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Genetic relationships between visual and objective measures of carcass composition in crossbred lambs

Published online by Cambridge University Press:  18 August 2016

H. E. Jones
Affiliation:
Genetics and Reproduction Department, Animal Biology Division, Scottish Agricultural College, King’s Buildings, Edinburgh EH9 3JG
G. Simm
Affiliation:
Genetics and Reproduction Department, Animal Biology Division, Scottish Agricultural College, King’s Buildings, Edinburgh EH9 3JG
W. S. Dingwall
Affiliation:
Genetics and Reproduction Department, Animal Biology Division, Scottish Agricultural College, King’s Buildings, Edinburgh EH9 3JG
R. M. Lewis
Affiliation:
Genetics and Reproduction Department, Animal Biology Division, Scottish Agricultural College, King’s Buildings, Edinburgh EH9 3JG
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Abstract

The aim of this study was to estimate genetic and phenotypic (co)variances between objective measures and carcass visual scores, as a test of the potential value of visual scores in selection programmes to improve carcass composition in crossbred lambs. In each of 1986, 1987 and 1988, 22 Suffolk rams were chosen with either high or low scores on an index designed to increase lean growth rate. These rams were joined with 18 to 20 crossbred ewes each and their lambs were grown on grass to one of three target live weights (35·5, 41·5 and 47·0 kg) for slaughter. The carcasses of 1881 lambs were visually scored for overall conformation and fatness using the standard Meat and Livestock Commission methods. Additionally, a more detailed 15-point scale assessment of conformation and a direct visual score of subcutaneous fat on the carcass were taken on 1252 lambs during the latter 2 years of the study. Carcass composition was estimated by dissection of a shoulder joint into lean, fat and bone. The possibility of combining data collected on lambs slaughtered at each of the three target live weights, for the estimation of genetic parameters was investigated. Results indicated that heritability estimates for a trait using data collected within each of the slaughter groups were homogeneous. Genetic correlations between records collected for a trait within each of the slaughter groups were not significantly different from one. These results indicated that data collected at each of the target slaughter weights could justifiably be combined. Heritability estimates were generally higher for shoulder tissue proportions (0·3) than for visual scores (0-2). Genetic correlations between all conformation scores and tissue proportions were not significantly different from 0 and therefore of little or no value in predicting carcass composition. Genetic correlations between visual scores of fat and both tissue proportions and ratios were generally high (around 0·65). These results suggest that fat scores collected on crossbred animals could be valuable in purebred selection programmes where improving carcass composition of the crossbred generation is the underlying objective.

Type
Research Article
Copyright
Copyright © British Society of Animal Science 1999

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References

Bennett, G. L., Meyer, H. H. and Kirton, A. H. 1988. Effects of selection for divergent ultrasonic fat depth in rams on progeny fatness. Animal Production 47: 379386.Google Scholar
Boldman, K. G., Kriese, L. A., Van Fleck, L. D., Van Tassell, C. P. and Kachman, S. D. 1995. A manual for use of MTDFREML. US Department of Agriculture, Agricultural Research Center, Clay Center, Nebraska.Google Scholar
Cameron, N. D. 1992. Correlated responses in slaughter and carcass traits of crossbred progeny to selection for carcass lean content in sheep. Animal Production 54: 379388.Google Scholar
Cook, G. L., Jones, D. E. and Kempster, A.J. 1983. A note on a simple criterion for choosing among sample joints for use in double sampling. Animal Production 36: 493495.Google Scholar
Groeneveld, E. 1996. REML VCE a multivariate model restricted maximum likelihood (co)variance component estimation package version 3.2 user’s guide. Federal Research Centre of Agriculture, Mariensee, Germany.Google Scholar
Guy, D. R. and Croston, D. 1994. UK experience and progress with sheep sire referencing schemes. Proceedings of the fifth world congress on genetics applied to livestock production, Guelph, vol. 18, pp. 5558.Google Scholar
Harrington, G. and Kempster, A. J. 1989. Improving lamb carcass composition to meet modern consumer demand. In Reproduction, growth and nutrition in sheep (ed. Dyrmundsson, O. R. and Thorgeirrsson, S.), pp. 7990. Agricultural Research Institute and Agricultural Society, Iceland.Google Scholar
Jackson, T. H. and Mansour, Y. A. 1974. Differences between groups of lamb carcasses chosen for good and poor conformation. Animal Production 19: 93105.Google Scholar
Kempster, A. J., Cook, G. L. and Grantley-Smith, M. 1986. National estimates of the body composition of British cattle, sheep and pigs with special reference to trends in fatness. A review. Meat Science 17: 107138.Google Scholar
Kempster, A. J., Croston, D. and Jones, D. W. 1981. Value of conformation as an indicator of sheep carcass composition within and between breeds. Animal Production 33: 3949.Google Scholar
Kirton, A. H. and Pickering, F. S. 1967. Factors associated with differences in carcass conformation in lamb. New Zealand Journal of Agricultural Research 10: 183200.Google Scholar
Lewis, R. M., Simm, G., Dingwall, W. S. and Murphy, S.V. 1996. Selection for lean growth in terminal sire sheep to produce leaner crossbred progeny. Animal Science 63: 133142.CrossRefGoogle Scholar
Mood, A. M., Graybill, F.A. and Boes, D.C. 1973. Introduction to the theory of statistics. McGraw-Hill, New York.Google Scholar
Patterson, H.D. and Thompson, R. 1971. Recovery or interblock information when block sizes are unequal. Biometrica 58: 545554.Google Scholar
Simm, G. 1987. Carcass evaluation in sheep breeding programmes. In New techniques in sheep production (ed. Marai, I. F. M. and Owen, J. B.), pp. 125144. Butterworths, London.CrossRefGoogle Scholar
Simm, G. 1992. Selection for lean meat production in sheep. In Recent advances in sheep and goat research (ed. A. W. Speedy, ), pp. 193215. CAB International.Google Scholar
Simm, G. and Dingwall, W. S. 1989. Selection indices for lean meat production in sheep. Livestock Production Science 21: 223233.Google Scholar
Simm, G. and Murphy, S. V. 1996. The effects of selection for lean growth in Suffolk sires on the saleable meat yield of their crossbred progeny. Animal Science 62: 255263.CrossRefGoogle Scholar
Thompson, R., Crump, R. E., Juga, J. and Visscher, P. M. 1995. Estimating variances and covariances for bivariate animal models using scaling and transformation. Genetics, Selection, Evolution 27: 3342.Google Scholar
Visscher, P. M., Thompson, R. and Hill, W. G. 1991. Estimation of genetic and environmental variances for fat yield in individual herds and an investigation into heterogeneity of variance between herds. Livestock Production Science 28: 273290.Google Scholar
Wei, M. and Werf, J. H. J. van der. 1994. Maximizing genetic response in crossbreds using both purebred and crossbred information. Animal Production 59: 401413.Google Scholar
Werf, J. H. J. van der, Wei, M. and Brascamp, E.W. 1994. Combined crossbred and purebred selection to maximize genetic response in crossbreds. Proceedings of the fifth world congress on genetics applied to livestock production, Ġuelph, vol. 18, pp. 266269.Google Scholar
Wolf, B. T., Smith, C., King, J. W. B. and Nicholson, D. 1981. Genetic parameters of growth and carcass composition in crossbred lambs. Animal Production 32: 17.Google Scholar
Woodward, J. and Wheelock, V. 1990. Consumer attitudes to fat in meat. In Reducing fat in meat animals (ed. Wood, J. D. and Fisher, A. V.), pp. 66100. Elsevier, London.Google Scholar