Hostname: page-component-586b7cd67f-vdxz6 Total loading time: 0 Render date: 2024-11-26T16:05:34.909Z Has data issue: false hasContentIssue false
  • English
  • Français

Application of a multiple-trait animal model for genetic evaluation of maternal and lamb traits in Norwegian sheep

Published online by Cambridge University Press:  02 September 2010

I. Olesen ,
M. Svendsen ,
G. Klemetsdal  and
T. A. Steine
I. Olesen
Affiliation:
Department of Animal Science, Agricultural University of Norway, PO Box 5025, N-1432 Ås, Norway
M. Svendsen
Affiliation:
Department of Animal Science, Agricultural University of Norway, PO Box 5025, N-1432 Ås, Norway
G. Klemetsdal
Affiliation:
Department of Animal Science, Agricultural University of Norway, PO Box 5025, N-1432 Ås, Norway
T. A. Steine
Affiliation:
Department of Animal Science, Agricultural University of Norway, PO Box 5025, N-1432 Ås, Norway
Get access

Abstract

A selection index for overall economic merit and five subindexes for maternal and lamb traits were constructed. For estimation of breeding values, two computer programs were developed. A multiple-trait animal model was programmed for the ewe traits including number of lambs born ofl-, 2- and 3-years-old ewes and ewe fleece weight of yearlings. In order to reduce the memory requirement, the lamb data (growth rate, carcass weight, carcass grade, fat% and lamb fleece iveight) were analysed by a reduced multiple-trait animal model including genetic maternal effect. Experiences with the computer programs in genetic evaluation of approximately 619 000 animals are presented. It is concluded that the models and computing strategy may be used for genetic evaluation in the national sheep breeding programme in Norway.

Relative economic values for all traits were derived from a profit equation on a 3-year-old ewe basis. The sensitivity towards changed economic values urns found to be low. Further, the genetic change in the ewe traits of the Norwegian breeds has been estimated, and a significant improvement was found, which was two to four times higher in the ram circles than outside. For breeding rams, the genetic change for number of lambs born was estimated to be approximately 0·01 lambs per ewe and year.

Keywords

breeding valuecarcass traitsgenetic changematernal traitssheep
Type
Research Article
Information
Animal Science , Volume 60 , Issue 3 , June 1995 , pp. 457 - 469
Copyright
Copyright © British Society of Animal Science 1995

