Advanced SearchSearch Tips
Estimation of Direct and Service Sire Genetic Parameters for Reproductive Traits in Yorkshire
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Estimation of Direct and Service Sire Genetic Parameters for Reproductive Traits in Yorkshire
Kim, B.W.; Kim, S.D.; Lee, I.J.; Chung, K.H.; Kwon, O.S.; Ha, J.K.; Lee, J.G.;
  PDF(new window)
Direct and service sire genetic parameters for total number of pigs born (TNB), number of pigs born alive (NBA), total pig weight at birth (TWB), and average pig birth weight (ABW) were estimated by DF-REML under a multiple trait animal model. Data on 3,078 litters of the Yorkshire from Jan, 1975 to Dec, 1998 at National Livestock Research Institute were obtained. The animal model included fixed contemporary group effects and random additive direct, service sire, and residual effects. Additive genetic relationships among animals were included. A separate relationship matrix for service sires and their sire was also included. Additive direct heritability estimates for TNB, NBA, TWB, and ABW were 0.19, 0.18, 0.25 and 0.39, respectively. Service sire heritability estimates for TNB, NBA, TWB, and ABW were 0.02, 0.01, 0.02 and 0.01, respectively. The genetic and phenotypic correlations of TNB with NBA estimated in this study were 0.81 and 0.81, respectively, and the genetic and phenotypic correlations of TNB with TWB estimated were 0.82 and 0.76, respectively. Results indicate that service sires account for 1 to 2% of the total variation for TNB, NBA, TWB, and ABW. Further investigation is needed to determine whether the service sire effect is primarily genetic or environmental.
Service Sire Effect;Genetic Correlation;Litter Size;Litter Weight;Genetic Parameters;
 Cited by
Effects of Sire Breed on the Subsequent Reproductive Performances of Landrace Sows,;;;;;

아세아태평양축산학회지, 2003. vol.16. 4, pp.489-493 crossref(new window)
Variance components estimation for farrowing traits of three purebred pigs in Korea, Asian-Australasian Journal of Animal Sciences, 2017, 30, 9, 1239  crossref(new windwow)
Boldman, K., L. A. Kriese, L. D. Van Vleck, C. P. Van Tassell and S. D. Kachman. 1995. A manual for use of MTDFREML. A set of programs to obtain estimates of variances and covariances (Draft). U. S. Dept. of Agriculture, Agricultural Research Service.

Buytels, J. A. A. M. and T. Long. 1991. The effect of service sire on pigs bron alive. In: Proc. 9th Cong. Australian Assoc. of Anim. Breed. and Genet. June 24-27, 1991, Univ. of Melbourne, Victoria, Australia. p. 303.

C. Lee and C. D. Wang. 2001. Genetic Parameter Estimation with Normal and Poisson Error Mixed Models for Teat Number of Swine. Aus. J. Anim. Sci. 7:910-914.

Feng, X. 1991. Genetic parameter estimates for swine litter traits. Ph.D. Dissertation. Ohio State Univ., Columbus.

Ferraz, J. B. S. and R. K. Johnson. 1993. Animal model estimation of genetic parameters and response to selection for litter size and weight, growth and backfat in closed seedstock popluations of Large White and Landrace swine. J. Anim. Sci. 71:850-858.

Henderson, C. R. 1986. Recent developments in variance and covariance estimation. J. Anim. Sci. 63:208.

Henderson, C. R. and R. L. Quass. 1976. Multiple trait evaluation using relative's record. J. Anim. Sci. 43:1188.

Mabry, J. W., B. K. Thomas and M. N. McCarter. 1988. The effect of service sire on number born alive, number weaned and litter weaning weight in Yorkshire swine. J. Anim. Sci. 66(Suppl. 1):16(Abstr.).

Misztal, I. 1990. Restricted maximum likelihood estimation of variance components in a animal model using sparse matrix inversion and a supercomputer. J. Dairy Sci. 73:163-172.

Mrode, R. A. 1996. Linear models for the prediction of animal breeding values. Cab International, UK.

Roehe, R. 1998. Estimation of crossbreeding parameters of birth weight and litter size in Swine using Bayesian analysis. Proc. 6th World Cong. Genet. Appl. Livest. Prod. 23:523-526.

SAS. 1996. SAS/STAT guide for personal computers @6.08. SAS inst., Cary, NC., USA.

Schaeffer, L. R. 1984. Sire and cow evaluation under multiple trait models. J. Dairy Sci. 67:1567-1580.

Searle, S. R. 1982. Matrix algebra useful for statistics. John Wiley & Sons, New York.

See, M. T., J. W. Mabry and J. K. Bertrand. 1993. Restricted maximum likelihood estimation of variance components from field data for number of pigs born alive. J. Anmi. Sci. 71:2905.

Southwood, O. I. and B. W. Kennedy. 1990. Estimation of direct and maternal genetic variance for litter size in Canadian Yorkshire and Landrace swine using an animal model. J. Anim. Sci. 68:1841.

Southwood, O. I. and B. W. Kennedy. 1991. Genetic and environmental trends for litter size in swine. J. Anim. Sci. 69:3177.

Strang, G. S. and J. W. B. King. 1970. Litter productivity in large white pigs. Anim. Prod. 12:235.

Van Vleck, L. D. and L. P. Johnson. 1980. Genetic and economic implications of fetal effects on the dam. J. Dairy Sci. 63:1483.

Van Vleck, L. D., K. G. Boldman, L. A. Kriese and S. D. Kachman. 1993. A manual for use of MTDFREML, USDA. ARS.

Wang, C. D. and C. Lee. 1999. Estimation of genetic variance and covariance components for litter size and litter weight in Danish Landrace swine using a multivariate mixed model. Asian-Aus. J. Anim. Sci. 12:1015-1018.

Woodward, B. W., J. W. Mabry, M. T. See, J. K. Bertrand and L. L. Benyshek. 1993. Development of an animal model for acrossherd genetic evaluation of number born alive in swine. J. Anim. Sci. 71:2040.