Random regression models with B-splines to estimate genetic parameters for body weight of young bulls in performance tests
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | LOCUS Repositório Institucional da UFV |
Texto Completo: | https://locus.ufv.br//handle/123456789/31333 https://doi.org/10.1590/rbz4720150300 |
Resumo: | The objective of this study was to estimate genetic parameters for body weight of beef cattle in performance tests. Different random regression models with quadratic B-splines and heterogeneous residual variance were fitted to estimate covariance functions for body weights of Nellore and crossbred Charolais × Nellore bulls. The criteria −2 residual log-likelihood (−2RLL), Akaike Information Criterion (AIC), and consistent AIC (CAIC) were used to choose the most appropriate model. For Nellore bulls, residual variance was modeled with six classes of age, and direct additive genetic and permanent environment effects were modeled with quadratic B-splines with two and one intervals, respectively. For crossbred bulls, quadratic B-splines with one interval fitted direct additive genetic and permanent environment effects and nine classes of age were needed to fit residual variance. Pooling classes of age with up to 40% in difference of residual variances does not compromise the fit of the model. Heritability for body weight in performance tests are moderate (>0.25, for crossbred bulls) to high (>0.5, for Nellore bulls) and genetic correlation between weights over the test are also high (>0.65). Then, selection of young bulls in performance test is an efficient tool to increase body weight in beef cattle |
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Scalez, Daiane Cristina BeckerFragomeni, Breno de OliveiraSantos, Dalinne Chrystian Carvalho dosPassafaro, Tiago LucianoAlencar, Maurício Mello deToral, Fabio Luiz Buranelo2023-08-21T14:07:35Z2023-08-21T14:07:35Z2018-07-241806-9290https://locus.ufv.br//handle/123456789/31333https://doi.org/10.1590/rbz4720150300The objective of this study was to estimate genetic parameters for body weight of beef cattle in performance tests. Different random regression models with quadratic B-splines and heterogeneous residual variance were fitted to estimate covariance functions for body weights of Nellore and crossbred Charolais × Nellore bulls. The criteria −2 residual log-likelihood (−2RLL), Akaike Information Criterion (AIC), and consistent AIC (CAIC) were used to choose the most appropriate model. For Nellore bulls, residual variance was modeled with six classes of age, and direct additive genetic and permanent environment effects were modeled with quadratic B-splines with two and one intervals, respectively. For crossbred bulls, quadratic B-splines with one interval fitted direct additive genetic and permanent environment effects and nine classes of age were needed to fit residual variance. Pooling classes of age with up to 40% in difference of residual variances does not compromise the fit of the model. Heritability for body weight in performance tests are moderate (>0.25, for crossbred bulls) to high (>0.5, for Nellore bulls) and genetic correlation between weights over the test are also high (>0.65). Then, selection of young bulls in performance test is an efficient tool to increase body weight in beef cattleengBrazilian Journal of Animal ScienceR. Bras. Zootec., 47:e20150300, 2018Creative Commons Attribution Licenseinfo:eu-repo/semantics/openAccessanimal breedingBos indicusgenetic correlationheritabilityRandom regression models with B-splines to estimate genetic parameters for body weight of young bulls in performance testsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlereponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINAL1806-9290-rbz-47-e20150300.pdf1806-9290-rbz-47-e20150300.pdfartigoapplication/pdf1787275https://locus.ufv.br//bitstream/123456789/31333/1/1806-9290-rbz-47-e20150300.pdff4f686d9435ae56e7939c6f2edc9520cMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://locus.ufv.br//bitstream/123456789/31333/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52123456789/313332023-08-21 11:07:36.676oai:locus.ufv.br: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Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452023-08-21T14:07:36LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false |
dc.title.pt-BR.fl_str_mv |
Random regression models with B-splines to estimate genetic parameters for body weight of young bulls in performance tests |
title |
Random regression models with B-splines to estimate genetic parameters for body weight of young bulls in performance tests |
spellingShingle |
