratic regressions of ultrasound fat thickness on age.
b Breed groups were from known Brahman and Angus matings and were segregated into
groups based on the following percentages of Angus breeding; 1 = 100 81 % Angus,
2 = 80 61 % Angus, 3 = 60 41 % Angus, 4 = 40 21 % Angus, and 5 = 20 0 %
Angus.
c Standard errors may be calculated by RMSE / vn, where RMSE = root mean square
error and n = the number of steers or heifers in each breed group.
de Means within the same row with different superscripts differ (P<.05).














0.6

BG 1
BG 2
---- BG3 /
0.5 -...... BG4 /
....... BG 5 /

u / -

0.4


S................

0.3 -




0.2
0 50 100 150 200 250

AGE, d

Figure 3-19. Preweaning fat thickness growth of heifers by breed
group (BG). Equations are as follows: BG 1, fat thickness=.299
+age(.0003) + age2(.000001); BG2, fat thickness=.342 age
(.0008) + age (.00001); BG3, fat thickness=.295 + age(.0003)
+ age (.000004); BG4, fat thickness=.349 age(.0005) + age
(.000004); BG5, fat thickness=.256 + age(.001) age (.000001).








89
differed among breed groups. Coefficients for BG2 were different (P<.05) from

coefficients for BG1, BG3, and BG5. The curves for the equations are plotted in

Figure 3-19.

Postweaning linear coefficients for fat thickness growth for steers in BG5

are significantly lower than coefficients for steers in BG1, BG2, and BG3. The

quadratic coefficients show much the same trend and the curves from these

equations are plotted in Figure 3-20. These curves are very similar to the

postweaning weight change curves and may help explain why weight decreased for

about 75 d postweaning in BG1 and BG2 while increasing steadily in BG4 and

BG5. It is postulated that higher percentage Angus calves may have had greater

appetite and therefore had more condition at weaning than calves with higher

percentage Brahman breeding. Hargrove (1962) reported that appetite was lower

in calves from predominantly Brahman breeding than for calves from Bos taurus

breeding. During the stress of weaning, calves from BG1 and BG2 lost weight,

most probably in the form of fat. When the calves were placed in the feedlot, at

about 300 d of age, fat deposition then increased dramatically. Additionally, the

higher percentage Brahman calves, BG4 and BG5, were born later in the calving

season and therefore were weaned later than the other breed groups. This

resulted in less time being spent in the backgrounding phase for BG4 and BG5

when compared with the other breed groups.















2.0

BG 1
BG 2
---- BG3 /
1.5 ....... BG4 /
....... BG 5 / ,



1.0






0-0
0. 1 0 I I I "






200 250 300 350 400 450 500

AGE, d

Figure 3-20. Postweaning fat thickness growth of steers by breed
group (BG). Equations are as follows: BG1, fat thickness=
3.71 age(.022) + age (.00004); BG2, fat thickness=2.95 age
(.018) + age (.00003); BG3, fat thickness=1.75 age(.010) 2
+ age (.00002); BG4, fat thickness=-.077 + age(.0005) + age
(.000004); BG5, fat thickness=.316 age(.001) + age (.000005).









Implications


This study provides a unique look at cattle growth from a very young age

to slaughter. Before weaning, steers increase in weight and ribeye area at a faster

rate than heifers, and ribeye area on a relative body weight basis (REACWT)

declines at a faster rate in heifers than in steers. When evaluating growth

preweaning, cattle of different sex conditions should be evaluated separately.

Frame size plays a role in preweaning growth, with large frame cattle showing

faster weight gain and ribeye area growth than small frame cattle; however,

REACWT was not different among frame size groups. Cattle of predominantly

Angus breeding (81% to 100%) tended to have slower weight gain and ribeye

area growth to weaning than did breed groups comprised of 20% to 100%

Brahman breeding. Breed groups were not different for REACWT. This suggests

that for evaluating ribeye area in cattle up to weaning, REACWT may be the best

method across various frame sizes and breed groups. Feedlot steer weight gain

and ribeye area growth were not different among frame size groups or breed

groups. Fat thickness changes during the feedlot period for steers of

predominantly Angus breeding were very different than the other four breed

groups, thus suggesting a breed effect exists for rate of fat deposition.













CHAPTER 4

SUMMARY AND CONCLUSIONS


This manuscript focused on the usefulness of ribeye area as a measurement

of muscularity in beef cattle. The first study was designed to evaluate the

relationship between ribeye area and cutability in a subset of the present cattle

population that represents a relatively narrow range of carcass weight and fat

thickness. Results indicate that ribeye area was moderately correlated with

carcass cutability end points and ribeye area was as valid as any other carcass

measurements evaluated for predicting carcass cutability. However, because

carcasses in this study were chosen to represent a relatively narrow range of

carcass weight and fat thickness, only 12% to 20% of the variation in cutability

could be explained by ribeye area alone. The variables from the USDA yield

grade equations explained from 28% to 38% of the variation in carcass cutability.

There was a tendency for carcasses classified as "above average" for ribeye area to

have greater cutability than those classified as "below average" for cutability.

Individual muscle and bone measurements were included in multiple regression

analysis and were found to be useful predictors of cutability when combined with

standard carcass measurements (R2 = .56 to .65). It was concluded from the first

study that prediction equations designed to predict cutability of "typical" beef









carcasses should include ribeye area along with other carcass measurements. If

feasible, major muscle and/or bone weights should be used as they greatly

enhance the predictive value of regression equations designed to predict carcass

cutability.

The second part of this study addressed cattle growth from a very young

age to slaughter. Serial measurements of weight, ribeye area and fat thickness

measured ultrasonically, and ribeye area/45.4 kg live weight (REACWT) were

regressed on age and growth coefficients were evaluated. Before weaning, steers

increase in weight and ribeye area at a faster rate than heifers, and ribeye area on

a relative body weight basis (REACWT) declines at a faster rate in heifers than in

steers. When evaluating growth preweaning, cattle of different sex conditions

should be evaluated separately. Frame size plays a role in preweaning growth,

with large frame cattle showing faster weight gain and ribeye area growth than

small frame cattle; however, REACWT was not different among frame size

groups. Postweaning, frame size groups were not different for growth patterns of

weight, ribeye area, REACWT and fat thickness. Cattle of predominantly Angus

breeding (81% to 100 %) tended to have slower weight gain and ribeye area

growth to weaning than did breed groups comprised of 20% to 100% Brahman

breeding. Breed groups were not different for REACWT. Feedlot steer weight

gain and ribeye area growth were not different among frame size groups or breed

groups. Fat thickness changes during the feedlot period for steers of

predominantly Angus breeding were very different than the other four breed




Full Text
RIBEYE AREA AS AN INDICATOR OF MUSCLING IN BEEF CATTLE
By
RANDALL DALE HUFFMAN
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
1991

ACKNOWLEDGEMENTS
I would like to express sincere gratitude to Dr. Roger West, chairman, and
Dr. Dwain Johnson, Dr. Don Hargrove, and Dr. Ramon Littell, members of my
supervisory committee, for their guidance and assistance throughout my graduate
program and in the preparation of this manuscript.
I also extend appreciation to Dr. Fred Leak, Dr. Tim Marshall, Dr.
Saundra TenBroeck, Dr. David Prichard and Mr. Don Wakeman for their
assistance, suggestions, and friendship during my graduate program.
There are numerous people who assisted in all phases of my graduate
program: Mr. Larry Eubanks and the crew of the Meat Laboratory; Jerry Wasdin
and the crew at the Pine Acres Research Unit; Janet Eastridge, Debbie Neubauer,
and Ana Zometa of the Meat Science Laboratory; and Mary Beth Forte,
secretary. My sincere thanks goes out to these individuals for their extensive
assistance in data collection and preparation.
Special thanks are expressed to fellow graduate students too numerous to
mention individually-you know who you are! I am indebted for your friendship,
support, and assistance throughout my five years at the University of Florida. I
will always have many fond memories of UF because of you.
11

I am sincerely grateful to my parents, JoAnn and Dale, who were the most
influential forces in my pursuit of this degree. I probably would have stopped
short of this degree if it weren’t for them. For that encouragement and support I
will be forever endebted. I am also thankful to my two very supportive sisters,
Shari and Emily, and my brother-in-law Dennis.
Finally, I express my deepest gratitude to Laura, my wife, for believing in
me and not giving up.

TABLE OF CONTENTS
ACKNOWLEDGEMENTS ii
ABSTRACT vi
CHAPTERS
1 INTRODUCTION 1
2 THE RELATIONSHIP OF RIBEYE AREA TO MUSCLE-TO-
BONE RATIO, LEAN PERCENTAGE AND RETAIL YIELD
AT DIFFERENT FAT TRIM LEVELS 9
Introduction 9
Materials and Methods 12
Carcass Selection 12
Carcass Fabrication 14
Statistical Analysis 17
Results and Discussion 18
Implications 35
3 RIBEYE AREA AND FAT THICKNESS GROWTH DURING
THE EARLY LIFE OF BEEF CALVES 38
Introduction 38
Materials and Methods 41
Experimental Procedure 41
Statistical Analysis 45
Results and Discussion 46
Sex Condition 49
Frame Size 63
Breed Group 73
Implications 91
4 SUMMARY AND CONCLUSIONS 92
IV

REFERENCE LIST 95
BIOGRAPHICAL SKETCH 101
v

Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy
RIBEYE AREA AS AN INDICATOR OF MUSCLING
IN BEEF CATTLE
By
Randall Dale Huffman
December, 1991
Chairperson: Roger L. West
Major Department: Animal Science
This study was undertaken to assess the usefulness of ribeye area (REA) as
a measurement of muscularity in beef cattle and to monitor growth of REA over
time. The first study utilized 54 steers selected to represent six, 22 kg carcass
weight ranges and three REA ranges. Cutability end points were defined as retail
yield at 2.54, .64, and 0 cm fat trim, muscle/bone ratio, fat-free muscle/bone ratio,
and separable lean. Significant correlations existed between REA and carcass
cutability. REA alone explained from 12% to 20% of the variation in cutability.
REA, plus the other yield grade variables, explained from 28% to 38% of the
variation in carcass cutability, depending on the cutability end point. Although not
different (P>.05), carcasses classified as "average," "above average," or "below
average" for REA did show a trend for "above average" carcasses to have greater
cutability than "below average" carcasses. In stepwise regression with other
vi

carcass measurements and some individual muscle and bone weights, REA was
included in all equations predicting cutability (R2=.53 to R2=.65). Part two of
this study provided a look at cattle growth from a very young age to slaughter.
Serial measurements of weight, ultrasound REA and fat thickness, and REA / 45.4
kg of live weight (REACWT) were regressed on age, and growth coefficients were
evaluated. This study suggested that when evaluating growth preweaning, cattle of
different sex condition should be evaluated separately. Frame size played a role
in preweaning growth, as larger framed cattle had faster weight gain and REA
growth than small frame cattle; however, REACWT was not different among
frame sizes. Cattle of predominantly Angus breeding (80% to 100%) had slower
(Pc.05) weight gain and REA growth to weaning than did breed groups
comprised of 20% to 100% Brahman breeding. Breed groups were not different
(P>.05) for REACWT. This suggests that for evaluating REA in cattle up to
weaning, REACWT may be a valid variable to utilize across frame sizes and breed
groups. Postweaning, REA growth was not different among frame sizes or breed
groups. In conclusion, REA is moderately associated with cutability, and REA on
a relative live weight basis is the best method to assess REA growth.
Vll

CHAPTER 1
INTRODUCTION
Animals of all species vary considerably in composition as a result of their
stage of growth, nutritional history, and genetic base (Topel and Kauffman, 1988).
This variation in carcass composition provides a challenge for animal scientists
and livestock producers to identify those animals which will produce the most
"optimum" carcass composition. But how is "optimum" composition defined?
Traditionally, the U.S. beef industry has relied on a strong market for high quality
(high fat) beef, and this has helped to define "optimum" carcass composition.
During the last decade, the link between diet, maintenance of health and the
development of chronic disease has become increasingly questioned. Advice from
national health organizations has influenced consumers to modify their diets by
decreasing consumption of excess calories, fat, saturated fatty acids, and
cholesterol (Call, 1988). Consumers became more health conscious and promptly
demanded leaner meat products, thus modifying the definition of "optimum"
carcass composition. In addition to consumer demands for more healthful meat
products, the 1990s appear to be the decade of environmental awareness, where
the industry will be forced to improve efficiency and eliminate unnecessary waste.
Although this is not a major concern to the livestock and meat industry yet,
1

2
animal agriculture will eventually feel pressure from concerned consumers and
will have to respond by producing animals more economically and more efficiently
than ever before. Many management practices influence the efficiency of animal
growth and there is much room for improvement. Currently, the beef industry
produces more than 5 billion pounds of waste fat trim annually (Byers et al.,
1988). To address this wastefulness and to become more economically efficient,
the industry may again be forced to redefine "optimum" carcass composition.
May (1985) reported that from 1980 to 1984 the percentage of USDA
Yield Grade 1 and 2 beef carcasses increased (30.6% to 45.3%), while the
percentage of USDA Yield Grade 3, 4, and 5 beef carcasses decreased (69.4% to
54.6%). This trend probably continued through the late 1980s as well. Topel
(1986) projected that the ideal carcass in the year 2000 will have the following
characteristics: weight, 320 kg; age, 20 mo; muscle percentage, 73; ribeye area, 97
cm2; fat thickness at the 12th rib, .25 cm; percentage kidney pelvic and heart fat, 1;
and marbling score, practically devoid. Some meat scientists may disagree with
these predictions; however, changes must occur or the livestock and meat industry
will eventually lose market share to competing protein sources. Current trends
and predictions emphasize the need for accurate and precise methods to identify
animal and carcass composition, so that the ever-changing definition of "optimum"
carcass composition will be better understood. Because carcass composition
continues to be an area of interest, so too do the methods used to determine
composition. The most accurate method of determining carcass composition

