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Relationships Between Body Measurements Obtained on Yearling Brangus Bulls and Measures of Carcass Merit Obtained from Their Steer Clone-Mates1
The Professional Animal Scientist 12:244-249
Relationships Between Body Measurements Obtained on Yearling Brangus Bulls and Measures of Carcass Merit Obtained from Their Steer Clone-Mates1 J.J.8. DILES*,2, R. D. GREENt.3, H. H. SHEPARD*, G. L. MATHIEWS t , L. J. HUGHES*, and M. F. MILLER* *Oepartment of Animal Science and Food Technology, Texas Tech University, Lubbock, TX 79409-2141, and tOepartment of Animal Sciences, Colorado State University, Fort Collins, CO 80523-1171
Serial (every 28 d) measurements of hip height (HH), body length (BL), rump This study was designed to determine length (RL), rump width (RW), shoulder the relationship between ultrasonic and width (SW), round mass (RNMS), linear body measurements of yearling metacarpal length and circumference bulls and percentage retail product (pRP) (MCL and MCC), metatarsal length and of slaughter steers using genetically circumference (MTL and MTC), and identical bulls and steers as experimental ultrasonic measurements of backfat animals. Four groups of Brangus, thickness (BFT), Longissimus muscle second-generation nuclear transfer calves area (LMA), Longissimus muscle depth (two steers and two to four bulls per (LMD), body wall thickness (BWT), clone group) were used in this study. rump fat thickness (RFT), and rump muscle depth (RMD) obtained on each bull from weaning (6 to 7 mo) until 16 to 17 mo of age were regressed on age to 'This work represents a portion of the M.S. obtain 365-d age constant estimates for thesis of the senior author and was supported, the traits. Steers were slaughtered in part, by funding from the Texas State Line between 480 and 520 d of age and Item for Efficient Production of Beef and the percentage of retail cuts (trimmed to J. W. Thornton Endowment. Assistance of S. Y. Gilbert, L. S. Barrett, and M. K. Butler in 0.64 em) was obtained. Genetic correlaprocurement of data is gratefully acknowl- tions of the adjusted traits of the bulls to edged. age-constant percentage retail yield of 2Current address: He2, Box 1181, Utopia, the steers were obtained following TX 78884. Yamada (1962). The highest genetic correlations (p<0.05) with PRP were 3To whom correspondence should be ad0.568, -0.532, and -0.523 with RNMS, dressed. RMD, and BIT, respectively. The best Reviewed by R. C. Albin and E. E. Hatfield. three-variable equation for predicting Sponsored by D. R. Ames. PRP developed from these data included
Abstract
RNMS, RL, and BFT (Rz = 0.80, P=O.OOOl).
(Key Words: Beef Cattle, Genetic Correlation, Retail Yield.)
Introduction Because of impending changes in the way beef cattle are marketed (UValue-Based Marketing"), breed associations and other organizations have become concerned with expanding genetic information on breeding animals to include measures of carcass merit. Progeny testing for carcass merit is the traditional method for accomplishing this objective, however the time and cost involved limits its usefulness. Ultrasound has been viewed as a technology for overcoming some of the problems associated with progeny testingi however, research must be conducted before ultrasound measures can replace, or supplement, progeny testing (7). In particular, perhaps the most critical question deals with whether ultrasonic mea-
Relationship Between Live Animal Measures in Bulls and Carcass Traits of Steers
surements taken from immature breeding animals are the same traits genetically as carcass measures obtained from slaughter animals. Yamada (15) and Dickerson (2) indicated that genetic correlations for similar traits measured in different sexes may be obtained by assuming them to actually be the same trait measured in different environments. These authors concluded that, when the error variance among genetic groups is the same in both environments, the genetic correlation (rg) can be estimated as:
rg =
where 0 2G + 0 21 are ANOVA estimators of the genetic group and the genotype by environment interaction variance components, respectively, obtained from balanced data. In the case of the same trait measured in different sexes, sex may be considered to be the environment. Fernando et al. (5) pointed out, however, that this method only holds if the two traits have identical heritabilities and residual variances. Given genetic identity of cattle between sexes within a cloned genotype, this method should have direct application to studies of live predictors of carcass merit using nuclear transfer experimental animals. This study was designed to determine the genetic relationship between yearling ultrasonic and linear body measurements of bulls and percentage retail product of slaughter steer progeny using groups of nuclear-transfer cloned bull and steer contemporaries as experimental animals.
