Individual animal model estimates of genetic correlations between performance test and reproduction traits of Landrace pigs performance tested in a commercial nucleus herd

A - Papers appearing in refereed journals

Crump, R. E., Thompson, R., Haley, C. S. and Mercer, J. 1997. Individual animal model estimates of genetic correlations between performance test and reproduction traits of Landrace pigs performance tested in a commercial nucleus herd. Animal Science. 65 (2), pp. 291-298.

AuthorsCrump, R. E., Thompson, R., Haley, C. S. and Mercer, J.
Abstract

Bivariate individual animal model estimates of genetic and environmental correlations between reproduction traits (number born alive and average piglet weight) and performance test traits (ultrasonic backfat depth, average daily food intake, average daily gain and food conversion ratio) of Landrace pigs were calculated. The estimates were produced using a derivative-free restricted maximum likelihood algorithm to calculate likelihoods for different combinations of covariance parameters. A quadratic approximation to the likelihood surface was used to estimate the maximum likelihood values with respect to the covariance parameters. For all combinations of performance test traits with reproduction traits the resulting genetic and residual correlation estimates were low, with a maximum absolute value of 0·233 for the genetic correlation between food conversion ratio and number born alive. Standard errors of genetic correlation estimates were between 0·11 and 0·15. There is expected to have been little effect upon reproduction traits from the rigorous selection carried out upon performance test traits over the years. When incorporating reproduction data into best linear unbiased prediction analysis procedures it should be possible to analyse performance test and reproduction traits from this population separately, thereby making savings on computer resources and time required for the analysis of all traits.

Year of Publication1997
JournalAnimal Science
Journal citation65 (2), pp. 291-298
Digital Object Identifier (DOI)doi:10.1017/S135772980001660X
Open accessPublished as non-open access
Funder project or code207
445
Project: 141673
Output statusPublished
Publication dates
Online02 Sep 2010
Print01 Oct 1997
Copyright licensePublisher copyright
ISSN1357-7298
PublisherCambridge University Press (CUP)

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