Abstract
An assumption underlying the use of BLUP in the context of genetic evaluation is that the expectations of the true breeding values are null. The aim of this paper is to address the robustness of genetic evaluation, in terms of the prediction of genetic trend and selection responses, when this assumption is violated. Animals that are likely to be genetically different are the animals for whom the accuracy of comparison is low, because they are bred in different environments which are not highly connected. In such a case, the environment and genetic effects are partially confounded and the genetic differences between animals in different environments are underestimated. An analytical criterion of robustness is proposed: the lowest coefficient of determination (CD 1) of a comparison between animals included in the evaluation. Its relationship with bias in genetic evaluation is explained. A numerical application considers two kinds of planned progeny test designs for French AI sire evaluation: the “reference sire design” and the “repeater sire design”. Using Monte-Carlo simulations, prediction of genetic trend is shown to be in close relation with CD 1. CD 1 appears to be a good indicator of the robustness of the design and a measure of the part of genetic trend that can be predicted. According to the number of progeny recorded per sire, the repeater sire design only accounted for 3 to 12% of the genetic trend whereas the reference sire design accounted for 22 to 59% for a trait of h 2=0.40. However, in terms of the selection response, the two designs are equivalent when genetic trend was below 0.5 σ a, which is always the case in animal breeding programs.
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