Materials and Methods Live Measures. DeSCriptions of the NT groups (genotypes A, B, C, and D) that were used in this study have been presented in previous papers 3, 6, 11). Linear and ultrasonic measures used also are the same as those described by Diles et al. (3); however,
only bull measures collected during the 140-d gain-test period were included in this portion of the study. Body weights (WT), various linear body measurements (10), and ultrasonic measures of muscle and fat were obtained simultaneously on bulls and steers beginning 2 wk after weaning at 28-d intervals. These serial measures were collected until 16 to 17 mo of age, and included: 1) hip height (HH, cm); height from ground to lumbar-sacral vertebrae juncture. 2) Body length (BL, cm); distance from point of shoulder to pins. 3) Rump length (RL, cm); distance from hooks to pins. 4) Rump width (RW, cm); measured at point of greatest width through the rump. 5) Shoulder width (SW, cm); measured at point of greatest width through the shoulder. 6) Round mass (RNMS, cm); measured with a flexible tape starting from tuber coxae passing proximal to the hind limb at the gaskin muscle and ending at the sacral-caudal vertebrae juncture. 7) Metacarpal length (MCL, cm); distance between metacarpal lateral tuberOSity and condyle. 8) Metacarpal circumference (MCC, cm); measured with flexible tape at narrowest point. 9) Metatarsal length (MTL, cm); distance between metatarsal lateral tuberosity and condyle. 10) Metatarsal circumference (MTC, cm); measured with flexible tape at narrowest point. 11) Backfat thickness (BFT, cm); measured at the 12th13th rib interface at a point threefourths of the distance from the medial end of the Longissimus muscle area. 12) Longissimus muscle area (LMA, cm2); measured at the 12th13th rib interface. 13) Longissimus muscle depth (LMD, cm); distance across LMA perpendicular to external body surface and passing through acorn fat deposit. 14) Body wall thickness (BWT, cm); measured at 12th-13th rib interface 1 cm ventral to the Longissimus costarum muscle, perpendicular to external body surface. 15) Rump fat thickness (RFT, cm); measured equidistant from vertebral column, tuber ischii and tuber coxae, perpendicular to exter-
245
nal body surface. 16) Rump muscle depth (RMD, cm); depth of Biceps femoris muscle measured in the same location as RFT. Ultrasonic images were obtained with an Aloka 500V ultrasound unit (Corometrics Medical Systems, Wallingford, CT) equipped with a 3.5-MHz, 17-cm scanning width, linear array transducer following procedures as described by Hamlin et al. (8, 9). Excess dirt and debris were removed from each ultrasound measurement site by vigorous brushing. Corn oil (Mazola, CPC, Foodservice, Englewood Cliffs, Nl) was used as a couplant to obtain adequate acoustical contact with the animal. A super-flab stand-off guide (Animal Ultrasound Services, Ithaca, NY) was used to insure proper contact with the curvature of the animal's back during recording of images for BFT, LMA, LMD, and BWT measurements. All ultrasonic images were recorded on a high resolution VHS video cassette recorder aVC HRS6600U,lVC Co. of America, Elmwood Park, Nl) and later interpreted by the same technician with computer software (AniMorphi Woods Hole Educational Associates, Woods Hole, MA) to obtain actual measurements. Carcass Data. Steers were slaughtered between 480 and 520 d of age after approximately 140 to 180 d on feed. Each steer was deprived of feed for 24 h, then weighed just prior to slaughter. Slaughter and retail fabrication was performed following industry standards at the Texas Tech University Meat Science Laboratory. Hot carcass weights (HCW) were obtained within 30 min postmortem. After a 24-h chill (2°C) period, chilled carcass weights (CCW) were obtained, then each carcass was evaluated by trained personnel and assigned USDA yield and quality grades (YG and QG, respectively) . The full right side from each carcass was fabricated into boneless (except as noted below) retail cuts trimmed to not more than 0.64 cm subcutaneous and intermuscular fat. Retail cuts obtained included: clod,
246
Diles et al.
arm section, chuck roll, brisket, rib (including bones), plate (including bones), lean trim (LN, < 30% fat), fat trim (FT, < 30% lean) and bone (BN, including connective tissue) from the forequarter and gooseneck, top round, knuckle, shortloin strip, top butt, ball tip, tri-tip, flap, flank steak, tender loin, LN, FT and BN from the hindquarter. Percentage retail product (PRP) was calculated by dividing the total weight of all cuts above, except for FT and BN, by CCW x 100. Data Analysis. Single estimates for each serially measured trait of each bull were required for describing the relationship of these measures to final PRP measured in the carcass of the steers. Obtaining these estimates required predicting each animal's measurements at a constant age. Age was chosen as an endpoint, rather than weight, because other performance measures are taken on ageconstant bases according to the guidelines of the Beef Improvement Federation (BIF, 1996). Adjustment for differences in age was accomplished by regressing serial measures on age. The equations produced for each trait by bull then were used to predict 365-d estimates for that trait. Methods described by Yamada (15) were used to obtain genetic correlation estimates from these data. Genetic correlation coefficients were estimated for the relationship be-
tween each of the predicted live measures of the bulls and PRP of the steers. Equations for predicting PRP from age adjusted live measures were developed using stepwise regression for maximum R2 improvement. All statistical analyses were performed using SAS~ (12) software.
Results and Discussion Descriptive carcass characteristics are presented for each steer in Table 1. The PRp, percentage waste fat (PFT, total FT divided by CCW x 100) and percentage waste bone (PBN, total BN divided by CCW x 100) are given in Table 2 for each steer. Slaughter dates were originally set so that one steer of each genotype would be slaughtered at one of two age-constant endpoints. This schedule was interrupted by a case of urinary calculi in one of the steers of genotype D. All other steers were slaughtered according to schedule; however, age at slaughter appeared to have little impact on the compositional traits of PRp, PFT, and PBN. Also, it is interesting to note that no apparent trend was observed regarding age and USDA marbling score. The extreme difference in carcass Longissimus muscle area within genotype C was due to one of the animals having been apparently stunted from birth.
TABLE 1. Descriptive characterlstlcs a of Individual steer carcasses. Glib
All A/2
CIl C/2 Oil 0/2
F/1 F/2
Age
HCW
(d)
(kg)
488 517 482 520 485 517 481 482
342.0 335.2 353.8 312.0 284.2 315.2 351.6 286.6
CCW
CBF
(cm) 326.6 311.0 334.2 293.2 266.0 308.2 345.0 281 .2
0.97 0.97 1.14 1.09 0.94 0.91 0.86 0.81
CLMA
KPH
(cm 2)
(%)
63.9 62.6 52.9 53.5 51.0 63.9 63.2 58.1
2.0 2.0 3.0 2.5 1.5 1.5 2.0 1.5
MRB
YG
Sm 10 SI40 Sm 60 Mt40 SI80 Sm 30 Sm 80 Sm 50
4.4 4.0 5.9 5.2 4.3 3.8 4.1 3.5
aHCW =hot carcass weight, CCW =chilled carcass weight, CSF =carcass backfat thickness, CLMA = carcass longissimus muscle area, KPH = kidney, pelvic and heart fat, MRS = USDA marbling (intramuscular fat) score, YG = USDA yield grade. blndividual steers identified by genotype/individual steer number within genotype.
