Hostname: page-component-78c5997874-xbtfd Total loading time: 0 Render date: 2024-11-13T09:20:13.689Z Has data issue: false hasContentIssue false
  • English
  • Français

Estimation of genetic parameters for litter size in Danish Landrace and Yorkshire pigs

Published online by Cambridge University Press:  02 September 2010

J. Estany  and
D. Sorensen
J. Estany
Affiliation:
National Institute of Animal Science, Department for Research in Pigs and Horses, DK-8830 Tjele, Denmark
D. Sorensen
Affiliation:
National Institute of Animal Science, Department for Research in Pigs and Horses, DK-8830 Tjele, Denmark
Get access

Abstract

Variance components for litter size (total number of piglets born) were estimated from Danish purebred Landrace and Yorkshire litters by restricting maximum likelihood. The data were collected from the national Danish breeding programme and consisted of 19 666 litters in Danish Landrace and 29 336 litters in Danish Yorkshire. Four different analyses for litter size were conducted within breed. In the first two, genetic groups were included in the model in order to account for the importation of animals from other countries; in the other two, genetic groups were removed from the model. Within each case, herd-year-type of insemination effects were fitted as fixed (H-fixed models), or herd-year-season-type of insemination effects were fitted as random (H-random models). Estimates of heritability ranged from about 0·11 to 0·14 in Landrace and from 0·10 to 0·11 in Yorkshire. Variance due to herd-year-season-type of insemination ranged from 0·029 to 0·041 of total variance, values somewhat lower than those obtained for non-genetic permanent effects. In order to compare the four models, data were divided into different subsets, and records from one subset were predicted using parameters estimated from the other subset. Both the correlation between observed and predicted values, and the mean squared error of prediction indicated that predictive ability was higher in the case of H-random models. There was no evidence that genetic groups improved the predictive ability for litter size. However, group effects affected inferences about genetic trend, particularly in Landrace, where genetic group composition changed consistently over the years.

Keywords

genetic parameterslitter sizemathematical modelspigs
Type
Research Article
Information
Animal Science , Volume 60 , Issue 2 , April 1995 , pp. 315 - 324
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