Random regression models with B-splines to estimate genetic parameters for body weight of young bulls in performance tests Scalez, Daiane Cristina Becker animal breeding Bos indicus genetic correlation heritability |
title_short |
Random regression models with B-splines to estimate genetic parameters for body weight of young bulls in performance tests |
title_full |
Random regression models with B-splines to estimate genetic parameters for body weight of young bulls in performance tests |
title_fullStr |
Random regression models with B-splines to estimate genetic parameters for body weight of young bulls in performance tests |
title_full_unstemmed |
Random regression models with B-splines to estimate genetic parameters for body weight of young bulls in performance tests |
title_sort |
Random regression models with B-splines to estimate genetic parameters for body weight of young bulls in performance tests |
author |
Scalez, Daiane Cristina Becker |
author_facet |
Scalez, Daiane Cristina Becker Fragomeni, Breno de Oliveira Santos, Dalinne Chrystian Carvalho dos Passafaro, Tiago Luciano Alencar, Maurício Mello de Toral, Fabio Luiz Buranelo |
author_role |
author |
author2 |
Fragomeni, Breno de Oliveira Santos, Dalinne Chrystian Carvalho dos Passafaro, Tiago Luciano Alencar, Maurício Mello de Toral, Fabio Luiz Buranelo |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Scalez, Daiane Cristina Becker Fragomeni, Breno de Oliveira Santos, Dalinne Chrystian Carvalho dos Passafaro, Tiago Luciano Alencar, Maurício Mello de Toral, Fabio Luiz Buranelo |
dc.subject.eng.fl_str_mv |
animal breeding Bos indicus genetic correlation heritability |
topic |
animal breeding Bos indicus genetic correlation heritability |
description |
The objective of this study was to estimate genetic parameters for body weight of beef cattle in performance tests. Different random regression models with quadratic B-splines and heterogeneous residual variance were fitted to estimate covariance functions for body weights of Nellore and crossbred Charolais × Nellore bulls. The criteria −2 residual log-likelihood (−2RLL), Akaike Information Criterion (AIC), and consistent AIC (CAIC) were used to choose the most appropriate model. For Nellore bulls, residual variance was modeled with six classes of age, and direct additive genetic and permanent environment effects were modeled with quadratic B-splines with two and one intervals, respectively. For crossbred bulls, quadratic B-splines with one interval fitted direct additive genetic and permanent environment effects and nine classes of age were needed to fit residual variance. Pooling classes of age with up to 40% in difference of residual variances does not compromise the fit of the model. Heritability for body weight in performance tests are moderate (>0.25, for crossbred bulls) to high (>0.5, for Nellore bulls) and genetic correlation between weights over the test are also high (>0.65). Then, selection of young bulls in performance test is an efficient tool to increase body weight in beef cattle |
publishDate |
2018 |
dc.date.issued.fl_str_mv |
2018-07-24 |
dc.date.accessioned.fl_str_mv |
2023-08-21T14:07:35Z |
dc.date.available.fl_str_mv |
2023-08-21T14:07:35Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://locus.ufv.br//handle/123456789/31333 |
dc.identifier.issn.none.fl_str_mv |
1806-9290 |
dc.identifier.doi.pt-BR.fl_str_mv |
https://doi.org/10.1590/rbz4720150300 |
identifier_str_mv |
1806-9290 |
url |
https://locus.ufv.br//handle/123456789/31333 https://doi.org/10.1590/rbz4720150300 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartofseries.pt-BR.fl_str_mv |
R. Bras. Zootec., 47:e20150300, 2018 |
dc.rights.driver.fl_str_mv |
Creative Commons Attribution License info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Creative Commons Attribution License |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Brazilian Journal of Animal Science |
publisher.none.fl_str_mv |
Brazilian Journal of Animal Science |
dc.source.none.fl_str_mv |
reponame:LOCUS Repositório Institucional da UFV instname:Universidade Federal de Viçosa (UFV) instacron:UFV |
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Universidade Federal de Viçosa (UFV) |
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UFV |
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UFV |
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LOCUS Repositório Institucional da UFV |
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LOCUS Repositório Institucional da UFV |
bitstream.url.fl_str_mv |
https://locus.ufv.br//bitstream/123456789/31333/1/1806-9290-rbz-47-e20150300.pdf https://locus.ufv.br//bitstream/123456789/31333/2/license.txt |
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fabiojreis@ufv.br |
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