Age and weight constant estimates for live measures of bulls are given in Table 3 for linear measurement traits and in Table 4 for ultrasonic measurement traits. Linear measurement traits tended to be more uniform within groups of clones than did ultrasonic measurement traits. Part of this difference could be attributed to the error involved in interpreting the ultrasonic images. The structure of these data presented some difficulties when using the method described by Yamada (15) for calculating genetic correlations. Because more bulls than steers were present in two of the genotypes, the data may be considered unbalanced, thus the correlations obtained by this method could be biased and unreliable according to Fernando et al. (5) . In general studies with unbalanced data, where genotype describes type, breed, sire group, etc., variations of maximum likelihood techniques as described by Schaeffer et al. (13) would be required to take into account all information available (12). However, the fact that the animals in each group were genetically identical, presented other options. The first option would be to obtain least squares means for each of the adjusted traits of the bulls and PRP of the steers. This option would eliminate bias from the correlation estimates by balancing the data to one observation for each sex within each genotype, but also would eliminate all of the within genotype variation still present in both the bull and steer traits. The second option involved the pairing of each bull measurement within a genotype with PRP of each steer of the same genotype. This option would decrease the variability within genotypes to a lesser degree, but would increase the number of observations in the data set. The second option was used in this study, because it would conserve more of the observed variability in the data. Increasing the number of observations within a data set in this manner under almost any other circumstances would have been a major
247
Relationship Between Live Animal Measures in Bulls and Carcass Traits of Steers
tion of bull measurement trait and PRP within a genotype will have an equal chance of best representing the relationship between the traits for Retail Waste Waste that genotype. The net effect of Gill product fat bone restructuring the data in this manner is a decrease in the variation on both -------(%)------the bull and the steer sides of the Nl 64.17 20.85 14.95 data set resulting from repeated N2 62.97 19.84 17.37 observations. Overall variation C/1 58.60 27.88 13.52 would be reduced greatest in the C/2 58.92 24.78 16.30 genotypes with more than two bulls, 19.57 0/1 61.28 19.15 because each PRP would be repeated 0/2 62.27 19.09 18.64 four and three times for genotypes B F/1 65.74 17.31 16.95 F/2 67.90 15.33 16.77 and C, respectively. Age-constant measurement traits Significantly (P<0.05) correlated to alndividual steers identified by PRP included RW, RNMS, MTC, BFT, genotype/individual steer number within genotype. and RMD with correlation coefficients of 0.424, 0.568, 0.470, -0.523, and -0.532, respectively. Nonsignificant (P>0.05) correlations were error. Although it cannot be proved obtained for BL, RL, SW, MCL, MCC, to be wholly without error in this MTL, LMA, LMD, BWT, and RFT. Although these results are encourcase, this method appeared to best fit the circumstances of this study. aging, other reports have been qUite The use of genetically identical contradictory. In a recently reported animals in this study implies that, study (4), genetiC correlation estiwithin a genotype, each estimate of a mates between ultrasound traits on bull measurement trait has an equal yearling bulls as compared to carcass chance of being the best estimate for measures in slaughter steers were that genotype. Likewise, each opposite in magnitude and sign. The calculation of PRP within a genotype authors used their results to venture a has an equal chance of being best. It hypothesis that stated that these follows that each possible combinagenetic correlations are caused by TABLE 2. Compositional characteristics of steer carcasses.
differences in degree of maturity in the different sexes due to the animals being measured at different points on their growth curve. Clearly, the contradictory nature of these results raises questions of whether the relationship between yearling bull ultrasound measures and slaughter steer carcass measures is understood. Results from stepwise regression of predicted live measures of bulls on PRP of steers appear in '!able 6. The paired data set described above also was used for the development of these regression models. Again, these results must be interpreted with caution, but the same justification used above additionally applies to this analysis. The data set is not complete with only one outcome per genotype reported, when more than one was actually observed. The best three-variable equation for predicting PRP developed from stepwise regression in this study included RNMS, RW, and BFT (RZ = 0.80, P=O.OOOl), whereas the best two-variable model included RW and RNMS (RZ = 0.48, P=0.OO19). BF!' and RNMS were identified as important variables, each controlling 32% of the observed variation in PRP. When the model was restricted to include only BFT and LMA, predictive power was much lower (RZ = 0.20, P=0.0468).
TABLE 3. Predicted 36S-d values for linear measurement traits· of bulls. Glib
HH
BL
RL
RW
SW
Nl
126.8 126.8 124.9 123.8 125.9 128.2 129.5 128.8 130.3 129.0 127.3
136.9 138.5 135.5 136.1 138.3 144.6 134.0 133.9 134.2 140.1 140.0
46.7 47.8 46.4 44.5 45.6 47.5 49.4 47.4 48.7 44.6 46.9
48.0 46.9 49.2 49.0 47.9 47.9 48.2 49.0 51.2 50.1 51.6
46.4 45.8 47.1 46.6 46.9 47.7 45.3 46.8 45.4 46.5 46.8
N2 C/1 C/2 C/3 C/4 0/1 0/2 0/3 F/l F/2
RNMS (cm) 1840 1826 1805 1800 1788 1835 1836 1825 1858 1816 1872
MCL
MCC
MTL
MTC
16.5 17.4 16.5 16.8 16.7 17.2 17.8 18.2 17.8 17.2 16.9
20.0 20.2 21.2 21.4 21.8 21.7 22.0 22.8 22.8 22.9 22.3
19.0 18.9 19.3 19.4 19.5 20.8 19.9 20.8 21.6 20.7 21.2
22.0 22.1 23.8 23.4 23.3 23.4 24.5 24.6 25.1 26.4 25.8
IHH =hip height, BL = body length, Rl =rump length, RW =rump width, SW = shoulder width, RMNS = round mass, MCl = metacarpal length, MCC = metacarpal circumference, MTl = metatarsal length, MTC = metatarsal circumference. blndividual bulls identified by genotype/individual bull number within genotype.