Andersen, S. and Petersen, E. S. 1990. The National Breeding Programme. Proceedings of the fourth world congress of genetics applied to livestock production, Edinburgh, vol. XV, pp. 431–434.Google Scholar
Anderson-Sprecher, R. 1994. Model comparisons and R2. American Statistician 48: 113–117.Google Scholar
Bidanel, J. P. and Ducos, A. 1994. Genetic evaluation of reproductive traits in swine. Proceedings of the symposium on application of mixed linear models in the prediction of genetic merit in pigs, Mariensee. (In press).Google Scholar
Boldman, K. and Van Vleck, L. D. 1991. Derivative-free restricted maximum likelihood estimation in animal models with a sparse matrix solver. Journal of Dairy Science 74: 4337–4343.CrossRefGoogle ScholarPubMed
Clark, L. K. and Leman, A. D. 1986. Factors that influence litter size in pigs. Part I. Pig News and Information 7: 303–310.Google Scholar
Gianola, D. and Fernando, R. L. 1986. Bayesian methods in animal breeding theory. Journal of Animal Science 63: 217–244.CrossRefGoogle Scholar
Gu, Y., Haley, C. S. and Thompson, R. 1989. Estimates of genetic and phenotypic parameters of litter traits from closed lines of pigs. Animal Production 49: 477–482.Google Scholar
Haley, C. S., Avalos, E. and Smith, C. 1988. Selection for litter size in the pig. Animal Breeding Abstracts 56: 317–332.Google Scholar
Henderson, C. R. 1973. Sire evaluation and genetic trends. Proceedings of the animal breeding and genetics symposium in honor of Dr J. L. Lush, American Society of Animal Science and American Dairy Association, Champaign, pp. 10–41.Google Scholar
Henderson, C. R. 1975. Best linear unbiased estimation and prediction under a selection model. Biometrics 31: 423–447.CrossRefGoogle Scholar
Im, S., Fernando, R. L. and Gianola, D. 1989. Likelihood inferences in animal breeding under selection: a missing-data theory view point. Genetics, Selection, Evolution 21: 399–414.CrossRefGoogle Scholar
Jansen, G. B. 1987. Herd effects. Fixed or random? Thirty-eighth annual meeting of the European Association for Animal Production, Lisbon.Google Scholar
Mercer, J. T. and Crump, R. E. 1990. Genetic parameter estimates for reproduction traits in purebred Landrace pigs. Proceedings of the fourth world congress of genetics applied to livestock production, Edinburgh, vol. XV, pp. 489–492.Google Scholar
Meyer, K. 1988. DFREML. Programs to estimate variance components for individual animal models by restricted maximum likelihood. User notes. University of Edinburgh.Google Scholar
Meyer, K. 1989. Restricted maximum likelihood to estimate variance components for animal models with several random effects using a derivative-free algorithm. Genetics, Selection, Evolution 21: 317–340.CrossRefGoogle Scholar
Quaas, R. L. 1988. Additive genetic model with groups and relationships. Journal of Dairy Science 71: 1338–1345.CrossRefGoogle Scholar
Rubin, D. B. 1976. Inference and missing data. Biometrika 63: 581–592.CrossRefGoogle Scholar
Shao, S. 1993. Linear model selection by cross-validation. Journal of the American Statistical Association 88: 486–494.CrossRefGoogle Scholar
Smith, C., Dickerson, G. E., Tess, M. W. and Bennett, G. L. 1983. Expected relative responses to selection for alternative measures of life cycle economic efficiency of pork production. Journal of Animal Science 56: 1306–1314.CrossRefGoogle ScholarPubMed
Smith, S. P. and Graser, H. U. 1986. Estimating variance components in a class of mixed models by restricted maximum likelihood. Journal of Dairy Science 69: 1156–1165.CrossRefGoogle Scholar
Sorensen, D. A. 1991. Predicted breeding values for litter size with an animal model used in the Danish breeding program. Report no. 697 from the National Institute of Animal Science, Foulum, Denmark.Google Scholar
Sorensen, D. A. and Johansson, K. 1992. Estimation of direct and correlated responses to selection using univariate animal models. Journal of Animal Science 70: 2038–2044.CrossRefGoogle ScholarPubMed
Southwood, O. I. and Kennedy, B. W. 1990. Estimation of direct and maternal genetic variance for litter size in Canadian Yorkshire and Landrace swine using an animal model. Journal of Animal Science. 68: 1841–1847.CrossRefGoogle ScholarPubMed
Tess, M. W., Bennett, G. L. and Dickerson, G. E. 1983. Simulation of genetic changes in life cycle efficiency of pork production. II. Effects of components on efficiency. Journal of Animal Science 56: 354–368.CrossRefGoogle Scholar
Thompson, R. 1986. Estimation of realized heritability in a selected population using mixed model methods. Genetics, Selection, Evolution 18: 475–484.CrossRefGoogle Scholar
Ugarte, E., Alenda, R. and Carabaflo, M. J. 1992. Fixed or random contemporary groups in genetic evaluations. Journal of Dairy Science 75: 269–278.CrossRefGoogle Scholar
Visscher, P. M. and Goddard, M. E. 1993. Fixed and random contemporary groups. Journal of Dairy Science 76: 1444–1454.CrossRefGoogle Scholar
Vries, A. G. de. and Sorensen, D. A. 1990. Optimization of present pig breeding programs. Proceedings of the fourth world congress of genetics applied to livestock production, Edinburgh, vol. XV, pp. 395–404.Google Scholar
Wade, K. M., Quaas, R. L. and Van VIeck, L. D. 1990. Mixed linear models with an autoregressive error structure. Proceedings of the fourth world congress of genetics applied to livestock production, Edinburgh, vol. XIII, pp. 508–511.Google Scholar
Webb, A. J. and Bampton, P. R. 1988. Impact of the new statistical technology on pig improvement. In Animal breeding opportunities, occasional publication, British Society of Animal Production, no. 12, pp. 111–128.Google Scholar