Test day milk, fat and protein yields from first lactations of 29,914 cows in 139 herds were used together with average daily temperature to study alternative selection criteria for heat tolerance. A random regression model fitting a cubic Legendre polynomial to the additive genetic effect was used. Eigenfunctions of the estimatedgenetic covariance matrices showed a dominant component associated to the level of production and a second component showing constant values in the mid range of temperatures and increasing or decreasing values outside that range, which could be used as a selection criteria for heat tolerance. This component explained 4, 15 and 11 % of the total variation for milk, fat and protein, respectively. The results suggest that the antagonistic relationship found between level and slope might be avoided using the eigendecomposition of the genetic covariance matrix of the random regression coefficients.
Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume Genetic Improvement Programs: Selection for harsh environments and management of animal genetic resources, , 033, 2014
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