There is abundant evidence for existence of genetic variance in environmental variance. Little is known about the relationships between environmental variance of one trait and levels of other traits, however. A genetic covariance between environmental variance of one trait and the level of another trait is expected to lead to non-linearity between them. Such non-linearity might occur for birth weight and survival of piglets, where animals of extreme weights have lower survival, and therefore uniformity in weight influences survival. The objectives were to derive this non-linear relationship analytically using multiple regression and apply it to piglet birth weight and piglet survival. Monte Carlo simulation was used to check the multiple regression equation derived. It explained most of the non-linearity between piglet birth weight and survival. The framework developed can help in developing optimal breeding strategies utilizing genetic variance in environmental variance.

Han A Mulder, William G Hill, Egbert F Knol

Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume Genetic Improvement Programs: Breeding objectives, economics of selection schemes, and advances in selection theory, , 014, 2014
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