3
would be to conduct a chemical analysis of the whole carcass (Hankins and Howe,
1946). Obviously this method has many drawbacks and is not applicable to an
industry situation. Consequently, much research has been done to develop
simplified techniques that are accurate and reliable across large groups of animals
and that can be applied to industry situations. Many techniques have been
described which involve chemical analysis of part of the carcass, which render
them impractical for today's high-speed beef slaughter plants (Griffin et al., 1989).
Therefore, methods that can predict carcass composition without destroying the
carcass have been widely studied. One such technique was adopted in 1965 by
USDA and is currently the basis for USDA Yield Grades for Beef. This
technique was developed by Murphey et al. (1960) and was designed to predict
the percentage of boneless retail cuts from the round, loin, rib, and chuck from
162 carcasses using the following equation: % boneless retail cuts = 51.34 - 5.78
(fat thickness, in.) - .462 (% kidney, pelvic, and heart fat) - .0093 (carcass weight,
lb) + .74 (ribeye area, sq. in.). The simple correlation coefficient between the
actual and the predicted yields were highly significant (r = .91). This original
equation has been modified slightly (USDA, 1965) and has been reevaluated by
many other researchers (Abraham et al., 1968; Brackelsberg and Willham, 1968;
Cross et al., 1973; Powell and Huffman, 1973; Abraham et al., 1980). All of these
researchers found the factors utilized in the USDA Yield Grade equation to be
useful predictors of carcass composition; however, numerous published reports
dispute the usefulness of ribeye area in equations that predict cutability. Cole et

4
al. (1960) found that ribeye area only accounted for 18% of the variation in
separable carcass lean and that carcass weight alone was more useful in predicting
separable carcass lean than the multiple regression including both carcass weight
and ribeye area. Ramsey and coworkers (1962) found that when ribeye area was
omitted from yield grade calculations, the resulting yield grades were more closely
related to separable lean and fat than when ribeye area was included. Other
researchers have also concluded that ribeye area should not be utilized in the
yield grade equation (Epley et al., 1970). Despite this discrepancy in the
literature, ribeye area remains in the USDA Yield Grade equation and is the only
direct measurement of carcass muscling.
Research is being conducted on instrument grading of carcasses and ribeye
area is considered one of the variables that should be studied (NCA, 1990). Also,
beef cattle breed associations are currently collecting data to determine expected
progeny differences (EPDs) for carcass traits, and ribeye area is one of the traits
of interest (Cundiff, 1991). Real-time ultrasound will play an important role in
both instrument grading and carcass EPDs. Topel and Kauffman (1988) report
that recent developments in ultrasound technology have led to new interest in
developing ultrasound techniques to predict carcass composition. Stouffer et al.
(1959) first reported on the use of ultrasound for measurement of carcass traits.
Since that time there has been a proliferation of new equipment and improved
techniques. Campbell and Herve (1971) found that ultrasonically determined
cross-sectional area measurements of the longissimus in the lumbar region can be

5
used to predict total muscle in live beef steers as accurately as prediction methods
based on measurements of anatomical dissection. Kempster and Owen (1981)
reported high correlations between ultrasonic measurements of cattle and carcass
composition using several different types of ultrasound units. Simm (1983)
conducted an exhaustive review of the literature concerning the use of ultrasound
to predict carcass composition. In general, he found that ultrasonically measured
muscle areas are the best predictors of dressing percentage, leambone ratio, and
weight of retail cuts, while ultrasonic fat measurements are the best predictors of
lean and fat percentages of the carcass. Stouffer et al. (1961) reported that
operator proficiency was crucial for obtaining reliable ultrasound estimates. Simm
(1983) also found operator proficiency was important in obtaining accurate
estimates. Simm (1983) concluded that marked improvements in the accuracy of
ultrasound were unlikely, since correlations between ultrasonic measurements and
carcass composition are often as high as correlations between actual
measurements of the carcass and carcass composition. Although improvements in
ultrasound equipment have occurred since the publication of that review in 1983,
no literature has addressed how those improvements may have increased the
accuracy and/or precision of ultrasonic measurements for predicting carcass
composition.
Several studies using more sophisticated ultrasound units have been
published in recent years. Bailey et al. (1986) studied the relationship of
ultrasonic estimates to carcass composition and muscle distribution and concluded

6
that for young, Holstein-type bulls that were of similar weight, the accuracy was
too low to justify the commercial use of ultrasonic scans and linear body
measurements. Miller et al. (1988) reported that ultrasound measurements of fat
and ribeye area may be used to predict percentage carcass fat with reliable
precision and accuracy (R2 = .83, rsd = 2.61). Faulkner et al. (1990) reported on
the usefulness of ultrasound 12th rib fat thickness for prediction of cow
composition. They found real-time ultrasound was a very accurate and precise
method of predicting fat measurement in the carcass and combined with live
weight and hip height was an accurate and precise method of estimating
percentage of fat, kilograms of fat, kilograms of fat-free lean, and percentage of
bone. An area that has not been thoroughly studied has been the use of
ultrasound to relate how ribeye area and fat thickness measurements change over
time. McLaren et al. (1989), working with swine, studied ribeye area and fat
growth and examined prediction equations for estimated body composition and
carcass characteristics based on serial real-time ultrasound measurements of loin
eye area and backfat thickness. They concluded that carcass characteristics of
market weight barrows and gilts can be predicted with reasonable accuracy by
early serial weight and ultrasonic measures of backfat and loin eye area. They
stated that this technique might prove valuable to seedstock swine producers
wishing to make early selection decisions. Little research of this type has been
published on beef cattle. Harada et al. (1989), working with Japanese Black bulls,
concluded that ultrasound estimates of fat thickness, ribeye area, and marbling

7
score at 20 and 40 mo of age could be predicted by the use of ultrasound
estimates at 14 mo of age. Turner et al. (1990) reported on the heritability of
ultrasonic measurements in Hereford bulls. They found that ultrasound fat
thickness and ribeye area were less heritable than carcass data traits and that
ribeye area measurements should be adjusted for age, weight, and fat thickness
effects.
The effects of frame size and breed on growth have been well documented;
however, little work has been done on the effect of frame size on ribeye area
changes over time. The concept of frame size, which is indicative of mature size,
is part of the basis for the USDA feeder cattle grading system (USDA, 1979).
Tatum et al. (1986) stated that cattle of large potential mature size (both among
and within breeds) normally grow faster, attain a given degree of maturity at older
ages, and begin to fatten at heavier weights than their smaller contemporaries.
From their study of the effect of feeder cattle frame size on absolute growth rate
and changes in carcass composition, Tatum et al. (1986) concluded that feeder
cattle frame size classification was indicative of differences in absolute growth rate
and slaughter weight at a specified level of fatness. Huffman et al. (1990)
reported that steers of 1/2 and 3/4 Brahman breeding had faster weight gains and
smaller ribeye areas than Angus steers. It is well documented that cattle of
predominantly Brahman breeding produce carcasses with smaller ribeye areas
than their contemporaries of predominantly Bos taurus breeding (Peacock et al.,
1982; Luckett et al., 1975; Crockett et al., 1979; Young et al., 1978; and Lopes,

8
1986); however, information on how Brahman breeding affects ribeye area
changes over time is lacking.
The literature is inconclusive concerning the effectiveness of ribeye area in
predicting carcass cutability. However, assuming that it is a useful measurement,
little work has been done to study how ultrasound technology can be utilized at an
early age to evaluate ribeye area growth and to make early selection decisions. In
general, this dissertation will address two major areas. The first study was
designed to evaluate the relationship between ribeye area and carcass cutability in
a subset of the current cattle population that represents a controlled range of
carcass weight and ribeye area. The second study was designed to examine the
changes that occur over time in ribeye area and fat thickness from a very young
age to slaughter and how sex condition, breed type, and frame size may be
related.

CHAPTER 2
THE RELATIONSHIP OF RIBEYE AREA TO MUSCLE-TO-BONE
RATIO, LEAN PERCENTAGE AND RETAIL YIELD AT DIFFERENT
FAT TRIM LEVELS
Introduction
The U.S. beef industry recently established a Value Based Marketing Task
Force (Cattlemen's Beef Board, 1990) whose primary objective was to "improve
efficiency of beef production by decreasing trimmable fat by 20% and increasing
lean by 6% by 1995, while maintaining taste qualities." How will this be
accomplished? During the late 1980s, retailers reduced fat trim on beef retail
cuts from 1.3 to .4 cm (Cross et al., 1986), which resulted in a 27% reduction in
fat in the retail case (Saveli et al., 1990). These findings show promise for
reaching the goal of reducing trimmable fat by 20% in the next 4 years, but how
will the industry accomplish the goal of increasing lean by 6%?
Many beef cattle breed associations are collecting data needed to estimate
expected progeny differences (EPDs) for ribeye area for beef cattle sire
summaries, so producers will have an objective tool to use for selection of cattle
with more muscle (Cundiff, 1991). Additionally, research is being conducted on
instrumental methods to appraise value of live animals and carcasses, and the
cross-sectional area of the longissimus at the 12th - 13th rib interface (ribeye area)
9

10
is considered one of the variables that should be assessed in this value
determination (NCA, 1990). Questions have been raised concerning the
effectiveness of ribeye area alone, or in combination with other carcass
measurements, as a tool to predict carcass cutability. Cole et al. (1960) reported
that ribeye area was associated with only 18% of the variation of percent
separable carcass lean, and that carcass weight alone was more useful in
predicting separable carcass lean than the multiple regression including both
carcass weight and ribeye area. Ramsey et al. (1962) found that when ribeye area
was omitted from yield grade calculations, the resulting yield grades were more
highly related to separable lean and fat than when ribeye area was included.
Epley et al. (1970) reported that ribeye area contributed little predictive value in
estimating percent retail cuts of the four major primáis. Other researchers,
however, have found that ribeye area contributes significantly to multiple
regression equations designed to predict carcass cutability (Pierce and Hallet,
1961; Brungardt and Bray, 1963; Hedrick et al., 1965; Abraham et al., 1968; Cross
et al., 1973; Powell and Huffman, 1973; and Abraham et al., 1980). Despite the
conflicting findings on the effect of ribeye area on cutability, ribeye area remains
one of the independent variables in the USDA Yield Grade equation (USDA,
1965). Since 1965, USDA Yield Grades for beef carcasses have been the basis
for estimating carcass cutability, and ribeye area is the only direct measurement of
muscling used in the yield grade equation. This equation was developed from a
representative sample of the U.S. cattle population in the 1960s, including

11
carcasses from all classes of sex condition and also from a wide range in carcass
weight, fatness, and muscling. This broad sample allowed for accurate prediction
of cutability (Hedrick, 1968), which was measured as percentage boneless retail
cuts with 1.27 cm of subcutaneous fat.
Several measurements of cutability have been addressed in the literature.
Berg and Butterfield (1966) suggest that when genetic comparisons of lean
content are desired, muscle/bone ratio should be the end point evaluated. This is
based on the fact that fat tissue is of low value and the level of fatness can readily
be controlled environmentally. These authors point out that the market
requirement at any particular time or locality would define the amount of fat
desired. Many authors have assessed the amount of lean, as a percentage of
carcass weight, which can be physically and/or chemically separated from fat and
bone (separable lean). The end point for the yield grade equation is retail yield
(lean and fat) of boneless subprimals trimmed to 1.27 cm of subcutaneous fat.
Retail yield can be expressed at various levels of fatness. As packers and retailers
reduce the amount of fat on boxed subprimals and retail cuts to .4 cm or less,
measurements of muscle, such as ribeye area, may become more important in
predicting cutability.
The current study was designed to evaluate the relationship between ribeye
area and cutability in a subset of the present cattle population that represents a
controlled range of sex class, carcass weight, and ribeye area. It is proposed that
this subset accurately reflects typical beef carcasses (USDA, 1977), where

12
assessment of the relationship between ribeye area and carcass cutability is most
crucial. The specific objectives of this study were: (1) to assess the relationship
between ribeye area and various carcass cutability end points in a population of
carcasses where, within specified carcass weight ranges, ribeye area varied; (2) to
determine if differences in cutability exist between carcasses classified as having
"above average," "average," or "below average" ribeye areas, relative to the USDA
cutability equation; (3) to determine if fat trim level has an affect on the
relationship between ribeye area and cutability; and (4) to develop the optimal
prediction equation for carcass cutability from carcass and individual muscle
measurements.
Materials and Methods
Carcass Selection
Figure 2-1 shows the distribution of carcasses (n=54) selected to represent
six weight ranges (1 = 227 to 249, 2 = 250 to 272, 3 = 273 to 295, 4 = 296 to
318, 5 = 319 to 340, and 6 = 341 to 367 kg) and three ribeye area classifications
(1 = below average, 2 = average, and 3 = above average). Carcasses originated
from crossbred steers in three different feeding trials; however, steers were of
similar age and pre-slaughter management treatments. Steers were produced at
University of Florida beef research units and placed in the feedlot after weaning
and were fed comparable rations until they reached pre-assigned slaughter end
points based on ultrasonic fat thickness measured at the 12th rib. Slaughter end

