Genet. Sel. Evol. 34 (2002) 61-81
DOI: 10.1051/gse:2001004

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

Urs Schnyder^a, Andreas Hofer^a, Florence Labroue^b and Niklaus Künzi<sup>a

a</sup>  Institute of Animal Science, Swiss Federal Institute of Technology (ETH), 8092 Zürich, Switzerland
^b  Institut technique du porc, La Motte au Vicomte, BP 3, 35651 Le Rheu cedex, France

(Received 14 September 2000; accepted 21 June 2001)

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 describe 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.

Key words: random regression / variance component / Gibbs sampling / feed intake / pig

Correspondence and reprints: Urs Schnyder
    e-mail: urs.schnyder@braunvieh.ch

© INRA, EDP Sciences 2002