248
Diles etal.
TABLE 4. Predicted 36S-d values for ultrasonic measurement traits· of bulls. Glib
BFT
LMA
A/1 A/2 C/1 C/2 C/3 C/4 0/1 0/2 0/3 F/1 F/2
(cm) 0.64 0.58 0.73 0.79 0.76 0.73 0.59 0.54 0.65 0.60 0.71
(cm 2) 56.70 55.87 53.32 53.16 52.08 46.01 51.64 50.18 51.77 46.94 49.30
LMD
5.47 5.33 5.52 5.67 4.96 5.00 5.23 5.42 5.18 5.53 5.49
BWT
RFT
RMD
4.95 4.76 4.96 5.01 4.80 4.45 4.96 4.70 4.87 4.61 5.22
(cm) 1.01 0.92 0.84 0.95 0.82 0.70 0.94 0.82 1.12 0.81 0.89
3.17 2.89 3.14 3.46 3.00 2.96 2.73 2.80 2.97 2.85 2.74
aBFT =backfat thickness, lMA =Longissimus muscle area, lMD =Longissimus muscle depth, BWT =body wall thickness, RFT =rump fat thickness, RMD = rump muscle depth. blndividual bulls identified by genotype/individual bull number within genotype.
PBN, whereas other carcass measures, especially CCw, varied considerably. Carcass composition of genetically Although calculated with untested methods, moderate to high genetic identical steers appeared very unicorrelations of HH, RW, RNMS, MTC, form as measured by PRp, PFr, and BFf, and RMD to PRP indicate selec-
Implications
TABLE S. Genetic correlation coefficients for the relationship of age-adjusted measurement traits of bulls to age-constant PRP of steers. Trait
rg
Hip height 0.422 Body length 0.128 Rump length 0.016 Rump width 0.424 Shoulder width -0.290 Round mass 0.568 Metacarpal length 0.136 Metacarpal circumference 0.181 Metatarsal length 0.294 Metatarsal circumference 0.470 Backfat -0.523 Longissimus area 0.022 Longissimus depth 0.359 Body wall thickness 0.186 Rump fat 0.173 Rump muscle depth - 0.532
Pvalue 0.050 0.572 0.945 0.050 0.190 0.006 0.546 0.421 0.184 0.027 0.013 0.924 0.101 0.408 0.442 0.D11
tion based on these traits can impact PRP. Measures identified to be predictive of carcass composition as measured by regression on PRP included RW, RNMS, BFf, LMD, and LMA. From this study it would appear that BFf and RNMS may be the best live measures of bulls for predicting PRP in slaughter steer progeny. In this study, it appeared that live measures of bulls can be used to predict PRP of their slaughter progeny, and that sel~ction of bulls based on live measures may increase the rate of genetic change possible in this area. The ability to discern predictive differences in such a closely related group of animals, as exhibited in this study, is encouraging. However, the indirect nature of deriving these estimates, coupled with contradictory results in the research literature, makes further studies to directly estimate this genetic correlation from experimental data badly needed. Additionally, further studies addressing the effects of selection for increased PRP through these traits on other important traits, such as
TABLE 6. Results from regression of predicted 36S-d values for bull measurement traits on age-constant PRP of steers. Model
Variable·
Variable Pvalue
Model R2
Model Cpb
Model Pvalue
32 48
167.1 125.2
0.0058 0.0019
80
40.0
0.0001
93
9.5
0.0001
(%) 1 2 3 4
RNMS RW RNMS RW RNMS BFT RW RNMS lMO BFT lMA
0.0058 0.0252 0.0005 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0212 0.0006
aRNMS =round mass, RW =rump width, BFT =backfat thickness, lMD =Longissimus muscle depth, lMA =Longissimus muscle area. bMeasure of total squared error. Model bias is minimized when Cp =number of variables in the equation.
Relationship Between Live Animal Measures in Bulls and Carcass Traits of Steers
reproductive efficiency, still are warranted.
Literature Cited 1. BIF. 1996. Uniform Guidelines for Beef Cattle Improvement Programs. (6th Ed.). June 1996. I 2. Dickerson, G. E. 1962. Implications of genetic environmental interaction in animal breeding. Anim. Prod. 4:47. 3. Diles, J.J.B., R. D. Green, H. H. Shepard, L. J. Hughes, and G. L. Mathiews. 1996. Variation within and between groups of genetically identical nuclear transfer Brangus bulls and steers for growth measures taken over time. Prof. Anim. Sci. 12:250.
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backfat thickness, loineye muscle area and gray shading score in Red Angus cattle. Proc. Western Section Am. Soc. Anim. Sci. 46:202.
and longissimus muscle area. II. Relationship between real-time ultrasound measures and carcass retail yield. J. Anim. Sci. 73:1725.
5. Fernando, R. L., S. A. Knights, and D. Gianola. 1984. One method of estimating the genetic correlation between characters measured in different experimental units. Theor. Appl. Genet. 67:175.
10. Moylan, J. C. 1991. Ultrasound, linear measurement and visual evaluation of cattle. M.S. Thesis, Texas Tech University, Lubbock, TX.