13
RIBEYE AREA, CM2
Figure 2-1. Number of carcasses selected for each ribeye area
and carcass weight range.

14
point varied between trials from .9 to 1.3 cm of ultrasound subcutaneous fat. Fat
thickness of the live animal was monitored monthly for the first 60 d of the
feeding period and every 2 wk thereafter. Steers were removed from the feedlot
when they reached their pre-assigned slaughter end point and were transported to
either a commercial packing facility or the University of Florida Meat Laboratory
for slaughter.
After routine slaughter procedures, carcasses were chilled for 24 h at 0° to
2° C, ribbed, and graded for USDA quality and yield grade factors by University
of Florida personnel. Within each weight range approximately three carcasses
were selected for each of the three ribeye area classifications. Average ribeye
area was based on the USDA Yield Grade "short cut" adjustment for ribeye area.
Ribeye area was assumed to be average if it was within 3.23 cm2 of the calculated
average for the particular hot carcass weight. Above and below average ribeye
areas spanned a range from 3.23 cm2 to 16.13 cm2 above and below the calculated
average within each weight range.
Carcass Fabrication
One side of each carcass, the side that had more bone after splitting, was
weighed, trimmed of hanging tender, heart fat, channel fat, and other trim
(thymus gland, tendinous edge of diaphragm and spinal cord). The side was then
ribbed between the 12th and 13th ribs, quartered and weighed as outlined by
USDA (1990). Sides were fabricated into wholesale cuts (Koch and Dikeman,

15
1977), trimmed to have not more than 2.54 cm of subcutaneous fat, and the
components weighed. The wholesale cuts were further fabricated into boneless
subprimals trimmed to .64 cm of subcutaneous fat. Weights of exposed
intermuscular fat, trimmed subcutaneous fat, lean trim, and bone plus heavy
connective tissue were recorded. Any intermuscular fat encountered during this
phase of fabrication was kept separate and was combined with other
intermuscular fat during the latter stages of fabrication. Wholesale cut fabrication
procedures were in accordance with Institutional Meat Purchase Specifications
(IMPS) for Fresh Beef (USDA, 1990). The IMPS boneless subprimals obtained
from the forequarter were: IMPS # 107-rib oven prepared (further fabricated into
IMPS #112A-ribeye roll, lip on); IMPS # 114-shoulder clod; IMPS #116A-
chuck roll; IMPS #116B-chuck tender; IMPS # 120-brisket, boneless, deckle off;
IMPS #121E-skirt steak; and IMPS # 117-foreshank. The IMPS boneless
subprimals obtained from the hindquarter were: IMPS # 176-strip loin; IMPS
# 182-sirloin butt; IMPS #189B—full tenderloin; IMPS # 193-flank steak; IMPS
# 167-knuckle; IMPS # 168-top round; and IMPS #170A-bottom round, heel
out.
The following boneless IMPS subprimals were completely trimmed of all
subcutaneous fat, and individual muscles were separated and completely trimmed
of all intermuscular fat: IMPS numbers 112A; 114; 116A; 120; 176; 182; 189; 167;
168; and 170A. The "bridging" and "planing" techniques were followed as outlined
in IMPS (USDA, 1990) to distinguish between intermuscular and subcutaneous

16
fat. Intermuscular fat, subcutaneous fat less than .64 cm, lean trim, and individual
trimmed muscles were separated, weighed, and recorded. Lean trim removed
during this phase of fabrication was kept separate from both hindquarter and
forequarter lean trim.
Lean trim from the forequarter, lean trim from the hindquarter, lean trim
from boneless subprimals and intermuscular fat were kept separate and were
ground two times, mixed thoroughly, subsampled, vacuum packaged and frozen for
subsequent lipid analysis. Lean trim subsamples were thawed overnight in an 8°
to 10° C cooler, then ground finely and mixed prior to moisture and lipid analysis
by the oven drying and soxhlet methods, respectively (AOAC, 1985).
Retail yields were calculated at three subcutaneous fat trim levels: 2.54 cm,
.64 cm, and 0 cm. For each subcutaneous fat trim level, successively leaner
chemical fat percentages were used to calculate lean trim yields. Retail yield at
2.54 cm included IMPS boneless subprimals with not more than 2.54 cm
subcutaneous fat and lean trim adjusted to 25% chemical fat. Retail yield at .64
cm included IMPS boneless subprimals trimmed to .64 cm subcutaneous fat and
lean trim adjusted to 20% chemical fat. Retail yield at 0 cm trim included IMPS
boneless subprimals with all subcutaneous fat removed (with intermuscular fat
intact), and lean trim adjusted to 10% chemical fat.
Muscle/bone ratio was calculated by two methods. First, muscle/bone
ratio was calculated by adding defatted retail muscles to lean trim that had all
"knife separable" fat removed and then dividing this value by total bone weight.

17
Secondly, fat-free muscle/bone ratio was calculated by adding defatted retail
muscles to lean trim adjusted to 0% chemical fat and then dividing by total bone
weight. It should be noted that defatted retail muscles contained intramuscular
fat. Separable lean was calculated by adding defatted retail muscles to lean trim
that had been adjusted to 5% chemical fat.
Additional measurements were made to assess the usefulness of various
parts of the carcass in predicting cutability of the whole carcass. These included
biceps femoris weight/femur weight ratio, longissimus weight, longissimus length,
circumference of longissimus at the 12th rib, and circumference of longissimus at
its widest point.
Statistical Analysis
Means, standard deviations, simple correlations, regression coefficients and
standard partial regression coefficients were computed using SAS (1985). Single
and multiple regression models were utilized to predict cutability end points using
traditional carcass measurements. The General Linear Model procedure was
utilized to determine if cutability differed among carcasses classified into three
groups based on ribeye area. Stepwise regression was used to establish the best
model for predicting cutability using carcass measurements, individual muscle
measurements, and part-whole relationships of the carcass.

18
Results and Discussion
Table 2-1 shows mean values for carcass characteristics and cutability end
points evaluated in this study. Coefficients of variation (CV) were much greater
for carcass measurements (12.3% to 23.3%) than for carcass cutability end points
(3.58% to 8.42%). The variability in ribeye area and hot carcass weight was
established as a result of the selection of carcasses. The carcass selection criteria
placed no restrictions on adjusted fat over the ribeye, and adjusted fat over the
ribeye was variable, .38 cm to 1.52 cm, even though steers were assigned to be
slaughtered when ultrasound fat thicknesses measured either .9, 1.0, or 1.35 cm.
When compared with other experiments designed to assess cutability prediction,
the range in adjusted fat thickness in this study was smaller (Ramsey et al., 1962;
Abraham et al., 1980; May et al., 1990) or comparable (Crouse et al., 1975;
Crouse and Dikeman, 1976). Variability relative to the mean (CV) increases as
fat in the cutability end point decreases. This may be due to the fact that the
means are getting smaller while variability is remaining constant, thus increasing
CV. Additional cut fabrication, and consequent increased chance of cutting error,
required to attain the lower fat end points, may also be a contributing factor.
Simple correlation coefficients (r) between carcass measurements and
carcass cutability are presented in Table 2-2. Ribeye area was correlated with (P
< .01) each of the carcass cutability end points (r = .35 to .45). Correlations for
ribeye area with various measures of cutability are similar to previously published
values: r = .43 for separable lean (Cole et al., 1960), r = .45 for retail yield at .94

19
TABLE 2-1. MEAN CARCASS AND CUTABILITY CHARACTERISTICS
Measurement
Mean
SD
Min.
Max.
CV,%C
Carcass measurements
Ribeye area, cm2
73.2
9.0
57.0
92.0
12.3
Hot carcass weight, kg
290.6
38.7
228.2
367.0
13.3
Adjusted fat over the eye, cm
1.03
.24
.38
1.52
23.3
Estimated KPH fat, %
2.1
.50
1.0
3.0
23.8
Marbling score3
336.7
68.6
170.0
520.0
20.4
USDA yield grade
2.7
.45
1.5
3.5
16.7
Carcass cutabilitv endpoints
Muscle/bone ratio
4.2
.33
3.5
5.2
7.9
Fat-free muscle/bone ratio
3.8
.32
3.2
4.7
8.4
Retail yield at 2.54 cm, %b
72.7
2.6
66.0
79.5
3.6
Retail yield at .64 cm, %b
66.8
2.7
60.4
73.2
4.0
Retail yield at 0 cm, %b
57.4
2.8
51.2
63.3
6.6
Separable lean, %b
55.7
2.7
49.9
61.8
4.9
a Marbling scores are as follows; 100-199 = practically devoid, 200-299 = traces,
300-399 = slight, 400-499 = small, 500-599 = modest.
b Calculated on a percentage of side weight basis.
c CV% = coefficient of variation.

TABLE 2-2. SIMPLE CORRELATION COEFFICIENTS BETWEEN MEASURES OF CARCASS CUT ABILITY
AND CARCASS TRAITS
Measurement
Muscle/bone
ratio
Fat-free
muscle/bone
ratio
Retail
yield, %
2.54 cm
Retail
yield, %
.64 cm
Retail
yield, %
0 cm
Separable
lean, %
Carcass measurements
Ribeye area
.37**
.45**
.36**
.35**
.37**
.39**
Hot carcass weight
.19
.25*
.15
.12
.14
.16
Adj. fat over the eye
.27*
.19
-.26
-.41**
-.43**
-.48**
Estimated KPH fat, %
.10
.05
-.45**
-.39**
-.34*
-.31*
USDA yield grade
-.07
-.16
-.48**
-.56**
-.57**
-.59**
Marbling score
.12
.02
-.22
-.30*
-.26*
-.36**
Muscle measurements
Longissimus circumference3
.24
.31*
.12
.14
.17
.09
Longissimus length, cm
.04
.10
.17
.18
.20
.20
Longissimus weight, kg
.24
.29*
.10
.15
.20
.21
Biceps femoris weight, kg
.32*
.41**
.47**
A¿**
.46
* *
.47
.49**
Femur weight, kg
-.22
-.13
.15
.21
.26
.28*
Biceps/femur ratio
.65**
.65**
.42**
.33*
.29*
*
00
(N
* p < .05, ** p < .01.
3 Circumference of the longissimus was measured at the 12th - 13th rib interface.

21
cm fat trim (Brungardt and Bray, 1963), r = .41 for retail product (Crouse and
Dikeman, 1976), and r = .42 for percent boneless wholesale cuts trimmed to .64
cm (May et al., 1990). Hot carcass weight appeared to have no correlation with
retail yield or separable lean and only a slight correlation (r = .25, P < .05) with
fat-free muscle/bone ratio. Adjusted fat over the ribeye was positively correlated
with muscle/bone ratio (r = .27, P < .05), but was not significantly correlated
with fat-free muscle/bone ratio. This may be partly explained by the fact that the
muscle value used in the muscle/bone ratio calculation contained fat that could
not be removed with a knife, whereas the muscle value in the fat-free
muscle/bone ratio calculation had all physical and chemical fat removed.
Adjusted fat over the ribeye was negatively associated with retail yield at both .64
cm and 0 cm fat trim levels (r = -.41 and r = -.43, P < .05), showing that as
carcass fat increases, retail yield at these fat trim end points decreases. Adjusted
fat over the ribeye was negatively related (r = -.48, P < .01) to separable lean.
These correlations are not as high as reported by other authors: r = -.76 for
separable lean (Ramsey et al., 1962), r = -.82 for major boneless subprimals
(Abraham et al., 1980), and r = -.52 for percent boneless wholesale cuts trimmed
to .64 cm (May et al., 1990). The lower correlations found in this study might be
explained by the narrower range in adjusted fat over the ribeye of the carcasses
when compared to other studies. Steers in this study were slaughtered at similar
fat thicknesses, therefore diminishing the variability in carcass fat thickness.
Estimated kidney, pelvic, and heart fat showed a negative relationship (r = -.45

22
to -.34) with retail yield. These relationships show a decreasing trend as fat trim
end point decreases. Separable lean was also significantly correlated (r = -.31)
with estimated kidney, pelvic, and heart fat. As expected, USDA Yield Grade
was negatively associated (P < .01) with retail yield at all three fat trim end
points, and the relationships appeared to be stronger when cuts were trimmed to
.64 cm or less. Separable lean had the greatest correlation with USDA Yield
Grade (r = -.59, P < .01). USDA Yield Grade was not correlated with (P>.05)
muscle/bone ratio. Marbling score was related to retail yield at .64 cm and 0 cm
fat trim end points (P <.05) and to separable lean (P < .01). This is in
agreement with May et al. (1990) who reported a correlation of r = -.39 between
retail yield at .64 cm and marbling score. The simple correlation between
marbling score and adjusted fat thickness was .47; therefore, carcasses with higher
marbling scores tended to be fatter and therefore had lower yields at higher levels
of marbling.
Correlations of individual muscle weights and measurements are presented
in Table 2-2. Circumference of the longissimus at the 12th - 13th rib interface (r =
.31, P < .05), and longissimus weight (r = .29, P < .05) were correlated with fat-
free muscle/bone ratio. Longissimus length showed no correlation with carcass
cutability. Weight of the biceps femoris, one of the heaviest muscles in the
carcass, was significantly correlated with each of the six cutability end points. The
femur, one of the heaviest bones in the carcass, was positively correlated with
separable lean. When these two values were used to develop a ratio, significant

23
positive correlations were obtained for all cutability end points. Lunt et al. (1985)
reported that the biceps femoris/femur ratio was useful in predicting cutability as
measured by percentage separable lean.
Table 2-3 presents multiple linear regression information using
independent variables of the USDA Yield Grade equation to predict each of six
cutability end points. Each of the four yield grade variables were forced into the
models. All models presented are significant (P < .01).
Ribeye area contributed (P < .01) to both muscle/bone ratio and fat-free
muscle/bone ratio models. Standardized partial regression coefficients (b1) show
ribeye area to be the most important independent variable in these two models.
The b1 coefficients are smaller for separable lean (Pc.Ol) and retail yield (P<.05)
than for muscle/bone ratio, thus suggesting that ribeye area is more useful in
predicting muscle/bone ratio end points. The b1 coefficients do show, however,
that ribeye area was still the most important independent variable in the models
predicting separable lean and retail yield. Crouse et al. (1975) reported that when
carcass weight was held constant, ribeye area was a very useful predictor of yield
of retail cuts; however, when carcass weight was allowed to vary, ribeye area's
usefulness diminished greatly. In this study, hot carcass weight was held relatively
constant in relation to ribeye area.
Hot carcass weight was not a significant variable in any of the models
examined. Griffin et al. (1989), using the same independent variables to predict
yield of major boneless subprimals at different fat trim levels, found very similar

