Estimation of genetic parameters for daily milk yield of primiparous Ayrshire cows by random regression test-day models

Test-day data comprising of 63,331 test-day milk records of 6310 primiparou s Finnish Ayrshire cows were used to estimate genetic parameters for daily milk production. Two alternative random regression (RR) sub-models were use d to describe bleeding values for the shape of lactation curves of individu al cows: a five parameter logarithmic polynomial (ASM) or a normalised thir d order orthogonal polynomial. Permanent environment (PE) of a cow was desc ribed by either a common PE effect (ASM and OPMPE1) or a normalised third o rder orthogonal polynomial (OPMPE4). Variance components were estimated wit h an animal model using EM-REML. A multitrait (MT) approach together with c ontinuous covariance function (CF) was used to derive reference for RR esti mates. Heritability estimates obtained by ASM (0.41-0.60) and OPMPE1 (0.28- 0.53) were higher than those derived from CF analysis (0.20-0.28). Fitting the RR sub-model for PE effects strongly influenced the magnitude of herita bility estimates (0.23-0.36). Estimates of heritability were found to be hi ghest during early and late lactation when estimated by ASM and OPMPE1 mode ls, while the converse was true for those derived by CF. Estimates obtained by the OPMPE4 model were highest at the beginning of lactation and between 183 and 256 days in milk. Genetic correlations were high between consecuti ve test days, but decreased when intervals between test days increased. Whe re models ASM and OPMPE1 indicated a negative correlation between distant t est days, OPMPE4 estimates were consistent with those of CF. Due to the sta tistical complexity of RR test-day models use of MT is a more feasible appr oach for the estimation of (co)variance components for CF coefficients. (C) 2000 Elsevier Science B.V. All rights reserved.