6. Green, R. D., J.J.B. Diles, L. J. Hughes, H. H. Shepard, and G. L. Mathiews. 1996. Variation in birth and weight traits of identical calves produced through nuclear transplantation. Prof. Anim. Sci. 12:238. 7. Green, R. D., H. H. Shepard, J.J.B. Diles, K. E. Hamlin, T. L. Perkins, N. E. Cockett, M. F. Miller, D. L. Hancock, and L. S. Barrett. 1994. Carcass merit EPD: Perceived status and needs. Proceedings of 4th Genetic Predn. Workshop. Beef Improvement Federation, Kansas City, MO. 8. Hamlin, K. E., R. D. Green, T. L. Perkins, L. V. Cundiff, and M. F. Miller. 1995a. Real-time ultrasonic measurement of fat thickness and longissimus muscle area: 1. Description of age and weight effects. J. Anim. Sci. 73:1713.
4. Evans, J. L., B. L. Golden, D.R.C. Bailey, R. P. 9. Hamlin, K. E., R. D. Green, L. V. Cundiff, T. L. Wheeler, and M. E. Dikeman. 1995b. RealGilbert, and R. D. Green. 1995. Genetic parameter estimates of ultrasound measures of time ultrasonic measurement of fat thickness
11. Plante, Y., S. Schmutz, R. D. Green, S. Hiendleder, and G. Kraay. 1994. Molecular genetic, biochemical and phenotypic characterization of cloned cattle. IntI. Soc. Anim. Genet. XXIV:141. 12. SAS. 1985. SASiI> User's Guide: Statistics. SAS Inst., Inc., Cary, NC. 13. Schaeffer, L. R., J. W. Wilton, and R. Thompson. 1978. Simultaneous estimation of variance and covariance components from multi trait mixed model equations. Biometrics. 34:199. 14. Thompson, R. 1977. Estimation of quantitative genetic parameters. In Proc. Int. Conf. Quant. Genet. p 639. Iowa State University Press, Ames, IA. 15. Yamada, Y. 1962. Genotype by environment interaction and genetic correlation of the same trait under different environments. Jpn. J. Genet. 37:498.
Relationships Between Body Measurements Obtained on Yearling Brangus Bulls and Measures of Carcass Merit Obtained from Their Steer Clone-Mates1 J.J.8. DILES*,2, R. D. GREENt.3, H. H. SHEPARD*, G. L. MATHIEWS t , L. J. HUGHES*, and M. F. MILLER* *Oepartment of Animal Science and Food Technology, Texas Tech University, Lubbock, TX 79409-2141, and tOepartment of Animal Sciences, Colorado State University, Fort Collins, CO 80523-1171
Serial (every 28 d) measurements of hip height (HH), body length (BL), rump This study was designed to determine length (RL), rump width (RW), shoulder the relationship between ultrasonic and width (SW), round mass (RNMS), linear body measurements of yearling metacarpal length and circumference bulls and percentage retail product (pRP) (MCL and MCC), metatarsal length and of slaughter steers using genetically circumference (MTL and MTC), and identical bulls and steers as experimental ultrasonic measurements of backfat animals. Four groups of Brangus, thickness (BFT), Longissimus muscle second-generation nuclear transfer calves area (LMA), Longissimus muscle depth (two steers and two to four bulls per (LMD), body wall thickness (BWT), clone group) were used in this study. rump fat thickness (RFT), and rump muscle depth (RMD) obtained on each bull from weaning (6 to 7 mo) until 16 to 17 mo of age were regressed on age to 'This work represents a portion of the M.S. obtain 365-d age constant estimates for thesis of the senior author and was supported, the traits. Steers were slaughtered in part, by funding from the Texas State Line between 480 and 520 d of age and Item for Efficient Production of Beef and the percentage of retail cuts (trimmed to J. W. Thornton Endowment. Assistance of S. Y. Gilbert, L. S. Barrett, and M. K. Butler in 0.64 em) was obtained. Genetic correlaprocurement of data is gratefully acknowl- tions of the adjusted traits of the bulls to edged. age-constant percentage retail yield of 2Current address: He2, Box 1181, Utopia, the steers were obtained following TX 78884. Yamada (1962). The highest genetic correlations (p<0.05) with PRP were 3To whom correspondence should be ad0.568, -0.532, and -0.523 with RNMS, dressed. RMD, and BIT, respectively. The best Reviewed by R. C. Albin and E. E. Hatfield. three-variable equation for predicting Sponsored by D. R. Ames. PRP developed from these data included
Abstract
RNMS, RL, and BFT (Rz = 0.80, P=O.OOOl).
(Key Words: Beef Cattle, Genetic Correlation, Retail Yield.)
Introduction Because of impending changes in the way beef cattle are marketed (UValue-Based Marketing"), breed associations and other organizations have become concerned with expanding genetic information on breeding animals to include measures of carcass merit. Progeny testing for carcass merit is the traditional method for accomplishing this objective, however the time and cost involved limits its usefulness. Ultrasound has been viewed as a technology for overcoming some of the problems associated with progeny testingi however, research must be conducted before ultrasound measures can replace, or supplement, progeny testing (7). In particular, perhaps the most critical question deals with whether ultrasonic mea-
Relationship Between Live Animal Measures in Bulls and Carcass Traits of Steers
surements taken from immature breeding animals are the same traits genetically as carcass measures obtained from slaughter animals. Yamada (15) and Dickerson (2) indicated that genetic correlations for similar traits measured in different sexes may be obtained by assuming them to actually be the same trait measured in different environments. These authors concluded that, when the error variance among genetic groups is the same in both environments, the genetic correlation (rg) can be estimated as:
rg =
where 0 2G + 0 21 are ANOVA estimators of the genetic group and the genotype by environment interaction variance components, respectively, obtained from balanced data. In the case of the same trait measured in different sexes, sex may be considered to be the environment. Fernando et al. (5) pointed out, however, that this method only holds if the two traits have identical heritabilities and residual variances. Given genetic identity of cattle between sexes within a cloned genotype, this method should have direct application to studies of live predictors of carcass merit using nuclear transfer experimental animals. This study was designed to determine the genetic relationship between yearling ultrasonic and linear body measurements of bulls and percentage retail product of slaughter steer progeny using groups of nuclear-transfer cloned bull and steer contemporaries as experimental animals.
