Variance component estimates applying random regression models for test-day milk yield in Caracu heifers (Bos taurus Artiodactyla, Bovidae)
Random regression models (RRM) were used to estimate covariance functions for 2,155 first-lactation milk yields of native Brazilian Caracu heifers. The models included contemporary group (defined as year-month of test and paddock) fixed effects, and quadratic effect of age of cow at calving. Genetic...
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Sociedade Brasileira de Genética
2008-01-01
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doaj-ccd8f9290d484c7892f1aeeb2e8dd0f12020-11-24T21:11:16ZengSociedade Brasileira de GenéticaGenetics and Molecular Biology1415-47571678-46852008-01-0131366567310.1590/S1415-47572008000400011Variance component estimates applying random regression models for test-day milk yield in Caracu heifers (Bos taurus Artiodactyla, Bovidae)Lenira El FaroVera Lucia CardosoLucia Galvão de AlbuquerqueRandom regression models (RRM) were used to estimate covariance functions for 2,155 first-lactation milk yields of native Brazilian Caracu heifers. The models included contemporary group (defined as year-month of test and paddock) fixed effects, and quadratic effect of age of cow at calving. Genetic and permanent environmental effects were fitted by a random regression model and Legendre polynomials of days in milk (DIM). Schwarz's Bayesian information criteria (BIC) indicated that the best RRM assumed a six coefficient function for both random effects and a sixth order variance function for residual structure. Akaike's information criteria suggested a model with the same number of coefficients for both effects and a residual structure fitted by a step function with 15 variances. Phenotypic, additive genetic, permanent environmental and residual variances were higher at the beginning and declined during lactation. The RRM heritability estimates were 0.09 to 0.26 and generally higher at the beginning and end of lactation. Some unexpected negative genetic correlations emerged when higher order covariance functions were used. A model with four coefficients for additive genetic covariance function explains more parsimoniously the changes in genetic variation with DIM since the genetic parameter was more acceptable and BIC was close to that for a six coefficient covariance function.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572008000400011covariance functionsdairy cattlegenetic parameterslongitudinal datamilk yield |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lenira El Faro Vera Lucia Cardoso Lucia Galvão de Albuquerque |
spellingShingle |
Lenira El Faro Vera Lucia Cardoso Lucia Galvão de Albuquerque Variance component estimates applying random regression models for test-day milk yield in Caracu heifers (Bos taurus Artiodactyla, Bovidae) Genetics and Molecular Biology covariance functions dairy cattle genetic parameters longitudinal data milk yield |
author_facet |
Lenira El Faro Vera Lucia Cardoso Lucia Galvão de Albuquerque |
author_sort |
Lenira El Faro |
title |
Variance component estimates applying random regression models for test-day milk yield in Caracu heifers (Bos taurus Artiodactyla, Bovidae) |
title_short |
Variance component estimates applying random regression models for test-day milk yield in Caracu heifers (Bos taurus Artiodactyla, Bovidae) |
title_full |
Variance component estimates applying random regression models for test-day milk yield in Caracu heifers (Bos taurus Artiodactyla, Bovidae) |
title_fullStr |
Variance component estimates applying random regression models for test-day milk yield in Caracu heifers (Bos taurus Artiodactyla, Bovidae) |
title_full_unstemmed |
Variance component estimates applying random regression models for test-day milk yield in Caracu heifers (Bos taurus Artiodactyla, Bovidae) |
title_sort |
variance component estimates applying random regression models for test-day milk yield in caracu heifers (bos taurus artiodactyla, bovidae) |
publisher |
Sociedade Brasileira de Genética |
series |
Genetics and Molecular Biology |
issn |
1415-4757 1678-4685 |
publishDate |
2008-01-01 |
description |
Random regression models (RRM) were used to estimate covariance functions for 2,155 first-lactation milk yields of native Brazilian Caracu heifers. The models included contemporary group (defined as year-month of test and paddock) fixed effects, and quadratic effect of age of cow at calving. Genetic and permanent environmental effects were fitted by a random regression model and Legendre polynomials of days in milk (DIM). Schwarz's Bayesian information criteria (BIC) indicated that the best RRM assumed a six coefficient function for both random effects and a sixth order variance function for residual structure. Akaike's information criteria suggested a model with the same number of coefficients for both effects and a residual structure fitted by a step function with 15 variances. Phenotypic, additive genetic, permanent environmental and residual variances were higher at the beginning and declined during lactation. The RRM heritability estimates were 0.09 to 0.26 and generally higher at the beginning and end of lactation. Some unexpected negative genetic correlations emerged when higher order covariance functions were used. A model with four coefficients for additive genetic covariance function explains more parsimoniously the changes in genetic variation with DIM since the genetic parameter was more acceptable and BIC was close to that for a six coefficient covariance function. |
topic |
covariance functions dairy cattle genetic parameters longitudinal data milk yield |
url |
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572008000400011 |
work_keys_str_mv |
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