Including an additional systematic environmental effect within a generation in an evaluation model improves accuracy of prediction of breeding values in a closed herd of pigs

Abstract

The present study evaluated the advantage of mixed-model techniques over a selection index under different magnitudes of an additional systematic environmental effect (ASEE) in terms of accuracy of prediction and expected genetic gain. The data attempted to simulate a closed herd in a pig breeding program. The base population (G 0 ) consisted of 10 males and 50 females. Six generations (G 0 to G 5 ) were selected by using a selection index of three traits without overlapping. Additional systematic environmental constants with four levels in a generation were assigned from a uniform distribution at different ranges. Breeding values of animals in the last generation (G 5 ) were estimated on the basis of an index of individual phenotype (SI-U), SI-U adjusted for ASEE using a least-squares mean (SI-A), best linear unbiased prediction using an animal model excluding ASEE (AM-E), and an animal model including ASEE (AM-I). Accuracy of prediction and expected genetic gain were larger by the animal model than by the selection index, even if heritability of the traits selected was high and ASEE was set to zero. When ASEE was zero, the accuracy of prediction and expected genetic gain given by SI-U and AM-I were similar to those given by SI-A and AM-E, respectively. However, the differences in accuracy and expected gain between SI-U and AI-A and between AM-I and AM-E increased as the range of ASEE increased. It was concluded that selection based on an animal model was more effective than index selection, even if the herd environment was uniform and traits with high heritability were selected, and that it should be always included in an evaluation model, however slight any systematic environmental effect may be in a closed herd.