Materials and Methods Live Measures. DeSCriptions of the NT groups (genotypes A, B, C, and D) that were used in this study have been presented in previous papers 3, 6, 11). Linear and ultrasonic measures used also are the same as those described by Diles et al. (3); however,
only bull measures collected during the 140-d gain-test period were included in this portion of the study. Body weights (WT), various linear body measurements (10), and ultrasonic measures of muscle and fat were obtained simultaneously on bulls and steers beginning 2 wk after weaning at 28-d intervals. These serial measures were collected until 16 to 17 mo of age, and included: 1) hip height (HH, cm); height from ground to lumbar-sacral vertebrae juncture. 2) Body length (BL, cm); distance from point of shoulder to pins. 3) Rump length (RL, cm); distance from hooks to pins. 4) Rump width (RW, cm); measured at point of greatest width through the rump. 5) Shoulder width (SW, cm); measured at point of greatest width through the shoulder. 6) Round mass (RNMS, cm); measured with a flexible tape starting from tuber coxae passing proximal to the hind limb at the gaskin muscle and ending at the sacral-caudal vertebrae juncture. 7) Metacarpal length (MCL, cm); distance between metacarpal lateral tuberOSity and condyle. 8) Metacarpal circumference (MCC, cm); measured with flexible tape at narrowest point. 9) Metatarsal length (MTL, cm); distance between metatarsal lateral tuberosity and condyle. 10) Metatarsal circumference (MTC, cm); measured with flexible tape at narrowest point. 11) Backfat thickness (BFT, cm); measured at the 12th13th rib interface at a point threefourths of the distance from the medial end of the Longissimus muscle area. 12) Longissimus muscle area (LMA, cm2); measured at the 12th13th rib interface. 13) Longissimus muscle depth (LMD, cm); distance across LMA perpendicular to external body surface and passing through acorn fat deposit. 14) Body wall thickness (BWT, cm); measured at 12th-13th rib interface 1 cm ventral to the Longissimus costarum muscle, perpendicular to external body surface. 15) Rump fat thickness (RFT, cm); measured equidistant from vertebral column, tuber ischii and tuber coxae, perpendicular to exter-
245
nal body surface. 16) Rump muscle depth (RMD, cm); depth of Biceps femoris muscle measured in the same location as RFT. Ultrasonic images were obtained with an Aloka 500V ultrasound unit (Corometrics Medical Systems, Wallingford, CT) equipped with a 3.5-MHz, 17-cm scanning width, linear array transducer following procedures as described by Hamlin et al. (8, 9). Excess dirt and debris were removed from each ultrasound measurement site by vigorous brushing. Corn oil (Mazola, CPC, Foodservice, Englewood Cliffs, Nl) was used as a couplant to obtain adequate acoustical contact with the animal. A super-flab stand-off guide (Animal Ultrasound Services, Ithaca, NY) was used to insure proper contact with the curvature of the animal's back during recording of images for BFT, LMA, LMD, and BWT measurements. All ultrasonic images were recorded on a high resolution VHS video cassette recorder aVC HRS6600U,lVC Co. of America, Elmwood Park, Nl) and later interpreted by the same technician with computer software (AniMorphi Woods Hole Educational Associates, Woods Hole, MA) to obtain actual measurements. Carcass Data. Steers were slaughtered between 480 and 520 d of age after approximately 140 to 180 d on feed. Each steer was deprived of feed for 24 h, then weighed just prior to slaughter. Slaughter and retail fabrication was performed following industry standards at the Texas Tech University Meat Science Laboratory. Hot carcass weights (HCW) were obtained within 30 min postmortem. After a 24-h chill (2°C) period, chilled carcass weights (CCW) were obtained, then each carcass was evaluated by trained personnel and assigned USDA yield and quality grades (YG and QG, respectively) . The full right side from each carcass was fabricated into boneless (except as noted below) retail cuts trimmed to not more than 0.64 cm subcutaneous and intermuscular fat. Retail cuts obtained included: clod,
246
Diles et al.
arm section, chuck roll, brisket, rib (including bones), plate (including bones), lean trim (LN, < 30% fat), fat trim (FT, < 30% lean) and bone (BN, including connective tissue) from the forequarter and gooseneck, top round, knuckle, shortloin strip, top butt, ball tip, tri-tip, flap, flank steak, tender loin, LN, FT and BN from the hindquarter. Percentage retail product (PRP) was calculated by dividing the total weight of all cuts above, except for FT and BN, by CCW x 100. Data Analysis. Single estimates for each serially measured trait of each bull were required for describing the relationship of these measures to final PRP measured in the carcass of the steers. Obtaining these estimates required predicting each animal's measurements at a constant age. Age was chosen as an endpoint, rather than weight, because other performance measures are taken on ageconstant bases according to the guidelines of the Beef Improvement Federation (BIF, 1996). Adjustment for differences in age was accomplished by regressing serial measures on age. The equations produced for each trait by bull then were used to predict 365-d estimates for that trait. Methods described by Yamada (15) were used to obtain genetic correlation estimates from these data. Genetic correlation coefficients were estimated for the relationship be-
tween each of the predicted live measures of the bulls and PRP of the steers. Equations for predicting PRP from age adjusted live measures were developed using stepwise regression for maximum R2 improvement. All statistical analyses were performed using SAS~ (12) software.
