Advertisement

Multiple trait model combining random regressions for daily feed intake with single measured performance traits of growing pigs

  • Urs SchnyderEmail author
  • Andreas Hofer
  • Florence Labroue
  • Niklaus Künzi
Open Access
Research

Abstract

A random regression model for daily feed intake and a conventional multiple trait animal model for the four traits average daily gain on test (ADG), feed conversion ratio (FCR), carcass lean content and meat quality index were combined to analyse data from 1 449 castrated male Large White pigs performance tested in two French central testing stations in 1997. Group housed pigs fed ad libitum with electronic feed dispensers were tested from 35 to 100 kg live body weight. A quadratic polynomial in days on test was used as a regression function for weekly means of daily feed intake and to escribe its residual variance. The same fixed (batch) and random (additive genetic, pen and individual permanent environmental) effects were used for regression coefficients of feed intake and single measured traits. Variance components were estimated by means of a Bayesian analysis using Gibbs sampling. Four Gibbs chains were run for 550 000 rounds each, from which 50 000 rounds were discarded from the burn-in period. Estimates of posterior means of covariance matrices were calculated from the remaining two million samples. Low heritabilities of linear and quadratic regression coefficients and their unfavourable genetic correlations with other performance traits reveal that altering the shape of the feed intake curve by direct or indirect selection is difficult.

Keywords

random regression variance component Gibbs sampling feed intake pig 

(To access the full article, please see PDF)

Copyright information

© INRA, EDP Sciences 2002

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors and Affiliations

  • Urs Schnyder
    • 1
    Email author
  • Andreas Hofer
    • 1
  • Florence Labroue
    • 2
  • Niklaus Künzi
    • 1
  1. 1.Institute of Animal ScienceSwiss Federal Institute of Technology (ETH)ZürichSwitzerland
  2. 2.Institut technique du porcLa Motte au VicomteLe Rheu cedexFrance

Personalised recommendations