Estimation of genetic parameters for test-day milk yield in Holstein cows using a random regression model

Detalhes bibliográficos
Autor(a) principal: Cobuci,Jaime Araujo
Data de Publicação: 2005
Outros Autores: Euclydes,Ricardo Frederico, Lopes,Paulo Sávio, Costa,Claudio Napolis, Torres,Robledo de Almeida, Pereira,Carmen Silva
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Genetics and Molecular Biology
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572005000100013
Resumo: Test-day milk yield records of 11,023 first-parity Holstein cows were used to estimate genetic parameters for milk yield during different lactation periods. (Co)variance components were estimated using two random regression models, RRM1 and RRM2, and the restricted maximum likelihood method, compared by the likelihood ratio test. Additive genetic variances determined by RRM1 and additive genetic and permanent environmental variances estimated by RRM2 were described, using the Wilmink function. Residual variance was constant throughout lactation for the two models. The heritability estimates obtained by RRM1 (0.34 to 0.56) were higher than those obtained by RRM2 (0.15 to 0.31). Due to the high heritability estimates for milk yield throughout lactation and the negative genetic correlation between test-day yields during different lactation periods, the RRM1 model did not fit the data. Overall, genetic correlations between individual test days tended to decrease at the extremes of the lactation trajectory, showing values close to unity for adjacent test days. The inclusion of random regression coefficients to describe permanent environmental effects led to a more precise estimation of genetic and non-genetic effects that influence milk yield.
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spelling Estimation of genetic parameters for test-day milk yield in Holstein cows using a random regression modelrandom regression modelsREML methodgenetic parameterstest-day milk yieldHolstein cowsTest-day milk yield records of 11,023 first-parity Holstein cows were used to estimate genetic parameters for milk yield during different lactation periods. (Co)variance components were estimated using two random regression models, RRM1 and RRM2, and the restricted maximum likelihood method, compared by the likelihood ratio test. Additive genetic variances determined by RRM1 and additive genetic and permanent environmental variances estimated by RRM2 were described, using the Wilmink function. Residual variance was constant throughout lactation for the two models. The heritability estimates obtained by RRM1 (0.34 to 0.56) were higher than those obtained by RRM2 (0.15 to 0.31). Due to the high heritability estimates for milk yield throughout lactation and the negative genetic correlation between test-day yields during different lactation periods, the RRM1 model did not fit the data. Overall, genetic correlations between individual test days tended to decrease at the extremes of the lactation trajectory, showing values close to unity for adjacent test days. The inclusion of random regression coefficients to describe permanent environmental effects led to a more precise estimation of genetic and non-genetic effects that influence milk yield.Sociedade Brasileira de Genética2005-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572005000100013Genetics and Molecular Biology v.28 n.1 2005reponame:Genetics and Molecular Biologyinstname:Sociedade Brasileira de Genética (SBG)instacron:SBG10.1590/S1415-47572005000100013info:eu-repo/semantics/openAccessCobuci,Jaime AraujoEuclydes,Ricardo FredericoLopes,Paulo SávioCosta,Claudio NapolisTorres,Robledo de AlmeidaPereira,Carmen Silvaeng2005-09-08T00:00:00Zoai:scielo:S1415-47572005000100013Revistahttp://www.gmb.org.br/ONGhttps://old.scielo.br/oai/scielo-oai.php||editor@gmb.org.br1678-46851415-4757opendoar:2005-09-08T00:00Genetics and Molecular Biology - Sociedade Brasileira de Genética (SBG)false
dc.title.none.fl_str_mv Estimation of genetic parameters for test-day milk yield in Holstein cows using a random regression model
title Estimation of genetic parameters for test-day milk yield in Holstein cows using a random regression model
spellingShingle Estimation of genetic parameters for test-day milk yield in Holstein cows using a random regression model
Cobuci,Jaime Araujo
random regression models
REML method
genetic parameters
test-day milk yield
Holstein cows
title_short Estimation of genetic parameters for test-day milk yield in Holstein cows using a random regression model
title_full Estimation of genetic parameters for test-day milk yield in Holstein cows using a random regression model
title_fullStr Estimation of genetic parameters for test-day milk yield in Holstein cows using a random regression model
title_full_unstemmed Estimation of genetic parameters for test-day milk yield in Holstein cows using a random regression model
title_sort Estimation of genetic parameters for test-day milk yield in Holstein cows using a random regression model
author Cobuci,Jaime Araujo
author_facet Cobuci,Jaime Araujo
Euclydes,Ricardo Frederico
Lopes,Paulo Sávio
Costa,Claudio Napolis
Torres,Robledo de Almeida
Pereira,Carmen Silva
author_role author
author2 Euclydes,Ricardo Frederico
Lopes,Paulo Sávio
Costa,Claudio Napolis
Torres,Robledo de Almeida
Pereira,Carmen Silva
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Cobuci,Jaime Araujo
Euclydes,Ricardo Frederico
Lopes,Paulo Sávio
Costa,Claudio Napolis
Torres,Robledo de Almeida
Pereira,Carmen Silva
dc.subject.por.fl_str_mv random regression models
REML method
genetic parameters
test-day milk yield
Holstein cows
topic random regression models
REML method
genetic parameters
test-day milk yield
Holstein cows
description Test-day milk yield records of 11,023 first-parity Holstein cows were used to estimate genetic parameters for milk yield during different lactation periods. (Co)variance components were estimated using two random regression models, RRM1 and RRM2, and the restricted maximum likelihood method, compared by the likelihood ratio test. Additive genetic variances determined by RRM1 and additive genetic and permanent environmental variances estimated by RRM2 were described, using the Wilmink function. Residual variance was constant throughout lactation for the two models. The heritability estimates obtained by RRM1 (0.34 to 0.56) were higher than those obtained by RRM2 (0.15 to 0.31). Due to the high heritability estimates for milk yield throughout lactation and the negative genetic correlation between test-day yields during different lactation periods, the RRM1 model did not fit the data. Overall, genetic correlations between individual test days tended to decrease at the extremes of the lactation trajectory, showing values close to unity for adjacent test days. The inclusion of random regression coefficients to describe permanent environmental effects led to a more precise estimation of genetic and non-genetic effects that influence milk yield.
publishDate 2005
dc.date.none.fl_str_mv 2005-03-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572005000100013
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572005000100013
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S1415-47572005000100013
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Genética
publisher.none.fl_str_mv Sociedade Brasileira de Genética
dc.source.none.fl_str_mv Genetics and Molecular Biology v.28 n.1 2005
reponame:Genetics and Molecular Biology
instname:Sociedade Brasileira de Genética (SBG)
instacron:SBG
instname_str Sociedade Brasileira de Genética (SBG)
instacron_str SBG
institution SBG
reponame_str Genetics and Molecular Biology
collection Genetics and Molecular Biology
repository.name.fl_str_mv Genetics and Molecular Biology - Sociedade Brasileira de Genética (SBG)
repository.mail.fl_str_mv ||editor@gmb.org.br
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