Expected efficiency of selection for growth in a French beef cattle breeding scheme. II. Prediction of asymptotic genetic gain in a heterogeneous population

Abstract

Asymptotic genetic gains and lags are derived in French beef cattle breeding schemes for an objective including direct and maternal effects on growth. A simple general method using matrix algebra is presented to simultaneously calculate asymptotic genetic gains and lags, whatever the population structure. The heterogeneity of use of artificial insemination (AI) in selection herds is considered. At the same overall rate of AI use, larger asymptotic genetic gains can be obtained by concentrating AI in only a fraction of the herds instead of keeping the same lower rate in all herds. An application concerns the Limousin selection nucleus, where 23% of calves are bred by AI in only 50% of the herds. When an aggregate breeding objective for growth is considered, positive annual asymptotic genetic gains are expected in both direct (+ 0.13 genetic standard deviation) and maternal effects (+ 0.05 genetic standard deviation) on growth, despite the negative estimates (around - 0.2) of genetic direct-maternal correlations. The major part of the genetic gains in direct and maternal effects are due to AI sire selection and dam selection respectively. Taking into account sampling uncertainty in estimates of preweaning genetic parameters leads to the conclusion that the predicted asymptotic response in maternal effects is positive with a very high probability. Nevertheless, strongly negative (around - 0.6) estimates of correlations between direct and maternal effects lead to negative responses in maternal effects. © 1995 Elsevier/INRA.