24
TABLE 2-3. MULTIPLE REGRESSION EQUATIONS AND STANDARD
PARTIAL REGRESSION COEFFICIENTS FOR PREDICTING CARCASS
CUT ABILITY END POINTS FROM CARCASS MEASUREMENTS
End point
Intercept
ba
and '
b1
Independent variable1
)
pc
REA
HCW
ADFOE
KPH
R2
Muscle/bone
2.6
b
.02“
-.002
.52'
.01
.28
.0023
ratio
b1
.62
-.24
.37
.02
Fat-free
2.2
b
.02“
-.002
.41*
-.01
.30
.0014
muscle/bone
b1
.66
-.21
.31
-.02
ratio
Retail yield,
71.8
b
.14'
-.01
-.79
-2.3“
.35
.0002
2.54 cm, %d
b1
.49
-.20
-.07
-.43
Retail yield,
68.0
b
.14'
-.02
-3.0'
-1.8'
.37
.0001
.64 cm, %d
b1
.47
-.23
-.26
-.32
Retail yield,
57.8
b
.15’
-.02
-3.35'
-1.46'
.36
.0002
0 cm, %d
b1
.49
-.23
-.28
-.26
Separable
56.2
b
.14“
-.01
-4.1“
-1.2
.38
.0001
lean, %d
b1
.46
-.20
-.35
-.22
* = P < .05, ** = P < .01.
a b = parameter estimate, b1 = standard partial regression coefficient.
b REA = ribeye area, HCW = hot carcass weight, ADFOE = adjusted fat over the ribeye,
KPH = estimated kidney, pelvic, and heart fat.
c P = significance level for the overall regression model.
d Calculated as a percentage of side weight.

25
b values for hot carcass weight: yield at 2.54 cm fat trim, b = -.009; and yield at
.64 cm fat trim, b = -.0109.
Adjusted fat over the ribeye has often been reported as the best single
indicator of cutability (Powell and Huffman, 1973); however, in this study adjusted
fat over the ribeye was not the most important variable in predicting cutability. In
the muscle/bone ratio and fat-free muscle/bone ratio models, adjusted fat over
the ribeye gave b1 values that were half as large as the b1 values for ribeye area.
Adjusted fat over the ribeye was significant in the models predicting retail yield at
.64 cm fat trim (P < .05, b1 = -.26), retail yield at 0 cm fat trim (P < .05, b1 =
-.28), and percentage separable lean (P < .01, b1 = -.35). As would be expected,
adjusted fat over the ribeye became more important as fat percentage in the
cutability end point decreased.
Kidney, pelvic, and heart fat was also included in the models presented in
Table 2-3. It had no significant influence on the prediction of muscle/bone ratio,
fat-free muscle/bone ratio or the percentage of separable lean. Kidney, pelvic,
and heart fat was a factor (P < .01) in the prediction of retail yield at 2.54 cm fat
trim and also was a significant factor in the prediction of retail yield at the
trimmer cutability end points; however, as the amount of fat in the cutability end
point decreased, the importance of kidney, pelvic, and heart fat diminished.
The R2 values reported in Table 2-3 are substantially smaller than those
reported by other authors. Crouse and Dikeman (1976), exploring the
determination of retail product yield in beef, reported an R2 of .69 for an

26
equation containing USDA Yield Grade variables of hot carcass weight, adjusted
fat thickness, ribeye area and kidney, pelvic, and heart fat. Abraham et al. (1980)
evaluated the usefulness USDA Yield Grades and reported R2 = .80 for an
equation containing yield grade variables. May et al. (1990) reported slightly
lower values for predicting retail yield at .64 cm subcutaneous fat trim (R2 = .59).
Murphey et al. (1960) analyzed data of the original study from which the USDA
Yield Grade was derived and reported simple correlation coefficients between the
actual and predicted retail yield were highly significant (r = .91). Hedrick (1968)
stated that when the USDA Yield Grade equation was applied to a more
homogenous group of carcasses than was used in the 1960 study, the relationships
are likely to be lower than originally reported. Griffin et al. (1989) presented
multiple regression equations containing the yield grade variables that had lower
R2 values, (R2 = .38 for predicting retail yield with 2.54 cm subcutaneous fat trim
to R2 = .49 for predicting retail yield with .64 cm of subcutaneous fat trim) more
similar to those reported in Table 2-3.
Figures 2-2 through 2-7 provide a graphical representation of the linear
regression of cutability on ribeye area. All simple regression models were
significant (P <.05) for predicting each of the cutability end points. Each of the
regression lines are rather similar with R2 values ranging from R2 = .12 for retail
yield at .64 cm fat trim to R2 = .20 for fat-free muscle/bone ratio. These data
are in agreement with Cole et al. (1960), who reported that when ribeye area was
used alone to predict separable lean from the carcass, only 18% of the variation

MUSCLE/BONE
RIBEYE AREA, CM 2
Figure 2-2. Linear regression of muscle/bone ratio on
ribeye area.

28
FAT-FREE MUSCLE/BONE
5.0 i
3.0 1 1 1 1—
50.0 60.0 70.0 80.0 90.0
RIBEYE AREA, CM 2
Figure 2-3. Linear regression of fat-free muscle/bone ratio on
ribeye area.
100.0

RETAIL YIELD, %
Figure 2-4. Linear regression of retail yield at 2.54 cm of
subcutaneous fat trim on ribeye area.

RETAIL YIELD, %
75.0
RETAIL YIELD, .64 cm, % â–  59.13 + REA(.10)
R2- .12
70.0
65.0
60.0 ' 1 1 -1—
50.0 60.0 70.0 80.0 90.0
RIBEYE AREA, CM 2
Figure 2-5. Linear regression of retail yield at .64 cm of
subcutaneous fat trim on ribeye area.
100.

RETAIL YIELD, %
Figure 2-6. Linear regression of retail yield at 0 cm of
subcutaneous fat trim on ribeye area.

32
SEPARABLE LEAN, %
Figure 2-7. Linear regression of separable lean percentage
on ribeye area.

33
could be explained. Much of the current literature in this area fails to provide
information regarding the usefulness of ribeye area as a single regressor for
predicting cutability. The single linear regressions were included in this
manuscript to gain a better understanding of the usefulness of ribeye area in
explaining the variation that exists in cutability.
Table 2-4 gives least squares means for carcass cutability end points for
each of the specified ribeye area classifications. These classifications were based
on the USDA Yield Grade "short cut" method for determining ribeye area
adjustment, which utilizes the relationship between ribeye area and hot carcass
weight. A carcass which would have a preliminary yield grade adjustment for
ribeye area of plus or minus .2 would be considered average, an above average
carcass would represent an adjustment of -.2 to -.45, and a below average carcass
would represent an adjustment of +.2 to +.45 to the preliminary yield grade.
This was examined to determine if a carcass that is generally considered as "above
average" for muscling (ribeye area) is actually different in cutability from a carcass
that is generally considered "below average" for muscling. Although there appears
to be a tendancy for the above average group to have higher cutability, no
significant differences were found between classification groups. A greater range
in ribeye area in the carcass population might provide the opportunity to detect
differences between these classification groups; however, in a population selected
to represent the majority of "typical" carcasses, using the ribeye area/weight
relationship to segregate carcasses into cutability groups appears to be ineffective.

34
TABLE 2-4. LEAST SQUARES MEANS FOR CARCASS CUT ABILITY
END POINTS BY RIBEYE AREA CLASSIFICATION WITH ADJUSTED
FAT OVER THE RIBEYE AS A COVARIATE
End point
Ribeye area classification
below average above
SE
P-valueb
Muscle/bone ratio
4.1
4.1
4.3
.07
.12
Fat-free
muscle/bone ratio
3.8
3.8
4.0
.07
.09
Retail yield, 2.54 cm, %3
72.4
72.5
73.2
.62
.41
Retail yield, .64 cm, %3
66.5
66.6
67.1
.60
.29
Retail yield, 0 cm, %3
57.1
57.3
57.9
.61
.21
Separable lean, %3
55.4
55.3
56.2
.58
.18
3 Calculated as a percentage of side weight.
b P-value for the overall least squares model.

35
Table 2-5 presents models to predict cutability generated from stepwise
regression. All carcass measurements, including individual muscle and bone
measurements, were considered as candidate variables. The level for entry into
the model was P < .15 and 12 variables were considered. Ribeye area was the
only carcass measurement that entered into all six of the models. A model
containing ribeye area, biceps femoris weight, and biceps femoris/femur ratio had
an R2 value of .56 for predicting muscle/bone ratio. A slightly different model
was obtained for predicting fat-free muscle/bone ratio (R2 = .58), the only
difference being the substitution of femur weight for biceps femoris weight.
Models for estimating retail yield end points were all different however, each used
ribeye area, estimated kidney, pelvic, and heart fat, and biceps weight.
The results of this study indicate significant, but low relationships exist
between carcass characteristics and carcass cutability. These results are in general
agreement with much of the current literature. Possible explanations for the lack
of predictability of carcass cutability may stem from the fact that the variation in
carcass cutability is relatively low within a population of typical slaughter cattle.
Implications
This study presents a unique look at the usefulness of ribeye area in
equations designed to predict beef carcass cutability. Although current literature
on this subject is not in full agreement, the results presented from this study
indicate that within a population of carcasses that represent the majority of

TABLE 2-5. STEPWISE REGRESSION EQUATIONS FOR PREDICTING CUT ABILITY END POINTS
FROM CARCASS MEASUREMENTS.
EQUATION VARIABLES3
Intercept
REA
HCW
ADFOE
KPH
LMCIR
BICEPS
FEMUR
B\F
C(p)b
R2
Muscle/bone ratio
1.65
.02
-.08
.86
3.6
.56
Fat-free
muscle/bone ratio
1.80
.02
-.11
.52
2.9
.58
Retail yield, 2.54 cm, %c
70.4
.09
-.05
-1.91
1.19
6.2
.53
Retail yield, .64 cm, %c
70.6
.07
-.03
-5.11
-1.14
1.37
5.9
.60
Retail yield, 0 cm, %c
57.1
.09
-.05
-3.32
-.98
1.34
4.4
.57
Separable lean, %c
69.1
.07
-8.2
-.89
1.38
-2.38
2.9
.65
a REA = ribeye area, HCW = hot carcass weight, ADFOE = adjusted fat over the eye, KPH = estimated kidney, pelvic and heart
fat, LMCIR = longissimus muscle circumference at the widest point, BICEPS = biceps femoris weight, B/F = biceps femoris/femur
ratio. Other candidate variables tested but not meeting the P < .15 level for entry into the model, were marbling score, longissimus
circumference at the 12th rib, longissimus length and longissimus weight.
b C(p) criterion is used to avoid overspecification of the regression model.
c Calculated on a percentage of side weight basis.
u>
ON

37
"typical" slaughter cattle, where variation in carcass weight and ribeye area were
controlled, ribeye area was as valid as any other carcass measurement in
predicting beef carcass cutability. However, only 12% to 20% of the variation in
cutability could be explained by ribeye area alone, and there were no statistical
differences in cutability between carcasses classified as "above average," "average,"
or "below average" for ribeye area. Biceps femoris weight, femur weight and the
ratio of these two variables proved valuable as predictors of cutability. Therefore,
programs aimed at determining beef carcass value should incorporate ribeye area
along with other carcass variables into prediction equations. If feasible, major
muscle and/or bone weights could greatly enhance the predictive value of
regression equations designed to predict cutability.

