Hostname: page-component-78c5997874-8bhkd Total loading time: 0 Render date: 2024-11-10T23:20:14.006Z Has data issue: false hasContentIssue false

The use of increased female reproductive rates in dairy cattle breeding schemes

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
Get access

Abstract

The effect of increased female reproductive rates on selection response, on efficiency of progeny testing and on the openness of the nucleus was investigated in open nucleus breeding plans. Conventional progeny testing plans and closed nucleus plans are special classes of open nucleus plans. In the open nucleus plans, generation intervals and selection across tiers were optimized. The number of offspring per elite dam was varied from 1 to 41, progeny testing of young bulls in the female base population was varied from 0 to 100 test records and the size of the nucleus was varied from 250 to 2000 young bulls born per year. Also efficiency of selection was varied: efficient selection in T(heoretical)-schemes and less efficient selection in P(ractical)-schemes. Especially, selection of base parents was less efficient i n P-schemes.

The deterministic prediction model took account of variance reduction due to selection and reduction of selection differentials due to correlations between estimated breeding values of relatives (order statistics). For closed nucleus plans, the results of the model were verified with Monte Carlo simulation results.

By increasing female reproductive rates, genetic gain increased by a factor 0·08 and 0·16 for the T- and P-schemes respectively. The nuclei in P-schemes were less open, due to the less efficient selection in the female base population. Schemes that were less open benefited more from increased female reproductive rates because selection differentials in small nuclei increased more than those in large base populations. The optimal open nucleus plan became less open with increasing female reproduction. Generally, progeny testing of bulls reduced genetic gain (by up to a factor 0·1) but it also reduced inbreeding rates. Progeny testing was more efficient in schemes that were less open: in P-schemes with 41 offspring per dam, progeny testing increased genetic gain. With many offspring per dam there were fewer full-sib families, causing lower selection differentials due to order statistics effects. This effect could be prevented by increasing the size of the nucleus.

Type
Research Article
Copyright
Copyright © British Society of Animal Science 1991

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Bulmer, M. G. 1971. The effect of selection on genetic variability. American Naturalist 105: 201211.CrossRefGoogle Scholar
Colleau, J. J. 1985. [Genetic improvement by embryo transfer within selection nuclei in dairy cattle.] Genetique Selection et Evolution 17: 499537.CrossRefGoogle Scholar
Colleau, J. J. 1989. The genetics of dairy Moet's. In New Selection Schemes in Dairy Cattle: Nucleus Programmes (ed. Kalm, E. and Liboriussen, T.), European Association of Animal Production, Publication No. 44, pp. 5563. Pudoc, Wageningen.Google Scholar
Cunningham, E. P. 1976. The use of egg transfer techniques in genetic improvement. Proceedings of Seminar on Egg Transfer in Cattle (ed. Rowson, L. E. A.), pp. 345353. European Economic Community.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. Zeitschrift fiir Tierzuchtung und Zuchtungsbiologie 104: 2327.Google Scholar
Juga, J. and Maki-Tanila, A. 1987. Genetic change in nucleus breeding dairy herds using embryo transfer. Ada Agriculturae Scandinavica 37: 511519.CrossRefGoogle Scholar
Keller, D. S. and Teepker, G. 1990. The effect of variability in response to superovulation on donor cow selection differentials in nucleus breeding units. Journal of Dairy Science 73: 549554.CrossRefGoogle Scholar
Meuwissen, T. H. E. 1989. A deterministic model for the optimization of dairy cattle breeding based on BLUP breeding value estimates. Animal Production 49: 193202.Google Scholar
Meuwissen, T. H. E. 1990. Reduction of selection differentials in finite populations with a full-/paternal half sib family structure. Biometrics In press.Google Scholar
Misztal, I. and Gianola, D. 1987. Indirect solution of mixed model equations. Journal of Dairy Science 70: 716723.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. 1977. The non-linearity of offspring-parent regression. Proceedings of the International Conference on Quantitiative Genetics, (ed. Pollak, E., Kempthorne, O. and Bailey, T. B.), pp. 297304. Iowa State University Press, Ames.Google Scholar
Ruane, J. 1988. Review of the use of embryo transfer in the genetic improvement of dairy cattle. Animal Breeding Abstracts 56: 437446.Google Scholar
Skjervold, H. and Langholz, H. J. 1964. Factors affecting the optimum structure of AI breeding in dairy cattle. Zeitschrift für Tierzuchtung und Zuchtungsbiologie 80: 2640.Google Scholar
Van Vleck, L. D. 1988. Observations on selection advances in dairy cattle. Proceedings of 2nd International Conference on Quantitative Genetics (ed. Weir, B. S., Goodman, M. M., Eisen, E. J. and Namkoong, G.), pp. 433437.Google Scholar
Woolliams, J. A. and Smith, C. 1988. The value of indicator traits in the genetic improvement of dairy cattle. Animal Production 46: 333345.CrossRefGoogle Scholar