Genetic evaluation of on-farm tested pigs using an animal model II. Prediction of breeding values with a multiple trait model

Abstract

The aim of this study was to examine the application of best linear unbiased prediction (BLUP)with a multiple trait animal model for the genetic evaluation of on-farm tested pigs. The analysis was based on test results of 197 949 Yorkshire (Y) and 70 550 Landrace (L) pigs tested in Switzerland from 1976 to 1987. The two traits considered were average daily gain (ADG) and premium cuts in proportion to carcass weight (PCP) estimated from ultrasonic measurements. The model contained fixed herd × year × season, sex, unknown parent group effects and the linear regression on live weight, as well as random litter and animal effects. The mixed model equations with 582 698 (Y) and 211 768 (L) unknowns were solved by ‘iteration on the data’. Inbreeding was taken into account. The average inbreeding coefficient of parents born in 1986 was 1% and 1.5% in the Y and L breed, respectively. On the supercomputer CRAY X-MP/28 all the data were kept in memory. The computing time (CPU time) required for one round of iteration was 2.5 (Y) and 0.9 (L) seconds. 100 rounds of iteration were sufficient for the estimation of genetic trend. In both traits genetic trend was positive for both breeds. During the 12 years considered, ADG improved genetically by 6.5 g/day and 10.3 g/day, and PCP by 1.9% and 1.2% in the Y and L breed respectively. The effect of ignoring inbreeding on predicted breeding values was small.