CHAPTER 3
RIBEYE AREA AND FAT THICKNESS GROWTH DURING
THE EARLY LIFE OF BEEF CALVES
Introduction
Animal scientists and cattlemen are faced with the task of identifying
individual breeding cattle that will perform to a specified level for a given trait.
Numerous traits have been evaluated over the years; however, carcass traits have
received a considerable amount of attention during the past decade due to
consumer demands for leaner meat products. Historically, carcass trait
information has been difficult to obtain on breeding cattle because of the
tremendous expense involved in collecting carcass data on progeny of individual
animals. However, during the last decade, the advent of real-time ultrasound has
provided the opportunity for the measurement of ribeye area and fat thickness on
the live animal at a relatively low cost and with reliable accuracy.
The area of cattle growth and development has been of interest to those
involved in animal production for decades, and complete understanding of the
complexities of the bovine growth curve has yet to be attained. Butterfield (1964)
stated that all organisms, except the most simple, undergo changes of form due to
differential growth rates of their constituent parts, and the early works of
Hammond (1921), Palsson (1932), and Huxley (1932) all described developmental
38

39
changes that occur in young, growing ruminant animals. The classical work of
Butterfield (1964), through the use of individual muscle dissection, established
"standard muscle groups", where muscles were grouped according to their relative
postnatal growth. The muscles surrounding the spinal column were classified as
average-developing muscles because their weight in relation to that of total
carcass muscle remained virtually unchanged during post-natal life. Berg and
Butterfield (1966) reported that major changes in the musculature of cattle occur
in the first 6 to 8 months of life. According to the body growth gradient theory,
Huxley (1932) stated that the cross-sectional area of the longissimus muscle at the
last rib was the best method to estimate the degree of muscle development. Since
those early days, numerous other researchers have proven the usefulness of
longissimus muscle area measurement in estimating muscle development (Hedrick
et al., 1965; Powell and Huffman, 1973; and Abraham et al., 1980). Therefore, a
measurement made at weaning (about 7 to 9 mo of age) of the longissimus dorsi
(ribeye area) has the potential to be a reliable predictor of total carcass muscle.
Growth of the longissimus after weaning should be relative to the growth of other
muscle groups of the carcass, since the longissimus muscle was in the group
classified as average developing by Butterfield (1964).
Understanding when to obtain and how to utilize ultrasound information
has become an area of great importance; however, little work has been published
on this subject. Harada et al. (1989), working with Japanese Black bulls,
concluded that ultrasound fat thickness and ultrasound ribeye area at 20 mo and

40
at 30 mo of age could be accurately predicted from ultrasound estimates of fat
thickness and ribeye area at 14 to 16 mo of age. Turner et al. (1990) suggested
that ultrasound measurements should be taken as close to 365 d of age as
possible. From an economical standpoint, however, cattlemen would prefer
obtaining ultrasound measurements early in the growth cycle so that selection
decisions could be made before bulls reach a year of age and incur added
expenses associated with feeding and management. Ultrasound measurements of
ribeye area have the potential to be more accurate on lighter weight cattle, before
the image of the ribeye becomes large and difficult to capture with the ultrasound
equipment. Additionally, if cattle are in good condition (> 10 mm), fat thickness
measurements may be less accurate. Turner et al. (1990) reported that ultrasound
technicians participating in the BIF certification consistently underestimated
actual carcass fat thickness as the animals got fatter. To address the problem of
when ultrasound measurements should be taken, information on how
ultrasonically determined muscle and fat measurements change over time and how
these changes are related to weight changes would be useful.
Berg and Butterfield (1966) found that the amount of fat on cattle is under
a high degree of environmental (management) control. Body composition can
vary greatly in the percentage of fat, depending on stage of growth and plane of
nutrition. Fat thickness is best utilized for describing changes in fatness within
populations of cattle that are of similar age and have been under similar
management.

41
Frame size and/or breed type may have an effect on the growth rate of
ribeye area and fat thickness. Frame size has been shown to have an influence on
cattle growth (BIF, 1990). In general, research shows that small frame cattle tend
to grow at a slower rate, whereas large frame cattle tend to exhibit faster growth
(Tatum et al., 1986). Huffman et al. (1990) found breed type had a significant
effect on weight gain and ribeye area size.
Very little data exist showing the changes that occur over time in ribeye
area and fat thickness from a very young age to slaughter, and how breed type
and/or frame size may be related. Development of growth curves for ribeye area
and fat thickness, both measured by ultrasound, would prove valuable in
understanding how to utilize ultrasound data on young breeding cattle. Therefore,
the objectives of this study were: 1) to develop and describe growth curves for
weight, ultrasound ribeye area, ultrasound ribeye area / 45.4 kg live weight, and
ultrasound fat thickness in cattle; and 2) to determine what effects sex condition,
frame size, and breed type have on these growth curves.
Materials and Methods
Experimental Procedure
One hundred and ninety five steer (n = 99) and heifer (n = 96) calves
were used in the preweaning phase of this study. These calves were from cows of
five breed groups [Angus (A), Brahman (B), 3/4A:l/4B, 1/2A:1/2B, and Brangus
(5/8A: 3/8B) and sires of six breed groups (the five breed groups of dams and

42
1/4A:3/4B)]. Fifteen separate calf breed percentages were represented ranging
from 100% Angus to 100% Brahman; however, for simplification of analysis and
interpretation, calves were classified into five "breed groups" as follows; BG 1 =
81% to 100% Angus, BG 2 = 61% to 80% Angus, BG 3 = 41% to 60% Angus,
BG 4 = 21% to 40% Angus, and BG 5 = 0% to 20% Angus. The number of
calves in each breed group and their distribution are displayed in Table 3-1.
Calves were born on the University of Florida's Pine Acres Research Unit, Citra,
from December, 1988 to May, 1989.
Beginning in February, when the oldest calves were about 2 months of
age, two Beef Improvement Federation (BIF) certified ultrasound technicians
obtained ultrasound images approximately every 4 to 6 wk until weaning. Calves
born early in the season (December to February) were weaned in September, and
calves born late (March to May) were weaned in October. This allowed for four
to seven pre-weaning measurements per calf, depending on the age of the calf.
After weaning, calves were allotted to three different experiments, not
associated with this study, where nutritional treatment was the area of interest.
For this reason some postweaning measurements were not obtained and some
animals were not utilized in the postweaning data set. Heifers were only utilized
in the preweaning period. Fifty-six of the steer calves were utilized in the
postweaning measurements. After weaning, steer calves were maintained on
bahiagrass pasture for approximately 75 d, then placed in the feedlot. Steer
calves were fed a finishing ration for no less than 98 d. Postweaning weight and

43
TABLE 3-1. DISTIRBUTION OF CALVES BY FRAME GROUP AND
BREED GROUP.
Breed group
Frame group
BG1
BG2
BG3
BG4
BG5
Steers
FG1
7
2
2
0
0
FG2
9
4
6
2
1
FG3
3
7
10
9
6
FG4
1
4
5
5
8
FG5
0
0
2
6
0
Heifers
FG1
21
5
6
3
0
FG2
7
5
16
7
1
FG3
0
3
3
9
9
FG4
0
1
0
0
1

44
ultrasound measurements were taken every four weeks until all steers were
slaughtered. Steers were removed from the feedlot and slaughtered when they
reached either .9 or 1.3 cm of ultrasound fat thickness determined at the 12th -
13th rib interface. This allowed for four to eight postweaning weight and
ultrasound measurements, depending on when slaughter occurred.
Hip height was determined at weaning and was used with age to calculate
frame size as described by the Beef Improvement Federation (BIF, 1990). In this
study, frame size ranged from .96 to 7.03. To study the influence of frame size on
growth, calves were grouped into frame size groups which attempted to cover the
range represented, while keeping numbers of calves within classification groups as
even as possible. Five frame size groups were created for steers (FG1 = <3,
FG2 = 3 to 4, FG3 = 4 to 5, FG4 = 5 to 6, FG5 = >6) and four for heifers
(FG1 = <3, FG2 = 3 to 4, FG3 = 4 to 5, FG4 = >5). Table 3-1 shows the
distribution of calves by frame group and breed group.
An Aloka 210-DX B-mode scanner equipped with a UST-5021 probe was
used to obtain cross-sectional images of the longissimus dorsi at the 12th - 13th rib
interface. This probe operates at 3.5 Mhz with an image refreshing rate (frame
rate) of 10 or 20 frames/s. Dynamic, or "real-time" ultrasound images were
recorded on a VHS video cassette recorder and stored for subsequent analysis.
All preweaning ultrasound scans were taken using the single-screen mode.
Because of the size of the ribeye at weaning, a desirable image in the single¬
screen mode could not be obtained; therefore, the split-screen mode had to be

45
utilized. The split-screen mode required the use of a calibrated probe guide that
allows the operator to freeze the left screen that contains half of the desired
picture, and then "match" the right screen to complete the desired picture. As
suggested by Simm (1983), all recorded scans were interpreted by one individual,
a BIF certified technician. Animorph, a video image analysis system, was used to
measure fat thickness and ribeye area from the ultrasound recordings. This
system allows the user to "grab" a single frame from the video tape, thus allowing
an interface with the computer. A trackball was then used to measure fat
thickness at a point, laterally from the spine, three-fourths of the distance across
the longissimus muscle. The trackball was used to trace the area of the
longissimus muscle (ribeye area). Duplicate scans of each animal were measured,
and when the first two values differed by more than 10%, a third measurement
was taken. A mean was computed on the two closest measurements.
Statistical Analysis
All analyses were done separately for preweaning and postweaning
measurements because calves were treated similarly prior to weaning and all one-
hundred and ninety five calves were utilized, however; after weaning calves were
allotted to three different experiments where nutritional treatment was the area of
interest. For this reason some postweaning measurements were not obtained. All
heifers were utilized preweaning. Postweaning measurements were utilized from
fifty-six (n = 56) steer calves that were backgrounded for 75 d and then placed in

46
the feedlot. Because of the repeated measurements on each animal, random
coefficient regression analysis, as described by Gumpertz and Pantula (1989) and
Littell (1990), was used. Linear and quadratic models were fitted to the data with
age as the independent variable and weight, ultrasound ribeye area, ultrasound
ribeye area/45.4kg live weight (REACWT), and ultrasound fat thickness as
dependent variables. Estimates of the intercept and coefficients for the linear and
quadratic terms were obtained for each calf. A new data set was then constructed
which contained estimates of these regression parameters for each calf. Using
estimates of the regression parameters as dependent variables, analysis of variance
procedures were employed to test for differences between steer and heifer calves.
Sex condition was found to have a significant effect on all regression coefficients
except for the quadratic weight term and the linear and quadratic fat thickness
terms. Because of the sex effect, further analyses was conducted separately for
steers and heifers. Analysis of variance procedures were then utilized to
determine the effects of frame size and breed type on the dependent variables.
Least squares means were computed and mean separations were performed and
considered significant at P <.05.
Results and Discussion
Table 3-2 presents means and standard deviations for age, weight, ribeye
area, REACWT, and fat thickness at each measurement time. Table 3-2 shows
that preweaning weight and ribeye area increased over time for both sexes. Steers

TABLE 3-2. MEANS (STANDARD DEVIATION) FOR SERIAL MEASUREMENTS BY SEX.
Measurement
period
Steers
Heifers
Age, d
Weight, kg
REA,
cm2a
REACWT,
cm2b
FAT,
cmc
Age,
d
Weight,
kg
REA,
cm2*
REACWT,
cm2b
FAT,
cmc
February
33 (17)
68.3 (16)
16.3 (5)
10.8 (3)
.33 (.07)
33 (16)
65.0 (16)
15.8 (5)
11.4 (2)
.32 (.04)
March
43 (27)
80.2 (25)
19.3 (6)
11.2 (2)
.34 (.07)
46 (25)
75.3 (25)
19.3 (5)
11.4 (2)
.34 (.08)
April
74 (32)
101.7 (32)
22.8 (6)
10.3 (2)
.33 (.06)
79 (32)
97.5 (32)
21.8 (6)
10.3 (2)
.34 (.06)
May
110 (38)
134.0 (42)
25.8 (8)
9.2 (1)
.32 (.06)
117 (36)
129.8 (39)
25.7 (7)
9.2 (2)
.34 (.11)
July
161 (38)
184.5 (44)
33.6 (8)
8.6 (1)
.37 (.10)
168 (36)
175.8 (40)
325 (7)
8.7 (2)
.39 (.10)
September
209 (38)
233.5 (45)
40.7 (8)
8.1 (1)
.42 (.08)
216 (36)
221.3 (42)
39.2 (9)
8.1 (2)
.46 (.10)
Weaning1
227 (27)
247.5 (40)
41.6 (8)
7.9 (1)
.42 (.07)
226 (30)
225.9 (39)
38.6 (8)
7.9 (1)
.46 (.10)
October
252 (38)
245.7 (41)
39.7 (7)
7.3 (1)
.42 (.08)
259 (36)
231.7 (36)
37.8 (7)
8.3 (1)
.44 (.10)
November
293 (38)
...
...
--
...
...
...
...
...
...
December
303 (38)
259.2 (39)
51.7 (9)
9.1 (1)
.45 (.11)
...
...
...
...
...
January
332 (38)
320.1 (47)
56.8 (9)
8.2 (1)
.59 (.16)
...
...
...
...
...
February
366 (38)
396.4 (59)
64.3 (10)
7.2 (1)
.78 (.16)
...
...
...
...
...
March
390 (38)
438.2 (60)
73.7 (10)
7.7 (1)
.91 (.25)
...
...
...
...
...
April
428 (38)
493.7 (44)
78.0 (14)
7.2 (1)
.92 (.18)
...
...
...
...
...
May
474 (38)
487.2 (76)
81.9 (10)
7.6 (1)
.92 (.16)
...
...
...
...
...
REA = ultrasound ribeye area, cm2.
REACWT = (ultrasound ribeye area, cm2 * 45.4 kg) / weight, kg.
FAT = ultrasound fat thickness, cm.
Weaning occurred in September for older calves (n=142) and October for younger calves (n=56).