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

Association of Norwegian Sheep and Goat Breeders. 1991. [Annual report 1991]. Oslo, Norway.Google Scholar
Baker, R. L. 1988. Finnsheep and their utilization — experiences in temperate conditions. Journal of Agricultural Science in Finland 60: 455–472.Google Scholar
Baker, R. L. and Steine, T. A. 1986. Components of genetic variation for litter size and lamb suvival in sheep. Proceedings of the third world congress on genetics applied to livestock production, vol. XI, pp. 84–89.Google Scholar
Baker, R. L., Steine, T., Våbeno, A. W. and Breines, D. 1985. The inheritance of yellow fat in Norwegian sheep. Acta Agriculturae Scandinavica 35: 389–397.CrossRefGoogle Scholar
Burfening, P. J. and Kress, D. D. 1993. Direct and maternal effects on birth and weaning weight in sheep. Small Ruminant Research 10:153–163.CrossRefGoogle Scholar
Cunningham, E. P. 1968. Program Selind. Institute of Animal Genetics and Breeding, Vollebekk, Norway. (Mimeo).Google Scholar
Cunningham, E. P. and Gjedrem, T. 1970. Genetic control of ewe body weight in selection for higher wool and lamb output. Acta Agriculturae Scandinavica 20:194–204.Google Scholar
De Veer, J. C. and Van Vleck, L. D. 1987. Genetic parameters for first lactation milk yields at three levels of herd production. Journal of Dairy Science 70: 1434–1441.CrossRefGoogle ScholarPubMed
De Vries, A. G. 1989. A model to estimate economic values of traits in pig breeding. Livestock Production Science 21: 49–66.CrossRefGoogle Scholar
Eikje, E. D. 1971. Studies on sheep production records. I. Effect of environmental factors on weight of lambs. Acta Agriculturae Scandinavica 21: 26–32.CrossRefGoogle Scholar
Eikje, E. D. 1975. Studies on sheep production records. VII. Genetic, phenotypic and environmental parameters for productivity traits of ewes. Acta Agriculturae Scandinavica 25: 242–252.CrossRefGoogle Scholar
Eikje, E. D. and Steine, T. A. 1976. Realized genetic change in ewe productivity traits. Scientific reports of the Agricultural University of Norway 55 (29).Google Scholar
Foulley, J. L., Gianola, D. and Im, S. 1987. Genetic evaluation of traits distributed as Poisson-binomial with reference to reproductive traits. Theoretical and Applied Genetics 73: 870–877.CrossRefGoogle Scholar
Fowler, V. R., Bichard, M. and Pease, A. 1976. Objectives in pig breeding. Animal Production 23: 365–387Google Scholar
Gerstmayr, S. 1992. Impact of the data structure on the reliability of the estimated genetic parameters in an animal model with maternal effects. Journal of Animal Breeding and Genetics 109: 321–336.CrossRefGoogle Scholar
Gianola, D. 1986. On sélection criteria and estimation of parameters when the variance is heterogeneous. Theoretical and Applied Genetics 72: 671–677.CrossRefGoogle ScholarPubMed
Gianola, D. and Foulley, J. L. 1983. Sire evaluation of ordered categorical data with a threshold model. Génétique Selection Evolution Animate 15: 201–224.CrossRefGoogle ScholarPubMed
Gianola, D., Foulley, J. L., Fernando, R. L., Henderson, C. R. and Weigel, K. A. 1992. Estimation of heterogeneous variances using empirical Bayes methods: theoretical considerations. Journal of Dairy Science 75: 2805–2823.CrossRefGoogle ScholarPubMed
Gjedrem, T. 1969. Some attempts to increase efficiency of sheep selection. Acta Agriculturae Scandinavica 19: 116–126.CrossRefGoogle Scholar
Gjedrem, T. 1972. A study on the definition of the aggregate genotype in a selection index. Acta Agriculturae Scandinavica 22:11–16.CrossRefGoogle Scholar
Gravdal, O. O. 1992. Sjukdomsregistrering og produksjons-uthald hjå søyer. Cand. Agriculture dissertation, Department of Animal Science, As, Norway.Google Scholar
Henderson, C. R. 1973. Sire evaluation and genetic trends. Proceedings of animal breeding and genetics symposium in honor of Dr. L. L. Lusli. American Society of Animal Science and American Dairy Science Association. Champaign, II., pp. 10–41.Google Scholar
Henderson, C. R. 1984. Application of linear models in animal breeding. University of Guelph, Guelph.Google Scholar
Henderson, C. R. and Quaas, E. J. 1976. Multiple trait evaluation using relatives' records, journal of Animal Science 43: 1188–1197.CrossRefGoogle Scholar
Im, S., Fernando, R. L. and Gianola, D. 1989. Likelihood inferences in animal breeding under selection: a missing data theory view point. Génétique Sélection Evolution Animate 21:399–414.CrossRefGoogle Scholar
Jonmundsson, J. V. 1981. Genetic correlation between direct and maternal effects for weaning weight of lambs. Journal of Agricultural Research of Iceland 13: 41–47.Google Scholar
Matos, C. A. 1993. Genetic analyses of reproductive discrete traits in sheep using linear and nonlinear models. Ph.D. thesis, University of Wisconsin, Madison.Google Scholar
