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A deterministic model for the optimization of dairy cattle breeding based on BLUP breeding value estimates

Published online by Cambridge University Press:  02 September 2010

T. H. E. Meuwissen
Affiliation:
Research Institute for Animal Production ‘Schoonoord’, PO Box 501, 3700 AM Zeist, The Netherlands
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Abstract

A deterministic model was developed to examine the optimization of open nucleus breeding schemes in order to maximize the rate of genetic response in dairy cattle. By changing the parameters, the model was able to simulate both a closed nucleus and a progeny testing scheme. The model implicitly optimized the generation interval and the selection across tiers by means of truncation across age classes and tiers respectively. The effects of size of the progeny test group and the nucleus size were assessed by comparing alternative plans. It is possible to optimize a breeding plan given the reproduction rates of the animals, the availability of different sources of information, the age distribution of the animals (survival rates) and the phenotypic and genetic parameters of the trait.

The steady state selection response was assessed by calculating the genetic progress year after year until it stabilized. The genetic gain was corrected for the effects of reduced variances due to previous selections and increased variances due to genetic differences between parental age classes.

In an example, the model was used to predict the improvement in milk yield in a closed artificial insemination breeding scheme. The genetic gain of a conventional progeny testing scheme was about one-third lower than the genetic gain of the optimized breeding plan. The variance reduction due to selection decreased the steady state genetic gain by a factor 0·3

Type
Papers
Copyright
Copyright © British Society of Animal Science 1989

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References

REFERENCES

Belonsky, G. M. and Kennedy, B. W. 1988. Selection on individual phenotype and best linear unbiased prediction of breeding value in a closed swine herd. Journal of Animal Science 66: 11241131.CrossRefGoogle Scholar
Brascamp, E. W. 1978. Methods on economic optimisation of animal breeding plans. Report, Research Institute of Animal Husbandry, Zeist, No. B-134.Google Scholar
Bulmer, M. G. 1971. The effect of selection on genetic variability. American Naturalist 105: 201211.CrossRefGoogle Scholar
Burrows, P. M. 1984a. Inbreeding under selection from unrelated families. Biometrics 40: 357366.CrossRefGoogle Scholar
Burrows, P. M. 1984b. Inbreeding under selection from related families. Biometrics 40: 895906.CrossRefGoogle Scholar
Cochran, W. G. 1951. Improvement by means of selection. Proceedings of the 2nd Berkeley Symposium on Mathematics, Statistics and Probability (ed. Neyman, J.), pp. 449470.Google Scholar
Cunningham, E. P. 1975. Multi-stage index selection. Theoretical and Applied Genetics 46: 5561.CrossRefGoogle ScholarPubMed
Ducroco, V. and Quaas, R. L. 1988. Prediction of genetic response to truncation selection across generations. Journal of Dairy Science 71: 25432553.CrossRefGoogle Scholar
Everett, R. W. 1984. Impact of genetic manipulation. Journal of Dairy Science 67: 28122818.CrossRefGoogle ScholarPubMed
Hazel, L. N. 1943. The genetic basis for constructing selection indexes. Genetics, USA 28: 476490.CrossRefGoogle ScholarPubMed
Hill, W. G. 1974. Prediction and evaluation of response to selection with overlapping generations. Animal Production 18: 117139.Google Scholar
Hill, W. G. 1976. Order statistics of correlated variables and implications in genetic selection programmes. Biometrics 32: 889902.CrossRefGoogle ScholarPubMed
James, J. W. 1987. Determination of optimal selection policies. Zeilschrift für Tierzuchtung und Zuchtungsbiologie 104: 2327.Google Scholar
Korvbr, S. and Renkema, J. A. 1979. Economic evaluation of replacement rates in dairy herds. II. Selection of cows during the first lactation. Livestock Production Science 6: 2937.CrossRefGoogle Scholar
Meuwisshn, T. H. E. and Ruane, J. 1989. The importance of daughters of bull dams in a progeny testing scheme. Livestock Production Science. In press.Google Scholar
Nicholas, F. W. and Smith, C. 1983. Increased rates of genetic change in dairy cattle by embryo transfer and splitting. Animal Production 36: 341353.Google Scholar
Rendel, J. M. and Robertson, A. 1950. Estimation of genetic gain in milk yield by selection in a closed herd of dairy cattle. Journal of Genetics 50: 18.CrossRefGoogle Scholar
Robertson, A. 1960. A theory of limits in artificial selection. Proceedings of the Royal Society B 153: 234249.Google Scholar
Van Vleck, L. D. 1987. Observations on selection advances in dairy cattle. Proceedings of the 2nd International Conference on Quantitative Genetics (ed. Weir, B. S., Goodman, M., Eisen, E. J. and Namkoong, G.), pp. 433437.Google Scholar