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Comparison of statistical models to analyse the genetic effect on within-litter variance in pigs

Published online by Cambridge University Press:  01 November 2008

D. Wittenburg ,
V. Guiard ,
F. Teuscher  and
N. Reinsch
D. Wittenburg
Affiliation:
Forschungsinstitut für die Biologie landwirtschaftlicher Nutztiere, FB Genetik und Biometrie, Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany
V. Guiard
Affiliation:
Forschungsinstitut für die Biologie landwirtschaftlicher Nutztiere, FB Genetik und Biometrie, Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany
F. Teuscher
Affiliation:
Forschungsinstitut für die Biologie landwirtschaftlicher Nutztiere, FB Genetik und Biometrie, Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany
N. Reinsch*
Affiliation:
Forschungsinstitut für die Biologie landwirtschaftlicher Nutztiere, FB Genetik und Biometrie, Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany
*
E-mail: reinsch@fbn-dummerstorf.de
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Abstract

Genetics affects not only the weight of piglets at birth but also the variability of birth weight within litter. Previous studies on this topic assigned the sample standard deviation of piglet birth weights within litter as an observation to the sow. However, the contribution of the difference in mean birth weight per sex on the within-litter variance has been neglected so far. This work deals with the genetic effect on within-litter variance when different statistical models with different distributional assumptions are used and considers the sex effect and appropriate weights per trait. Traits were formed from the pooled sample variance of male and female birth weights within litter. A linear model approach was fitted to the logarithmized within-litter variance and the sample standard deviation. A generalized linear model with gamma-distributed residuals and log-link function was applied to the untransformed sample variance. Models were compared by analysing data from 9439 litters from Landrace and Large White of a commercial breeding programme. The estimates of heritability for different traits ranged from 7% to 11%. Although the generalized linear mixed model is preferred from a mathematical view, the rank correlations between breeding values of the linear mixed models and the generalized linear mixed model were relatively high, i.e. 94% to 98%. By residual diagnostics, a linear mixed model using the weighted and pooled within-litter standard deviation was identified as most suitable.

Keywords

birth weightwithin-litter variationgamma distributionlinear mixed modelgeneralized linear mixed model
Type
Full Paper
Information
animal , Volume 2 , Issue 11 , November 2008 , pp. 1559 - 1568
Copyright
Copyright © The Animal Consortium 2008

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