Misztal, I. and Gianola, D. 1987. Indirect solution of mixed model equations. Journal of Dairy Science 70: 716–723.CrossRefGoogle Scholar
Misztal, I., Gianola, D. and Foulley, J. L. 1989. Computing aspects of a nonlinear method of sire evaluation for categorical data. Journal of Dairy Science 72: 72–1557.CrossRefGoogle Scholar
Misztal, I., Gianola, D. and Schaeffer, L. R. 1987. Extrapolation and convergence criteria with Jacobi and Gauss-Seidel iteration in animal models. Journal of Dairy Science 70: 70–2577.CrossRefGoogle Scholar
National Board of Animal Production Recording. 1990. [Annual report 1990], pp. 143–158. Norway.Google Scholar
National Board of Animal Production Recording. 1991. [Annual report 1991], pp. 138–154. Norway.Google Scholar
Norwegian Agricultural Economics Research Institute. 1990. [Manual of management planning 1990/1991]. Oslo, Norway.Google Scholar
Olesen, I. 1986. Tilslutning til og erfaring med ulike tiltak i avlsarbeidet med sau. Aktuelt fra Statens fagtjeneste for landbniket 1986, no. 5, pp. 389–393.Google Scholar
Olesen, I. 1993. Effects of cervical insemination with frozen semen on fertility and litter size of Norwegian sheep. Livestock Production Science 37:169–184.CrossRefGoogle Scholar
Olesen, I. and Husabø, J. O. 1994. Effect of using ultrasonic muscle depth and fat depth on the accuracy of predicted phenotypic and genetic values of carcass traits on live ram lambs. Acta Agriculturae Scandinavica 44A: 65–72.CrossRefGoogle Scholar
Olesen, I., Perez-Enriso, M., Gianola, D. and Thomas, D. L. 1994. A comparison of normal and nonnormal mixed models for number of lambs born in Norwegian sheep. Journal of Animal Science 72: 72–1166.CrossRefGoogle ScholarPubMed
Olesen, I. and Steine, T. 1991. Use of carcass records from commercial slaughterhouses in sheep selection. Paper presented at the forty-second annual meeting of European Association for Animal Production. (Mimeo).Google Scholar
Quaas, R. L. and Pollak, T. E. 1980. Mixed model methodology for farm and ranch beef cattle testing programs, journal of Animal Science 51: 51–1277.CrossRefGoogle Scholar
Robinson, G. K. 1986. Group effects and computing strategies for models for estimating breeding values. Journal of Dairy Science 69: 69–3106.CrossRefGoogle Scholar
Robison, O. W. 1981. The influence of maternal effects on the efficiency of selection. A review. Livestock Production Science 8:121–137.CrossRefGoogle Scholar
Schaeffer, L. R. and Kennedy, B. W. 1986. Computing strategies for solving mixed model equations. Journal of Dairy Science 69: 575–579.CrossRefGoogle Scholar
Schaeffer, L. R. and Wilton, J. W. 1987. RAM computing strategies and multiple traits. Prediction of genetic value for beef cattle. Proceedings of workshop 11, Winrock International, Kansas City, Missouri.Google Scholar
Searle, S. R. 1982. Matrix algebra useful for statistics. John Wiley, New York.Google Scholar
Short, T. H., Blake, R. W.Quaas, R. L. and Van Vleck, L. D. 1990. Heterogenous within-herd variance. 1. Genetic parameters for first and second lactation milk yields of grade Holstein cows, journal of Dairy Science 73: 73–3312.Google Scholar
Simm, G., Young, M. J. and Beatson, P. R. 1987. An economic selection index for lean meat production in New Zealand sheep. Animal Production 45: 465–475.Google Scholar
Smith, C. 1983. Effects of changes in economic weights on the efficiency of index selection. Journal of Animal Science 56: 56–1057.CrossRefGoogle Scholar
Standal, N. 1991. Ram circles in Norway. Paper presented at the British Sheep Breeders Roundtable, Harrogate, England. (Mimeo).Google Scholar
Steine, T. 1980. Fifteen years experience with a co-operative sheep breeding scheme in Norway. Proceedings of the first world congress, on sheep and beef cattle breeding, vol. 2, pp. 145–148.Google Scholar
Steine, T. 1983. Vereindeks I. Stensiltrykk nr. 26/83. Department of Animal Science, Ås, Norway. (Mimeo).Google Scholar
Steine, T. 1985. Genetic studies of reproduction in Norwegian sheep. In Genetics of reproduction in sheep (ed. Land, R. B. and Robinson, D. W.), pp. 47–54. Butterworths, London.CrossRefGoogle Scholar
Steine, T. A., Vabene, A. W., Bekken, A. and Eikje, E. D. 1976. Results from a crossbreeding experiment with Finnsheep. Scientific reports of the Agricultural University of Norway 57: no. 25.Google Scholar
Weigel, K. A. and Gianola, D. 1992. Estimation of heterogeneous within-herd variance components using empirical Bayes methods: a simulation study. Journal of Dairy Science 75: 75–2824.CrossRefGoogle ScholarPubMed
Winkelman, A. and Schaeffer, L. R. 1988. Effect of heterogeneity of variance in dairy sire evaluation, journal of Dairy Science 71: 3033–3039.Google Scholar