Random regression test-day models (RRM) are preferred above lactation models for milk production traits because of their abilities to model a separate lactation curve for every animal and to account for short-term environmental effects. Precise estimates of genetic parameters are needed for genetic evaluation with models using test-day data. Estimating variance components of a RRM is not a straightforward task. Misztal et al. (2000) showed that the range and pattern of variances and heritability across days in milk vary widely among studies on RRM. Differences in estimated parameters may be due to the size of the data and the functions used to describe random regressions. Third and fourth order Legendre polynomials where suggested (Pool and Meuwissen, 2000) as a compromise between model complexity and accuracy of genetic evaluation. If estimated parameters are incorrect, however, the advantage of RRM over lactation model may not be fully realized. The objective of this simulation study was to analyze the impact of incorrect variance components on the estimation of breeding values with RRM
Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume 2002. Session 1, , 1.09, 2002
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