48
were heavier and had slightly larger ribeye areas at each measurement period
than heifers. Ribeye area expressed relative to body weight, REACWT, showed a
decreasing trend through the preweaning period and heifers had REACWT values
that were as large as or larger than steers at every measurement period.
Preweaning fat thickness showed little change and was very similar between sexes.
Postweaning, steer weight increased up to about 490 kg and then leveled off.
Ribeye area of the steers was increasing even at the last measurement period, and
REACWT declined until leveling off around 7.2 to 7.7 cm2/45.4 kg, after about 60
d on feed. Fat thickness increased up to about .9 cm and then appeared to level
off. These phenomena were due to steers being removed from the feedlot and
slaughtered when half reached .9 and the other half reached 1.3 cm of outside fat.
Littell (1990) pointed out the difficulties associated with analysis of
repeated measurement data using conventional multivariate and univariate
techniques. Traditionally, repeated measurement data have been analyzed as
"split-plot in time" experiments with individual animals being treated as main-plot
units and the measurements on the animals at particular points in time treated as
the sub-plot units. These techniques present unique problems associated with the
correlation structure and the validity of using such techniques on unbalanced data
is questionable. Additionally, these methods overlook the regression on time, or
as it applies to this study, age. Gumpertz and Pantula (1989) and Littell (1990)
proposed utilizing the Random Coefficient Regression Model to analyze repeated
measures data. This method entails developing regression curves for treatment

49
groups by fitting a regression curve to each experimental unit, and then averaging
the coefficients of the curves over the units. Treatment groups can then be
compared by applying typical analysis of variance procedures to the group means
of the coefficients. This method has been employed in this study to describe and
compare differences that exist in the growth curves of cattle of different sex
condition, frame size, and breed group.
Sex Condition
Table 3-3 presents regression coefficients for weight between steers and
heifers. Weight gain was linear (P<.0001) during the preweaning phase and
steers gained faster (P<.0001) than heifers (.9816 kg/d vs. .8968 kg/d). Figure 3-
1 displays this relationship graphically and provides the regression equations used
to plot these lines. Steers and heifers had similar weights at approximately 30 d
of age; however, steers exhibited faster (P<.0001) growth to weaning. The
postweaning weight gain coefficient for steers is presented in Table 3-3 and the
predicted growth curve is presented graphically in Figure 3-2. The linear
relationship between age and weight is higher for steers postweaning versus
preweaning (1.5215 kg/d vs. .9816 kg/d). A quadratic curve best explains weight
gain in steers postweaning (Figure 3-2). Steers gained weight at a very rapid
rate, during the feedlot phase, from about 300 d of age to 450 d of age. This was
expected since steers were receiving a high energy diet ad libitum and were
slaughtered at constant fat end points of .9 cm or 1.3 cm of subcutaneous fatness.

50
TABLE 3-3. REGRESSION COEFFICIENTS BY SEX CONDITION
FOR WEIGHT CHANGES WITH AGE.
Regression3
Sex condition
P-value
Steers
Heifers
Preweaning, n
99
97
linear
.9816
.014
.8968
±
.014
.0001
quadratic
.00068
±
.0002
.00085
.0002
.4317
Postweaning. n
56
linear
1.5215
±
.023
N/A
quadratic
.0050
±
.0005
N/A
3 Indicates the linear and quadratic regressions of weight on age.

AGE, d
Figure 3-1. Preweaning weight gain by sex condition. Equations
are as follows: steers, weight=23.34 + age(.982), and heifers,
weight=22.30 + age(.897).

WEIGHT, kg
52
AGE, d
Figure 3-2. Postweaning weight gain of steers. Equation
as follows: weight=396.68 - age(1.90) + age2(.005).

53
Most cattle reach these endpoints while still in the phase of rapid growth.
Huffman et al. (1990) reported on steers of Brahman and Angus breeding and
found average daily gains of 1.69 kg/d for steers fed to .83 cm of subcutaneous fat
to 1.62 kg/d for steers fed to 1.31 cm of subcutaneous fat.
Table 3-4 presents regression coefficients for ribeye area of steers and
heifers. As with weight, steers exhibit faster linear ribeye area growth than heifers
in the preweaning phase (P<.0155). Quadratic curves appear to fit the
preweaning data and are presented graphically in Figure 3-3. Figure 3-3 shows
that steers and heifers had very similar ribeye area measurements at about 30 d of
age. Steers appeared to grow faster than heifers from about 30 to 150 d of age,
and then growth slowed slightly so that steers and heifers had similar ribeye areas
at weaning. Table 3-4 shows linear ribeye area growth in steers is much more
rapid postweaning vs. preweaning. Figure 3-4 shows that steer ribeye area growth
followed weight gain during the postweaning period. Steers were experiencing
rapid weight gain because they were on a high energy diet fed ad libitum, and
were slaughtered when they attained either .9 or 1.3 cm of outside fat, before
muscle development plateaued.
To account for the positive correlation between weight and ribeye area, a
variable was created, REACWT, to assess ribeye area on a relative body weight
basis. Table 3-5 presents regression coefficients by sex condition for REACWT
change with age. During the preweaning phase, the linear response was not
different (P>.05) between steers and heifers; however the quadratic regression

54
TABLE 3-4. REGRESSION COEFFICIENTS BY SEX CONDITION
FOR RIBEYE AREA CHANGES WITH AGE.
Regression3
Sex condition
P-value
Steers
Heifers
Preweaning, n
99
97
linear
.1390
±
.004
.1251
±
.004
.0155
quadratic
-.0003
±
.00006
.00005
±
.00006
.0013
Postweaning. n
56
linear
.2399
±
.006
N/A
quadratic
.0005
±
.0002
N/A
Indicates the linear and quadratic regressions of ultrasound ribeye area on age.

55
Figure 3-3. Preweaning ribeye area growth by sex condition. Equations
are as follows: steers, ribeye area=9.54 + age(.204) - age (.0003),
and heifers, ribeye area=11.94 + age(.135) - age (.00005).

RIBEYE AREA,
56
AGE, d
Figure 3-4. Postweaning ribeye area growth of steers. Equation
is as follows: ribeye area=32.667- age(.096) + age (.0005).

57
TABLE 3-5. REGRESSION COEFFICIENTS BY SEX CONDITION
FOR RIBEYE AREA/45.4 KG LIVE WEIGHT CHANGES WITH AGE.
Sex condition
Regression3
Steers
Heifers
P-value
Preweaning, n
99
97
linear
-.0187
.0011
-.0210 ±
.0011
.1286
quadratic
.000006
±
.00002
.000095 ±
.00002
.0097
Postweaning. n
56
linear
-.0033
±
.0011
N/A
quadratic
-.00009
Hh
.00002
N/A
3 Indicates the linear and quadratic regressions of ultrasound ribeye area/45.5 kg live
weight on age.

58
was different (P<.05) and is expressed graphically in Figure 3-5. This illustrates
clearly that REACWT favors lighter weight cattle, which was a concern expressed
by Turner et al. (1990). Heifers showed a greater rate of decline in REACWT
than steers. Apparently, the growth impetus for ribeye area as a function of
weight is higher in steers than in heifers. Heifers were growing rapidly and ribeye
area was increasing; however, a greater percent of the weight must have been
directed toward growth of other tissues, such as fat or organs associated with the
reproductive tract. Postweaning the linear response was not different (P>.05)
between sexes. Figure 3-6 displays the quadratic response of REACWT on age in
steers. During the postweaning phase, REACWT only ranged from approximately
7 to 8 cm2/45.4kg with the peak corresponding to the period shortly after steers
were placed on feed.
Table 3-6 presents regression coefficients for outside fat thickness between
steers and heifers. Preweaning, there were no differences between the sexes for
fat thickness; however, there was a tendency (P = .0979) for heifers to deposit fat
more rapidly than steers (.0007 cm/d vs .0006 cm/d). Although the difference in
these growth coefficients is small, it may explain, in part, why REACWT declines
at a faster rate in heifers than in steers. As expected, postweaning fat deposition
was rapid for steers (Figure 3-7). Steers increased rapidly in fat deposition soon
after being placed in the feedlot, at about 300 d of age.

59
AGE, d
Figure 3-5. Preweaning change of ribeye area / 45.4 kg live
weight by sex condition. Equations are as follows: steers,
REACWT=12.10 - age(.024) + age2(.000006), and
heifers, REACWT=13.54 - age(.046) + age2(.0001).
250

60
AGE, d
Figure 3-6. Postweaning change of ribeye area / 45.4 kg live
weight of steers. Equations is as follows: REACWT = .48
+ age(.044) - age2(00007).

61
TABLE 3-6. REGRESSION COEFFICIENTS BY SEX CONDITION
FOR FAT THICKNESS CHANGES WITH AGE.
Regression*
Sex condition
P-value
Steers
Heifers
Preweaning, n
99
97
linear
.0006
±
.00004
.0007
.00005
.0990
quadratic
.000002
±
.0000009
.000002
±
.000001
.5952
Postweaning. n
56
linear
.0038
Hh
.0001
N/A
quadratic
.00002
±
.000003
N/A
a Indicates the linear and quadratic regressions of ultrasound fat thickness on age.

FAT THICKNESS
62
AGE, d
Figure 3-7. Postweaning fat thickness growth of steers
Equation is as follows: fat thickness=1.60 - age(.009)
+ age2(.00002).

63
Frame Size
The linear effect of age on weight gain was different among frame groups
for both steers and heifers (Table 3-7, Figures 3-8 and 3-9). Smaller frame steers
(FG1 and FG2) grew slower (P<.05) than steers in the larger framed classes
(FG3 and FG4) and all of these groups increased in weight at a slower rate
(P<.05) than steers in FG5. This may be partly explained by the fact that the
large frame steers may weigh less in relation to their mature weight, and therefore
they experience faster growth. These results are in general agreement with
Thonney et al. (1981), who demonstrated that large frame Holstein steers grew
faster than small frame Angus steers. Apparently, the genes that affect growth
also affect frame size. Fitzhugh and Taylor (1971) have shown that mature size
exerts an influence on cattle growth and carcass composition via genetic
relationships to growth rate, maturing rate and weight at the onset of fattening.
Heifers showed the same trend in the preweaning phase with FG1 heifers having
the slowest (P<.05) rate of linear growth. Heifers in FG2 had slower growth
(P<.05) than heifers in FG4, and heifers in FG3 were intermediate and not
significantly different from heifers in FG2 and FG4. Quadratic equations for
weight gain of heifers by frame size classification are shown in Figure 3-9. The
largest frame heifers (FG4) start out heavier and grow at a slightly faster rate
than the other, smaller frame groups. It should be pointed out, however, that
coefficients from heifers in FG4 were calculated from measurements on two
animals and therefore inferences concerning this group should be made with

64
TABLE 3-7. REGRESSION COEFFICIENTS BY FRAME SIZE
CLASSIFICATION FOR WEIGHT CHANGES WITH
AGE IN STEERS AND HEIFERS.
Frame
size classificationb
Regression2
FG1
FG2
FG3
FG4
FG5
RMSEC
Preweaning
Steers, n
11
22
35
23
8
linear
.9064d
.9118d
.9859S
1.0192e
1.1508f
.127
quadratic
.0015
.0009
.0006
.0002
.0010
.002
Heifers, n
35
36
24
2
N/A
linear
,8343d
.9052e
.9607ef
1.0738f
N/A
.117
quadratic
,0013d
.OOIO*3
.00003e
.0007de
N/A
.0004
Postweaning
Steers, n
3
15
20
13
5
linear
1.5802
1.4889
1.4647
1.6433
1.4945
.235
quadratic
.2200
.2530
.2400
.2377
.2184
.056
Indicates the linear and quadratic regressions of live weight on age.
Frame size calculated by the Beef Improvment Federation method where
smaller numbers equate to smaller frame scores, (FG1 = frame <3, FG2 =
frame 3-4, FG3 = frame 4-5, FG4 = frame 5-6, FG5 = frame >6).
Standard errors may be calculated by RMSE / Vn, where RMSE = root mean
square error and n = the number of steers or heifers in each frame size
classification.
Means within the same row with different superscripts differ (P< .05).

65
AGE, d
Figure 3-8. Preweaning weight gain of steers among frame size
classifications. Equations are as follows: FG1, weight= 17.06
+ age(.906); FG2, weight=21.89 + age(.912); FG3, weight=
3.24 + age(.986); FG4, weight=26.94 + age(l.OlO); FG5,
weight=26.06 + age(1.151).

66
Figure 3-9. Preweaning weight gain of heifers by frame size classification.
Equations are as follows: FG1, weight=36.18 + age(.502) + age2
(.001); FG2, weight=33.06 + age(.644) + age2(.001); FG3, weight=
22.27 + age(.984) + age2(.00003); FG4, weight=46.69 + age(.86l) +
age2(.0007.

67
caution. This will hold true for heifers from FG4 throughout this manuscript.
Unexpectedly, postweaning weight regression coefficients for steers were not
different among frame size classifications. The lack of sufficient animal numbers
in FG1 (n = 3) and FG5 (n = 8), postweaning, may be a contributing factor to the
reason no differences were detected. Tatum et al. (1986), who used USDA feeder
cattle grades to estimate frame size, reported that large frame steers grew at a
faster rate, during a 140 d finishing period, than small frame steers, while medium
frame steers were intermediate.
Significant differences were found for daily increases in ribeye area among
frame size groups of steers (Table 3-8 and Figure 3-10). Steers from FG1 and
FG2 had similar growth rates (P>.05) for ribeye area; however, ribeye area
growth was significantly slower for steers from FG1 and FG2 than for steers from
the other three frame size groups (FG3, FG4, and FG5). The later three groups
did not differ from each other (P>.05). Heifer calves showed a similar trend in
ribeye area growth (Table 3-8 and Figure 3-11). The two smaller frame groups
were not different (P>.05); however, they had significantly slower ribeye area
growth than heifers from FG3. Postweaning, steer ribeye area growth did not
differ among frame size classifications.
Table 3-9 shows that only slight differences in REACWT were found
among frame size groups. Figure 3-12 shows the linear regression of REACWT
on age in preweaning measurements of heifers. Heifers from FG3 showed a
slightly slower rate of decline in REACWT with increasing age, than FG1 and

68
TABLE 3-8. REGRESSION COEFFICIENTS BY FRAME SIZE
CLASSIFICATION FOR RIBEYE AREA CHANGES WITH AGE
IN STEERS AND HEIFERS.
Frame size classification15
Regression3
FG1
FG2
FG3
FG4
FG5
RMSEC
Preweaning
Steers, n
11
22
35
23
8
linear
.1194d
.1230d
,1446e
.1476e
.1606e
.038
quadratic
-.0001
-.0001
-.0003
-.0005
-.0004
.0007
Heifers, n
35
36
24
2
N/A
linear
.1143d
.nso*1
.1517e
.1228de
N/A
.038
quadratic
.000008
.00002
-.00021
-.00037
N/A
.0004
Postweaning
Steers, n
3
15
20
13
5
linear
.2200
.2530
.2400
.2377
.2184
.056
quadratic
.0013
.0009
.0004
.0002
-.0003
.001
Indicates the linear and quadratic regressions of ultrasound ribeye area on age.
Frame size calculated by the Beef Improvment Federation method where smaller
numbers equate to smaller frame scores, (FG1 = frame <3, FG2 = frame 3-4, FG3
= frame 4-5, FG4 = frame 5-6, FG5 = frame >6).
Standard errors may be calculated by RMSE / /n, where RMSE = root mean
square error and n = the number of steers or heifers in each frame size
classification.
Means within the same row with different superscripts differ (P< .05).