Results and Discussion Descriptive carcass characteristics are presented for each steer in Table 1. The PRp, percentage waste fat (PFT, total FT divided by CCW x 100) and percentage waste bone (PBN, total BN divided by CCW x 100) are given in Table 2 for each steer. Slaughter dates were originally set so that one steer of each genotype would be slaughtered at one of two age-constant endpoints. This schedule was interrupted by a case of urinary calculi in one of the steers of genotype D. All other steers were slaughtered according to schedule; however, age at slaughter appeared to have little impact on the compositional traits of PRp, PFT, and PBN. Also, it is interesting to note that no apparent trend was observed regarding age and USDA marbling score. The extreme difference in carcass Longissimus muscle area within genotype C was due to one of the animals having been apparently stunted from birth.
TABLE 1. Descriptive characterlstlcs a of Individual steer carcasses. Glib
All A/2
CIl C/2 Oil 0/2
F/1 F/2
Age
HCW
(d)
(kg)
488 517 482 520 485 517 481 482
342.0 335.2 353.8 312.0 284.2 315.2 351.6 286.6
CCW
CBF
(cm) 326.6 311.0 334.2 293.2 266.0 308.2 345.0 281 .2
0.97 0.97 1.14 1.09 0.94 0.91 0.86 0.81
CLMA
KPH
(cm 2)
(%)
63.9 62.6 52.9 53.5 51.0 63.9 63.2 58.1
2.0 2.0 3.0 2.5 1.5 1.5 2.0 1.5
MRB
YG
Sm 10 SI40 Sm 60 Mt40 SI80 Sm 30 Sm 80 Sm 50
4.4 4.0 5.9 5.2 4.3 3.8 4.1 3.5
aHCW =hot carcass weight, CCW =chilled carcass weight, CSF =carcass backfat thickness, CLMA = carcass longissimus muscle area, KPH = kidney, pelvic and heart fat, MRS = USDA marbling (intramuscular fat) score, YG = USDA yield grade. blndividual steers identified by genotype/individual steer number within genotype.
Age and weight constant estimates for live measures of bulls are given in Table 3 for linear measurement traits and in Table 4 for ultrasonic measurement traits. Linear measurement traits tended to be more uniform within groups of clones than did ultrasonic measurement traits. Part of this difference could be attributed to the error involved in interpreting the ultrasonic images. The structure of these data presented some difficulties when using the method described by Yamada (15) for calculating genetic correlations. Because more bulls than steers were present in two of the genotypes, the data may be considered unbalanced, thus the correlations obtained by this method could be biased and unreliable according to Fernando et al. (5) . In general studies with unbalanced data, where genotype describes type, breed, sire group, etc., variations of maximum likelihood techniques as described by Schaeffer et al. (13) would be required to take into account all information available (12). However, the fact that the animals in each group were genetically identical, presented other options. The first option would be to obtain least squares means for each of the adjusted traits of the bulls and PRP of the steers. This option would eliminate bias from the correlation estimates by balancing the data to one observation for each sex within each genotype, but also would eliminate all of the within genotype variation still present in both the bull and steer traits. The second option involved the pairing of each bull measurement within a genotype with PRP of each steer of the same genotype. This option would decrease the variability within genotypes to a lesser degree, but would increase the number of observations in the data set. The second option was used in this study, because it would conserve more of the observed variability in the data. Increasing the number of observations within a data set in this manner under almost any other circumstances would have been a major
247
Relationship Between Live Animal Measures in Bulls and Carcass Traits of Steers
tion of bull measurement trait and PRP within a genotype will have an equal chance of best representing the relationship between the traits for Retail Waste Waste that genotype. The net effect of Gill product fat bone restructuring the data in this manner is a decrease in the variation on both -------(%)------the bull and the steer sides of the Nl 64.17 20.85 14.95 data set resulting from repeated N2 62.97 19.84 17.37 observations. Overall variation C/1 58.60 27.88 13.52 would be reduced greatest in the C/2 58.92 24.78 16.30 genotypes with more than two bulls, 19.57 0/1 61.28 19.15 because each PRP would be repeated 0/2 62.27 19.09 18.64 four and three times for genotypes B F/1 65.74 17.31 16.95 F/2 67.90 15.33 16.77 and C, respectively. Age-constant measurement traits Significantly (P<0.05) correlated to alndividual steers identified by PRP included RW, RNMS, MTC, BFT, genotype/individual steer number within genotype. and RMD with correlation coefficients of 0.424, 0.568, 0.470, -0.523, and -0.532, respectively. Nonsignificant (P>0.05) correlations were error. Although it cannot be proved obtained for BL, RL, SW, MCL, MCC, to be wholly without error in this MTL, LMA, LMD, BWT, and RFT. Although these results are encourcase, this method appeared to best fit the circumstances of this study. aging, other reports have been qUite The use of genetically identical contradictory. In a recently reported animals in this study implies that, study (4), genetiC correlation estiwithin a genotype, each estimate of a mates between ultrasound traits on bull measurement trait has an equal yearling bulls as compared to carcass chance of being the best estimate for measures in slaughter steers were that genotype. Likewise, each opposite in magnitude and sign. The calculation of PRP within a genotype authors used their results to venture a has an equal chance of being best. It hypothesis that stated that these follows that each possible combinagenetic correlations are caused by TABLE 2. Compositional characteristics of steer carcasses.
differences in degree of maturity in the different sexes due to the animals being measured at different points on their growth curve. Clearly, the contradictory nature of these results raises questions of whether the relationship between yearling bull ultrasound measures and slaughter steer carcass measures is understood. Results from stepwise regression of predicted live measures of bulls on PRP of steers appear in '!able 6. The paired data set described above also was used for the development of these regression models. Again, these results must be interpreted with caution, but the same justification used above additionally applies to this analysis. The data set is not complete with only one outcome per genotype reported, when more than one was actually observed. The best three-variable equation for predicting PRP developed from stepwise regression in this study included RNMS, RW, and BFT (RZ = 0.80, P=O.OOOl), whereas the best two-variable model included RW and RNMS (RZ = 0.48, P=0.OO19). BF!' and RNMS were identified as important variables, each controlling 32% of the observed variation in PRP. When the model was restricted to include only BFT and LMA, predictive power was much lower (RZ = 0.20, P=0.0468).
