Variance components for birth and carcass traits of crossbred cattle
W. S. Pitchford A F , H. M. Mirzaei A B , M. P. B. Deland C , R. A. Afolayan A D , D. L. Rutley A and A. P. Verbyla EA Livestock Systems Alliance, The University of Adelaide, Roseworthy Campus, Roseworthy, SA 5371, Australia.
B Current address: Department of Animal Science, Faculty of Agriculture, Zabol University, Iran.
C Struan Research Centre, South Australian Research and Development Institute, Naracoorte, SA 5271, Australia.
D Current address: Department of Primary Industries, Forest Road, Orange, NSW 2800, Australia.
E BiometricsSA, The University of Adelaide, Waite Campus, Glen Osmond, SA 5064, Australia.
F Corresponding author. Email: wayne.pitchford@adelaide.edu.au
Australian Journal of Experimental Agriculture 46(2) 225-231 https://doi.org/10.1071/EA05248
Submitted: 19 September 2005 Accepted: 6 February 2006 Published: 3 March 2006
Abstract
During a 4-year period (1994–97) of the Australian ‘Southern Crossbreeding Project’, mature Hereford cows (n = 637) were mated to 97 sires from 7 breeds (Jersey, Wagyu, Angus, Hereford, South Devon, Limousin and Belgian Blue), resulting in 1334 calves. Heifers were slaughtered at around 16 months and steers at 23 months. The objective of the study was to quantify between- and within-breed genetic variation for numerous production and quality traits in a southern-Australian production system. Calf survival, birth weight and carcass production traits (carcass weight, fat depth, loin eye area, intramuscular fat) were obtained from these cattle. The carcass traits were loge-transformed because of a scale effect on the variance. Data were analysed using multi-variate animal models containing fixed effects of sex with random effects of management group, sire breed and animal. In addition, birth month and age of dam were included as fixed effects for birth weight. Covariances between survival and other traits could not be estimated from the multi-variate model so they were estimated from a series of bi-variate models. On average, management group and sire breed accounted for similar proportions of variance. Heritability ranged from 0.14 (survival), 0.17 (intramuscular fat), 0.28 (loin eye area), 0.29 (P8 fat depth), 0.31 (birth weight) to 0.50 (carcass weight). In general, environmental (management and residual) correlations between meat (carcass weight and loin eye area) and fat traits (fat depth and intramuscular fat) were positive, but the genetic correlations (both between and within breed) were negative. Management and genetic (co)variation has been quantified and can facilitate production of calves with carcasses suitable for specific market requirements.
Additional keywords: beef cattle, birth weight, carcass quality, covariance, heritability, survival.
Acknowledgments
The authors thank Andrew Ewers (SARDI) for leading the bone-out trial used to develop yield prediction equations used herein. Michael Milne and farm staff at Struan assisted with both live and carcass measurements. Brian Siebert and his team were responsible for the intramuscular fat quantification. The initial funding for the Southern Crossbreeding Project was obtained from the South Australian Cattle Compensation Trust Fund and the J.S. Davies Bequest to the University of Adelaide. Tony Davis (AW and PR Davis Pty Ltd) funded the feedlot phase of the project. Lastly, the authors thank Cynthia Bottema generally for support in this work and specifically for editorial comments.
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