69
Figure 3-10. Preweaning ribeye area growth of steers among
frame size classifications. Equations are as follows: FG1,
ribeye area=10.72 + age(.119); FG2, ribeye area= 12.50
+ age(.123); FG3, ribeye area= 11.97 + age(.145); FG4,
ribeye area=12.60 + age(.148); FG5, ribeye area=14.50 +
age(.l6l).

RIBEYE AREA
70
AGE, d
Figure 3-11. Preweaning ribeye area growth of heifers among
frame size classification. Equations are as follows: FG1,
ribeye area=11.56 -I- age(.114); FG2, ribeye area= 12.70 +
age(.118); FG3, ribeye area=11.97 + age(.152); FG4, ribeye
area=14.20 + age(123).

71
TABLE 3-9. REGRESSION COEFFICIENTS BY FRAME SIZE
CLASSIFICATION FOR RIBEYE AREA/45.4 KG LIVE WEIGHT
CHANGES WITH AGE IN STEERS AND HEIFERS.
Frame size classificationb
Regression3
FG1
FG2
FG3
FG4
FG5
RMSEC
Preweaning
Steers, n
11
22
35
23
8
linear
-.0198
-.0168
-.0197
-.0181
-.0193
.012
quadratic
.00006
.00004
-.00002
-.00002
.000003
.0003
Heifers, n
35
36
24
2
N/A
linear
-.0235d
-,0163e
-.0130**
N/A
.009
quadratic
.00009
.00013
.00005
-.00003
N/A
.0001
Postweaning
Steers, n
3
15
20
13
5
linear
-.0084
-.0040
-.0011
-.0045
-.0043
.011
quadratic
.00008
-.00010
-.00012
-.00006
-.00015
.0003
Indicates the linear and quadratic regressions ultrasound ribeye area/45.4 kg live
weight on age.
Frame size calculated by the Beef Improvment Federation method where smaller
numbers equate to smaller frame scores (FG1 = frame <3, FG2 = frame 3-4, FG3
= frame 4-5, FG4 = frame 5-6, FG5 = frame >6).
Standard errors may be calculated by RMSE / Vn, where RMSE = root mean
square error and n = the number of steers or heifers in each frame size
classification.
Means within the same row with different superscripts differ (P<.05).

72
Figure 3-12. Preweaning change of ribeye area / 45.4 kg live weight
in heifers, by frame size classification. Equations are as follows:
FG1, REACWT= 12.52 - age(.022); FG2, REACWT=12.63 - age(.024);
FG3, REACVVT=11.84 - age(.0l6); FG4, REACWT=9.69 - age(.013).

73
FG2 heifers. Ribeye area on a relative body weight basis, REACWT, may be a
useful variable for evaluating ribeye area in cattle of various frame sizes.
Fat thickness changes did not differ (P>.05) among frame size groups
(Table 3-10). Preweaning fat thickness measurement was relatively constant for
both steers and heifers (Table 3-2). Postweaning fat deposition in steers was
rapid (.0029 to .0055 cm/d) because they were on a high energy feedlot diet.
Frame size appears to be an important factor affecting preweaning weight
gain and growth of ribeye. Larger frame cattle grow at a more rapid rate than
smaller frame cattle. Some of this preweaning weight gain appears to come from
an increase in muscle (ribeye area). Growth curves for ribeye area and weight
gain are similar. Postweaning, frame size appears to be unimportant in describing
the differences in growth patterns of steers when slaughtered at constant levels of
fatness. The variable REACWT was not different among frame size groups, and
therefore may be an appropriate variable to use to evaluate ribeye area
measurements in cattle of various frame sizes.
Breed Group
The linear relationship of weight on age for steers was different (P<.05)
among breed groups (Table 3-11). The linear regression coefficients for BG1 and
BG5 were similar (P>.05), and were smaller (P<.05) than coefficients from BG2,
BG3, and BG4. This suggests that the two groups that are partially composed of
straightbred cattle, BG1 (81% to 100% Angus) and BG5 (81% to 100%

74
TABLE 3-10. REGRESSION COEFFICIENTS BY FRAME SIZE
CLASSIFICATION FOR FAT THICKNESS CHANGES WITH AGE
IN STEERS AND HEIFERS.
Frame size classification15
Regression3
FG1
FG2
FG3
FG4
FG5
RMSEC
Preweaning
Steers, n
11
22
35
23
8
linear
.0006
.0007
.0006
.0005
.0005
.0005
quadratic
.000002
.000001
.000002
.000001
.000004
.00001
Heifers, n
35
36
24
2
N/A
linear
.0007
.0007
.0009
.0008
N/A
.0005
quadratic
.000002
.000002
.000003
.000008
N/A
.000008
Postweaning
Steers, n
3
15
20
13
5
linear
.0055
.0038
.0039
.0038
.0029
.001
quadratic
-.0000002
.00003
.00003
.000006
.000007
.00003
Indicates the linear and quadratic regressions of ultrasound fat thickness changes on
age.
Frame size calculated by the Beef Improvment Federation method where smaller
numbers equate to smaller frame scores (FG1 = frame <3, FG2 = frame 3-4, FG3
= frame 4-5, FG4 = frame 5-6, FG5 = frame >6).
Standard errors may be calculated by RMSE / /n, where RMSE = root mean square
error and n = the number of steers or heifers in each frame size classification.

75
TABLE 3-11. REGRESSION COEFFICIENTS BY BREED GROUP
FOR WEIGHT CHANGES WITH AGE IN STEERS AND HEIFERS.
Breed group'
5
Regression3
1
2
3
4
5
RMSEC
Preweaning
Steers, n
20
17
25
22
15
linear
.8871d
1.0095e
1.05996
1.0256e
.8812d
.123
quadratic
,0011de
.0016e
.0012de
,0006d
-.0018f
.001
Heifers, n
28
14
25
19
11
linear
.8259d
.9706e
,9265ef
.9247ef
,8679df
.120
quadratic
.0012d
.0016d
.0015d
,0002e
-,0013f
.001
Postweaning
Steers, n
7
12
16
15
6
linear
1.5881
1.5619
1.5750
1.4904
1.2983
.230
quadratic
.OlOO*1
.0091d
.0054e
.0017f
-,0023fg
.005
a Indicates the linear and quadratic regressions of weight on age.
b Breed groups were from known Brahman and Angus matings and were
segregated into groups based on the following percentages of Angus breeding; 1
= 100-81 % Angus, 2 = 80 - 61 % Angus, 3 = 60 - 41 % Angus, 4 = 40 - 21
% Angus, and 5 = 20 - 0 % Angus.
c Standard errors may be calculated by RMSE / Vn, where RMSE = root mean
square error and n = the number of steers or heifers in each breed group.
defs Means within the same row with different superscripts differ (P<.05).

76
Brahman), had slower (Pc.05) weight gain during the preweaning phase than
BG2, BG3, and BG4. Table 3-11 shows the quadratic regression coefficients for
steers are different (Pc.05) among breed groups and the quadratic equations are
plotted graphically in Figure 3-13. The coefficient for BG2 is larger (Pc.05) than
the coefficient for BG4, while BG1 and BG3 are intermediate and not
significantly different from BG2 and BG4. The coefficient for BG5 is negative
and smaller (Pc.05) than all other breed groups and therefore the plotted line
from the equation takes a different shape (Figure 3-13). Calves from BG5 started
out at lighter weights than the other breed group; however, these steers grew at a
faster rate during the first 100 d of life. After this point, growth appeared to slow
somewhat for the BG5 calves and they eventually had the lightest weights at
weaning.
Preweaning heifer data, by breed group, showed trends very similar to
steers. The linear coefficient for preweaning weight gain for BG1 was
significantly smaller than coefficients for BG2, BG3, and BG4, while the
coefficient for BG5 was smaller (Pc.05) than the coefficient for BG2. Quadratic
equations for heifers are different among breed groups. The coefficients show a
decreasing trend with increasing Brahman breeding. Coefficients from BG1, BG2,
and BG3 are similar (P>.05) and larger (Pc.05) than coefficients from BG4,
which were larger (P c .05) than coefficients from BG5. These curves are plotted
in Figure 3-14. The curve for the group with the highest percentage Brahman
breeding (BG5) shows a very slight leveling at about 100 d of age, whereas the

WEIGHT, kg
77
Figure 3-13. Preweaning weight gain of steers by breed group (BG).
Equations are as follows: BG 1, weight=37.85 + age(.606)
+ age2(.001); BG 2, weight=40.71 + aee(.577) + age2(.002);
BG3, weight=34.73 + age(.752) + age (.001); BG4, weight=29.64
+ age(.873) + age2(.0006); BG5, weight=2.03 + age(1.363) - age2
(.002).

78
Figure 3-14. Preweaning weight gain of heifers by breed group (BG).
Equations are as follows: BG1, weight=37.44 + age(.512) + age
(.001); BG2, weight=35.28 + age(.598) + age2(.002); BG3,
weight=40.67 + age (.514) + age (.0002); BG4, weight=24.21 +
age(.893) + age2(.0002); BG5, weight=5.95 + age(123) - age2(.001).

79
curves for heifers in BG1, BG2, and BG3 all showed an upward trend during this
age period. Heifers from BG4 had a weight growth curve that was almost linear
during the preweaning phase.
Table 3-11 also shows growth coefficients for steers postweaning. Linear
coefficients for steers were not significant; however, there was a tendency (P = .12)
for the groups with lower percentage of Brahman breeding (BG1, BG2, and BG3)
to have a faster rate of growth during the postweaning phase than BG5. The
quadratic coefficients were different among breed groups of steers and the
equations are plotted in Figure 3-15. The intercepts of the curves are quite
different, with the higher percentage Angus calves weighing the most at weaning
and the higher percentage Brahman calves weighing the least. There was a
backgrounding period of 75 d after weaning, before the steers were placed in the
feedlot, during which time steers from BG1 and BG2 lost weight. Table 3-12
gives the regression coefficients for ribeye area changes with age among breed
groups. During the preweaning phase, steers and heifers from BG1 had the
slowest (P<.05) linear growth of ribeye area. The other four breed groups were
not statistically different; however, there appeared to be an increasing trend with
increasing percentage Brahman breeding. Figure 3-16 depicts the preweaning
linear trends of ribeye area growth in steers. Breed groups 2 through 4 all show a
similar (P>.05) relationship between ribeye area and age, while BG1 shows a
significantly slower (P<.05) rate of ribeye area growth. Figure 3-17 shows the
quadratic equations for heifer ribeye area growth by breed group, and again the

WEIGHT, kg
80
AGE, d
Figure 3-15. Postweaning weight gain of steers by breed group (BG).
Equations are as follows: BG1, weight= 1039.2 - age(5.6l) -l- age
(.010); BG2, weight=865.2 - age(4.73) + age2(.009); BG3, weight
=416.4 - age(2.05) + age2(.005); BG4, weight=11.9 + age(.344)
-I- age2(.002); BG5, weight=-380.3 + age(2.86) - age2(.002).

81
TABLE 3-12. REGRESSION COEFFICIENTS BY BREED GROUP
FOR RIBEYE AREA CHANGES WITH AGE IN
STEERS AND HEIFERS.
Breed groupb
Regression3
1
2
3
4
5
RMSEC
Preweaning
Steers, n
20
17
25
22
15
linear
.1077d
.1401e
.1461e
.15506
.036
quadratic
-.00016
-.00026
-.00027
-.00034
-.00054
.0007
Heifers, n
28
14
25
19
11
linear
.1021d
.1444e
.1263e
.1339*
.141 le
.038
quadratic
.00007d
.00009d
,00006d
-.0002e
-.0004e
.0004
Postweaning
Steers, n
7
12
16
15
6
linear
.2723
.2604
.2246
.2366
.2106
.054
quadratic
.00111
.00004
.00033
.00068
.00067
.001
Indicates the linear and quadratic regressions of ultrasound ribeye area on age.
Breed groups were from known Brahman and Angus matings and were
segregated into groups based on the following percentages of Angus breeding; 1
= 100 - 81 % Angus, 2 = 80 - 61 % Angus, 3 = 60 - 41 % Angus, 4 = 40 - 21
% Angus, and 5 = 20 - 0 % Angus.
Standard errors may be calculated by RMSE / /n, where RMSE = root mean
square error and n = the number of steers or heifers in each breed group.
Means within the same row with different superscripts differ (P<.05).

82
Figure 3-16. Preweaning ribeye area growth of steers among breed
groups (BG). Equations are as follows: BG1 , ribeye area= 14.91
+ age(.108); BG2, ribeye area=11.91 + age(.140); BG3, ribeye area
= 12.04 + age(.147); BG4, ribeye area=13.07 + age(.146); BG5,
ribeye area=9.66 + age(.156).

Figure 3-17. Preweaning ribeye area growth of heifers by breed
group (BG). Equations are as follows: BG1, ribeye area=13.00
+age(.080) + age2(.00007); BG2, ribeye area=12.80 + age
(.125) + age2(.00009); BG3, ribeye area=12.90 + age(.122)
+ a_^e2(.000006); BG4, ribeye area=10.87 + age(.188) -
age (.0002); BG5, ribeye area=7.86 + age(.224) - age (.0004).

