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Genetic Parameters for Litter Size in Pigs Using a Random Regression Model

  • Lukovic, Z. (Faculty of Agriculture, University of Zagreb) ;
  • Uremovic, M. (Faculty of Agriculture, University of Zagreb) ;
  • Konjacic, M. (Faculty of Agriculture, University of Zagreb) ;
  • Uremovic, Z. (Faculty of Agriculture, University of Zagreb) ;
  • Vincek, D. (Croatian Livestock Center)
  • Received : 2006.03.10
  • Accepted : 2006.07.10
  • Published : 2007.02.01

Abstract

Dispersion parameters for the number of piglets born alive were estimated using a repeatability and random regression model. Six sow breeds/lines were included in the analysis: Swedish Landrace, Large White and both crossbred lines between them, German Landrace and their cross with Large White. Fixed part of the model included sow genotype, mating season as month-year interaction, parity and weaning to conception interval as class effects. The age at farrowing was modelled as a quadratic regression nested within parity. The previous lactation length was fitted as a linear regression. Random regressions for parity on Legendre polynomials were included for direct additive genetic, permanent environmental, and common litter environmental effects. Orthogonal Legendre polynomials from the linear to the cubic power were fitted. In the repeatability model estimate of heritability was 0.07, permanent environmental effect as ratio was 0.04, and common litter environmental effect as ratio was 0.01. Estimates of genetic parameters with the random regression model were generally higher than in the repeatability model, except for the common litter environmental effect. Estimates of heritability ranged from 0.06 to 0.10. Permanent environmental effect as a ratio increased along a trajectory from 0.03 to 0.11. Magnitudes of common litter effect were small (around 0.01). The eigenvalues of covariance functions showed that between 7 and 8 % of genetic variability was explained by individual genetic curves of sows. This proportion was mainly covered by linear and quadratic coefficients. Results suggest that the random regression model could be used for genetic analysis of litter size.

Keywords

References

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