TABLE 3. Predicted 36S-d values for linear measurement traits· of bulls. Glib
HH
BL
RL
RW
SW
Nl
126.8 126.8 124.9 123.8 125.9 128.2 129.5 128.8 130.3 129.0 127.3
136.9 138.5 135.5 136.1 138.3 144.6 134.0 133.9 134.2 140.1 140.0
46.7 47.8 46.4 44.5 45.6 47.5 49.4 47.4 48.7 44.6 46.9
48.0 46.9 49.2 49.0 47.9 47.9 48.2 49.0 51.2 50.1 51.6
46.4 45.8 47.1 46.6 46.9 47.7 45.3 46.8 45.4 46.5 46.8
N2 C/1 C/2 C/3 C/4 0/1 0/2 0/3 F/l F/2
RNMS (cm) 1840 1826 1805 1800 1788 1835 1836 1825 1858 1816 1872
MCL
MCC
MTL
MTC
16.5 17.4 16.5 16.8 16.7 17.2 17.8 18.2 17.8 17.2 16.9
20.0 20.2 21.2 21.4 21.8 21.7 22.0 22.8 22.8 22.9 22.3
19.0 18.9 19.3 19.4 19.5 20.8 19.9 20.8 21.6 20.7 21.2
22.0 22.1 23.8 23.4 23.3 23.4 24.5 24.6 25.1 26.4 25.8
IHH =hip height, BL = body length, Rl =rump length, RW =rump width, SW = shoulder width, RMNS = round mass, MCl = metacarpal length, MCC = metacarpal circumference, MTl = metatarsal length, MTC = metatarsal circumference. blndividual bulls identified by genotype/individual bull number within genotype.
248
Diles etal.
TABLE 4. Predicted 36S-d values for ultrasonic measurement traits· of bulls. Glib
BFT
LMA
A/1 A/2 C/1 C/2 C/3 C/4 0/1 0/2 0/3 F/1 F/2
(cm) 0.64 0.58 0.73 0.79 0.76 0.73 0.59 0.54 0.65 0.60 0.71
(cm 2) 56.70 55.87 53.32 53.16 52.08 46.01 51.64 50.18 51.77 46.94 49.30
LMD
5.47 5.33 5.52 5.67 4.96 5.00 5.23 5.42 5.18 5.53 5.49
BWT
RFT
RMD
4.95 4.76 4.96 5.01 4.80 4.45 4.96 4.70 4.87 4.61 5.22
(cm) 1.01 0.92 0.84 0.95 0.82 0.70 0.94 0.82 1.12 0.81 0.89
3.17 2.89 3.14 3.46 3.00 2.96 2.73 2.80 2.97 2.85 2.74
aBFT =backfat thickness, lMA =Longissimus muscle area, lMD =Longissimus muscle depth, BWT =body wall thickness, RFT =rump fat thickness, RMD = rump muscle depth. blndividual bulls identified by genotype/individual bull number within genotype.
PBN, whereas other carcass measures, especially CCw, varied considerably. Carcass composition of genetically Although calculated with untested methods, moderate to high genetic identical steers appeared very unicorrelations of HH, RW, RNMS, MTC, form as measured by PRp, PFr, and BFf, and RMD to PRP indicate selec-
Implications
TABLE S. Genetic correlation coefficients for the relationship of age-adjusted measurement traits of bulls to age-constant PRP of steers. Trait
rg
Hip height 0.422 Body length 0.128 Rump length 0.016 Rump width 0.424 Shoulder width -0.290 Round mass 0.568 Metacarpal length 0.136 Metacarpal circumference 0.181 Metatarsal length 0.294 Metatarsal circumference 0.470 Backfat -0.523 Longissimus area 0.022 Longissimus depth 0.359 Body wall thickness 0.186 Rump fat 0.173 Rump muscle depth - 0.532
Pvalue 0.050 0.572 0.945 0.050 0.190 0.006 0.546 0.421 0.184 0.027 0.013 0.924 0.101 0.408 0.442 0.D11
tion based on these traits can impact PRP. Measures identified to be predictive of carcass composition as measured by regression on PRP included RW, RNMS, BFf, LMD, and LMA. From this study it would appear that BFf and RNMS may be the best live measures of bulls for predicting PRP in slaughter steer progeny. In this study, it appeared that live measures of bulls can be used to predict PRP of their slaughter progeny, and that sel~ction of bulls based on live measures may increase the rate of genetic change possible in this area. The ability to discern predictive differences in such a closely related group of animals, as exhibited in this study, is encouraging. However, the indirect nature of deriving these estimates, coupled with contradictory results in the research literature, makes further studies to directly estimate this genetic correlation from experimental data badly needed. Additionally, further studies addressing the effects of selection for increased PRP through these traits on other important traits, such as
TABLE 6. Results from regression of predicted 36S-d values for bull measurement traits on age-constant PRP of steers. Model
Variable·
Variable Pvalue
Model R2
Model Cpb
Model Pvalue
32 48
167.1 125.2
0.0058 0.0019
80
40.0
0.0001
93
9.5
0.0001
(%) 1 2 3 4
RNMS RW RNMS RW RNMS BFT RW RNMS lMO BFT lMA
0.0058 0.0252 0.0005 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0212 0.0006
aRNMS =round mass, RW =rump width, BFT =backfat thickness, lMD =Longissimus muscle depth, lMA =Longissimus muscle area. bMeasure of total squared error. Model bias is minimized when Cp =number of variables in the equation.
Relationship Between Live Animal Measures in Bulls and Carcass Traits of Steers
reproductive efficiency, still are warranted.
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