84
group with the highest percentage Angus breeding (BG1) producing a dissimilar
ribeye area growth curve. Quadratic coefficients from BG4 and BG5 are negative
and smaller (P<.05) than coefficients from the other three breed groups. As was
the case with weight (Figure 3-14), curves from BG5 showed a leveling around
100 d of age while curves from the other groups showed an upturn. Postweaning,
there was a tendancy (P = .13) for steers with a greater percentage of Brahman
breeding to have slower ribeye area growth.
Table 3-13 shows regression coefficients by breed group for REACWT. As
with the frame size analysis, no differences were noted among breed groups
during the preweaning phase. Differences among breed groups were significant
during the postweaning phase. The quadratic regression of REACWT on age in
steers is graphically displayed in Figure 3-18. Coefficients from BG1, BG2, and
BG3 were not different (P>.05); however, coefficients for REACWT from BG2
were more negative (P<.05) that those from BG4. The quadratic curve for BG5
takes a drastically different shape than curves from BG1, BG2, and BG3. The
reason for this difference is unknown.
Table 3-14 provides regression coefficients by breed group for fat thickness
changes with increasing age. As discussed in Table 3-2, there was very little
change in fatness during the preweaning phase. Figure 3-19 shows the range of
fat thickness change during the preweaning phase only spanned about .2 cm, and
therefore, any breed group differences were probably of little practical
significance. However, it should be noted that quadratic coefficients of heifers

85
TABLE 3-13. REGRESSION COEFFICIENTS BY BREED GROUP
FOR RIBEYE AREA/45.4 KG LIVE WEIGHT CHANGES WITH
AGE IN STEERS AND HEIFERS.
Breed groupb
Regression3
1
2
3
4
5
RMSEC
Preweaning
Steers, n
20
17
25
22
15
linear
-.0231
-.0189
-.0182
-.0176
-.0148
.011
quadratic
.00002
-.00003
-.000006
.00002
.00003
.0003
Heifers, n
28
14
25
19
11
linear
-.0218
-.0212
-.0213
-.0223
-.0156
.010
quadratic
.00013
.00012
.00007
.00010
.00002
.0001
Postweaning
Steers, n
7
12
16
15
6
linear
-.0008
.0012
-.0040
-.0074
-.0033
.011
quadratic
-,00013de
-,00027d
-.00014de
-.0000008ef
.0002f
.0003
Indicates the linear and quadratic regressions of ultrasound ribeye area/45.4 kg live
weight on age.
Breed groups were from known Brahman and Angus matings and were segregated
into groups based on the following percentages of Angus breeding; 1 = 100 - 81 %
Angus, 2 = 80 - 61 % Angus, 3 = 60 - 41 % Angus, 4 = 40 - 21 % Angus, and 5 =
20 - 0 % Angus.
Standard errors may be calculated by RMSE / Vn, where RMSE = root mean
square error and n = the number of steers or heifers in each breed group.
Means within the same row with different superscripts differ (P<.05).

86
AGE, d
Figure 3-19. Postweaning change of ribeye area / 45.4 kg live
weight of steers by breed group (BG). Equations are as follows:
BG1, REACWT=-10.28 + age(.099) - age2(.0001); BG2,
REACWT=-24.22 + age(.188) - age2(.0003); BG3, REACWT=
-8.61 + agef.097) - age2(.0001); BG4, REACWT=12.34 - age
(.011) - age (.000001); BG5, REACWT=30.21 - age(.131) +
age2(.0020).

87
TABLE 3-14. REGRESSION COEFFICIENTS BY BREED GROUP
FOR FAT THICKNESS CHANGES WITH AGE IN
STEERS AND HEIFERS.
Breed group*5
Regression3
1
2
3
4
5
RMSEC
Preweaning
Steers, n
20
17
25
22
15
linear
.0005
.0006
.0008
.0004
.0007
.0005
quadratic
.000004
.000002
-.0000002
.000003
.000001
.00001
Heifers, n
28
14
25
19
11
linear
.0006
.0009
.0008
.0007
.0009
.0005
quadratic
.0000009**
,000007e
.000002d
,000004de
.0000009**
.000008
Postweaning
Steers, n
7
12
16
15
6
linear
.0044d
.0044d
.0041d
,0034de
,0023e
.001
quadratic
,00004d
.00003d
,00002d
.000004e
,000005e
.00003
Indicates the linear and quadratic regressions of ultrasound fat thickness on age.
Breed groups were from known Brahman and Angus matings and were segregated into
groups based on the following percentages of Angus breeding; 1 = 100 - 81 % Angus,
2 = 80 - 61 % Angus, 3 = 60 - 41 % Angus, 4 = 40 - 21 % Angus, and 5 = 20 - 0 %
Angus.
Standard errors may be calculated by RMSE / Vn, where RMSE = root mean square
error and n = the number of steers or heifers in each breed group.
Means within the same row with different superscripts differ (P<.05).

FAT THICKNESS,
88
AGE, d
Figure 3-19. Preweaning fat thickness growth of heifers by breed
group (BG). Equations are as follows: BG 1, fat thickness=.299
+age(.0003) + age2(.000001); BG2, fat thickness=.342 - age
(.0008^ + age2(.00001); BG3, fat thickness=.295 + age(.0003)
+ age (.000004); BG4, fat thickness=.349 - age(.0005) + age2
(.000004); BG5, fat thickness=.256 + age(.OOl) - age2(.000001).

89
differed among breed groups. Coefficients for BG2 were different (P<.05) from
coefficients for BG1, BG3, and BG5. The curves for the equations are plotted in
Figure 3-19.
Postweaning linear coefficients for fat thickness growth for steers in BG5
are significantly lower than coefficients for steers in BG1, BG2, and BG3. The
quadratic coefficients show much the same trend and the curves from these
equations are plotted in Figure 3-20. These curves are very similar to the
postweaning weight change curves and may help explain why weight decreased for
about 75 d postweaning in BG1 and BG2 while increasing steadily in BG4 and
BG5. It is postulated that higher percentage Angus calves may have had greater
appatite and therefore had more condition at weaning than calves with higher
percentage Brahman breeding. Hargrove (1962) reported that appatite was lower
in calves from predominantly Brahman breeding than for calves from Bos taurus
breeding. During the stress of weaning, calves from BG1 and BG2 lost weight,
most probably in the form of fat. When the calves were placed in the feedlot, at
about 300 d of age, fat deposition then increased dramatically. Additionally, the
higher percentage Brahman calves, BG4 and BG5, were born later in the calving
season and therefore were weaned later than the other breed groups. This
resulted in less time being spent in the backgrounding phase for BG4 and BG5
when compared with the other breed groups.

FAT THICKNESS,
90
AGE, d
Figure 3-20. Postweaning fat thickness growth of steers by breed
group (BG). Equations are as follows: BG1, fat thickness=
3.71 - age(.022) + age2(.00004); BG2, fat thickness=2.95 - age
(.018) + age2(.00003); BG3, fat thickness=1.75 - age(.OlO)
+ age2(.00002); BG4, fat thickness=-.077 + age(.0005) + age2
(.000004); BG5, fat thickness=.316 - age(.OOl) + age2(.000005).

91
Implications
This study provides a unique look at cattle growth from a very young age
to slaughter. Before weaning, steers increase in weight and ribeye area at a faster
rate than heifers, and ribeye area on a relative body weight basis (REACWT)
declines at a faster rate in heifers than in steers. When evaluating growth
preweaning, cattle of different sex conditions should be evaluated separately.
Frame size plays a role in preweaning growth, with large frame cattle showing
faster weight gain and ribeye area growth than small frame cattle; however,
REACWT was not different among frame size groups. Cattle of predominantly
Angus breeding (81% to 100%) tended to have slower weight gain and ribeye
area growth to weaning than did breed groups comprised of 20% to 100%
Brahman breeding. Breed groups were not different for REACWT. This suggests
that for evaluating ribeye area in cattle up to weaning, REACWT may be the best
method across various frame sizes and breed groups. Feedlot steer weight gain
and ribeye area growth were not different among frame size groups or breed
groups. Fat thickness changes during the feedlot period for steers of
predominantly Angus breeding were very different than the other four breed
groups, thus suggesting a breed effect exists for rate of fat deposition.

CHAPTER 4
SUMMARY AND CONCLUSIONS
This manuscript focused on the usefulness of ribeye area as a measurement
of muscularity in beef cattle. The first study was designed to evaluate the
relationship between ribeye area and cutability in a subset of the present cattle
population that represents a relatively narrow range of carcass weight and fat
thickness. Results indicate that ribeye area was moderately correlated with
carcass cutability end points and ribeye area was as valid as any other carcass
measurements evaluated for predicting carcass cutability. However, because
carcasses in this study were chosen to represent a relatively narrow range of
carcass weight and fat thickness, only 12% to 20% of the variation in cutability
could be explained by ribeye area alone. The variables from the USDA yield
grade equations explained from 28% to 38% of the variation in carcass cutability.
There was a tendency for carcasses classified as "above average" for ribeye area to
have greater cutability than those classified as "below average" for cutability.
Individual muscle and bone measurements were included in multiple regression
analysis and were found to be useful predictors of cutability when combined with
standard carcass measurements (R2 = .56 to .65). It was concluded from the first
study that prediction equations designed to predict cutability of "typical" beef
92

93
carcasses should include ribeye area along with other carcass measurements. If
feasible, major muscle and/or bone weights should be used as they greatly
enhance the predictive value of regression equations designed to predict carcass
cutability.
The second part of this study addressed cattle growth from a very young
age to slaughter. Serial measurements of weight, ribeye area and fat thickness
measured ultrasonically, and ribeye area/45.4 kg live weight (REACWT) were
regressed on age and growth coefficients were evaluated. Before weaning, steers
increase in weight and ribeye area at a faster rate than heifers, and ribeye area on
a relative body weight basis (REACWT) declines at a faster rate in heifers than in
steers. When evaluating growth preweaning, cattle of different sex conditions
should be evaluated separately. Frame size plays a role in preweaning growth,
with large frame cattle showing faster weight gain and ribeye area growth than
small frame cattle; however, REACWT was not different among frame size
groups. Postweaning, frame size groups were not different for growth patterns of
weight, ribeye area, REACWT and fat thickness. Cattle of predominantly Angus
breeding (81% to 100 %) tended to have slower weight gain and ribeye area
growth to weaning than did breed groups comprised of 20% to 100% Brahman
breeding. Breed groups were not different for REACWT. Feedlot steer weight
gain and ribeye area growth were not different among frame size groups or breed
groups. Fat thickness changes during the feedlot period for steers of
predominantly Angus breeding were very different than the other four breed

94
groups. Breed groups with 60% to 100% Angus breeding lost fat during a 75 d
backgrounding period, while steers with 40% to 100% Brahman breeding gained
fat throughout the backgrounding and feedlot phase, thus suggesting a breed
effect for the rate of fat deposition. This may be more easily explained the the
fact that the higher percentage Brahman calves spent less time in the
backgrounding phase. This phenomena needs further study.

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measures of ribeye area and fat thickness in yearling Hereford bulls. J.
Anim. Sci. 68:3502.
USDA. 1965. Official United States standards for grades of carcass beef. Title 7,
Ch. 1, Pt 53, Sections 53.102-53.106. June. U. S. C. & M. S. Washington,
DC.
USDA. 1977. Grades of Fed Beef Carcasses. Agr. Marketing Service, Market
Research Report Number 1073, USDA, Washington, DC.
USDA. 1979. Official United States standards for grades of feeder cattle. Agr.
Marketing Serv., USDA, Washington, DC.
USDA. 1990. Institutional Meat Purchase Specifications for Fresh Beef. Agr.
Marketing Service., USDA, Washington, DC.
Young, L.D., L.V. Cundiff, J.D. Crouse, G.M. Smith, and K.E. Gregory. 1978.
Characterization of biological types of cattle. VIII. Postweaning growth
and carcass traits of three-way cross steers. J. Anim. Sci. 46:1178.

BIOGRAPHICAL SKETCH
Randall Dale Huffman was born in Auburn, Alabama, September 11, 1964.
He received his high school diploma from Auburn High School, Auburn,
Alabama, in June, 1982. In the fall of 1982 he enrolled at Auburn University
where he majored in Animal and Dairy Sciences and, in the spring of 1986, he
received the degree of Bachelor of Science. In August, 1986, he accepted a
graduate assistantship from the Department of Animal Science, University of
Florida and, on December 17, 1988 he received the degree of Master of Science.
On that same date, he was wed to Miss Laura Ann Lockard, of Auburn, Alabama.
In January, 1989, he began pursuit of the degree of Doctor of Philosophy, in the
field of meat science, in the Department of Animal Science, University of Florida.
101

I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and
quality, as a dissertation for the degree of Doctor of Philosophy.
e-tz
y
v
RogerjL. West, Chair
Professor of Animal Science
I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and
quality, as a dissertation for the degree of Doctor of Philosophy.
M¿m
D. Dwain Johnsofy/Cochair
Associate Professor of Animal Science
I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and
quality, as a dissertation for the degree of Doctor of Philosophy.
Don D. Hargrove
Professor of Animal Science
I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and
quality, as a dissertation for the degree of Doctor of Philosophy.
Ramon C. Littell
Professor of Statistics
This dissertation was submitted to the Graduate Faculty of the College of
Agriculture and to the Graduate School and was accepted as partial fulfillment of
the requirements for the degree of Doctor of Philosophy.
December, 1991
Dean, College of
Agriculture
Dean, Graduate School

UNIVERSITY OF FLORIDA
3 1262 08556 9993




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