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Multibreed designs. 1. Variation between breeds

Published online by Cambridge University Press:  02 September 2010

C. S. Taylor
Affiliation:
ARC Animal Breeding Research Organisation, West Mains Road, Edinburgh EH9 3JQ
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Summary

When testing facilities are limited and the number of breeds and/or crosses to be tested is potentially large, then multibreed designs which involve a large number of breeds with only a few animals per breed give the optimum allocation of animals within and between breeds for various objectives. Multibreed designs could therefore form a useful adjunct to existing breed testing and selection programmes. How far such designs should be introduced would depend, among other things, on the degree of confidence in existing information, on the success of existing testing schemes, and on the relevance of the selection criteria currently being used. In this, the first of a series of papers on multibreed designs, the general approach is outlined, and designs for measuring between-breed variation are considered.

To estimate the extent of between-breed variation, the best overall design is to have four unrelated animals per breed and as large a number of breeds as possible. Valuable experimental work on breed variation can therefore be done without vast facilities.

Type
Research Article
Copyright
Copyright © British Society of Animal Science 1976

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References

REFERENCES

Connolly, J. 1974. Economic and statistical optimisation of beef breed comparisons. Proc. Genetics Operations Research Workshop. Trinity College, Dublin (Abstr. and Mimeograph).Google Scholar
Dickerson, G. E. 1969. Experimental approaches in utilising breed resources. Anim. Breed Abstr. 37: 191202.Google Scholar
Donald, H. P. and Russell, W. S. 1970. The relationship between live weight of ewe at mating and weight of newborn lamb. Anim. Prod. 12: 273280.Google Scholar
Fisher, R. A. 1946. Statistical Methods for Research Workers. 10th ed. Oliver and Boyd, Edinburgh.Google Scholar
Hammersley, J. M. 1949. The unbiased estimate and standard error of the inter-class variance. Metron 15: 173188.Google Scholar
Hill, W. G. 1974. Size of experiments for breed or strain comparisons. Proc. Work. Symp. Breed Evaluation and Crossing Expts with Farm Animals, Research Institute for Animal Husbandry, ‘Schoonord’, Zeist, Netherlands, pp. 4354.Google Scholar
Mason, I. L. 1969. A World Dictionary of Livestock Breeds Types and Varieties. 2nd ed. Commonwealth Agricultural Bureaux, Farnham Royal, Bucks.Google Scholar
Nordskog, A. W. 1959. Note on optimum group size for progeny tests. Biometrics 15: 513517.CrossRefGoogle Scholar
Rendel, J. M. 1959. Optimum group size in half-sib family selection. Biometrics 15: 376381.CrossRefGoogle Scholar
Robertson, A. 1957. Optimum group size in progeny testing and family selection. Biometrics 13: 442450.Google Scholar
Robertson, A. 1959a. Experimental design in the evaluation of genetic parameters. Biometrics 15: 219226.CrossRefGoogle Scholar
Robertson, A. 1959b. The sampling variance of the genetic correlation coefficient. Biometrics 15: 469485.Google Scholar
Scheffé, H. 1959. The Analysis of Variance. Chap. 7. Wiley, New York.Google Scholar
Tallis, G. M. 1959. Sampling errors of genetic correlation coefficients calculated from analyses of variance and covariance. Aust. J. Statistics 1: 3543.CrossRefGoogle Scholar
Tallis, G. M. 1960. The sampling errors of estimated genetic regression coefficients and the errors of predicted genetic gains. Aust. J. Statistics 2: 6677.Google Scholar
Taylor, St C. S. 1971. The effect of body size on production efficiency in cattle. Annls Génét. Sét. anim. 3: 8598.CrossRefGoogle Scholar
Weardon, S. 1959. The use of the power function to determine an adequate number of progeny per sire in a genetic experiment involving half sibs. Biometrics 15: 417423.Google Scholar