Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials
Autor(a) principal: | |
---|---|
Data de Publicação: | 2014 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Pesquisa Agropecuária Brasileira (Online) |
Texto Completo: | https://seer.sct.embrapa.br/index.php/pab/article/view/18731 |
Resumo: | The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test‑day milk yield (TDMY) from 2,816 first‑lactation Guzerat cows were used. TDMY grouped into 10‑monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second‑order Legendre polynomial for the additive genetic effect, and a fifth‑order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second‑order Legendre polynomial for the additive genetic effect, and that with a fourth‑order for the permanent environmental effect could also be employed in these analyses. |
id |
EMBRAPA-4_c26f0711d5a4998a48d215f8686d959a |
---|---|
oai_identifier_str |
oai:ojs.seer.sct.embrapa.br:article/18731 |
network_acronym_str |
EMBRAPA-4 |
network_name_str |
Pesquisa Agropecuária Brasileira (Online) |
repository_id_str |
|
spelling |
Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomialsModelos de regressão aleatória para estimação de parâmetros genéticos para produção de leite da raça Guzerá com uso de polinômios ortogonais de LegendreBos indicus; covariance functions; lactation curve; test‑day modelBos indicus; covariance functions; lactation curve; test‑day modelThe objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test‑day milk yield (TDMY) from 2,816 first‑lactation Guzerat cows were used. TDMY grouped into 10‑monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second‑order Legendre polynomial for the additive genetic effect, and a fifth‑order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second‑order Legendre polynomial for the additive genetic effect, and that with a fourth‑order for the permanent environmental effect could also be employed in these analyses.O objetivo deste trabalho foi comparar modelos de regressão aleatória para a estimação de parâmetros genéticos da produção de leite de Guzerá, com uso dos polinômios ortogonais de Legendre. Foram utilizados 20.524 registros da produção de leite no dia do controle (PLDC) de 2.816 vacas da raça Guzerá em primeira lactação. Agrupadas em 10 classes mensais, as PLDC foram analisadas quanto aos efeitos genéticos aditivos, e aos de ambiente permanente e residual (efeitos aleatórios); enquanto efeitos de grupo de contemporâneos, covariável idade da vaca ao parto (efeito linear e quadrático) e a curva média de lactação foram analisados como efeitos fixos. Trajetórias quanto aos efeitos aditivos genéticos e de ambiente permanente foram modeladas por meio de uma função de covariância com uso do polinômio de Legendre de segunda à quinta ordem. As variâncias residuais foram consideradas em 1, 4, 6 ou 10 classes de variância. O melhor modelo teve seis classes de variância residual. As estimativas de herdabilidade para os registros de PLDC variaram de 0.19 a 0.32. O modelo de regressão aleatória que utilizou o polinômio de Legendre de segunda ordem, quanto ao efeito genético aditivo, e o polinômio de quinta ordem, quanto ao efeito de ambiente permanente, é o mais adequado para a comparação dos principais critérios utilizados. O modelo que utilizou o polinômio de Legendre de segunda ordem, quanto ao efeito genético aditivo, e o de quarta ordem, quanto ao efeito de ambiente permanente, pode ser utilizado nestas análises.Pesquisa Agropecuaria BrasileiraPesquisa Agropecuária BrasileiraCNPqFAPEMIGPeixoto, Maria Gabriela Campolina DinizSantos, Daniel Jordan de AbreuBorquis, Rusbel Raul AspilcuetaBruneli, Frank Ângelo TomitaPanetto, João Cláudio do CarmoTonhati, Humberto2014-06-18info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.sct.embrapa.br/index.php/pab/article/view/18731Pesquisa Agropecuaria Brasileira; v.49, n.5, maio 2014; 372-383Pesquisa Agropecuária Brasileira; v.49, n.5, maio 2014; 372-3831678-39210100-104xreponame:Pesquisa Agropecuária Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAenghttps://seer.sct.embrapa.br/index.php/pab/article/view/18731/12651https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/18731/11926https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/18731/11927https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/18731/11928https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/18731/11929info:eu-repo/semantics/openAccess2014-07-01T19:03:19Zoai:ojs.seer.sct.embrapa.br:article/18731Revistahttp://seer.sct.embrapa.br/index.php/pabPRIhttps://old.scielo.br/oai/scielo-oai.phppab@sct.embrapa.br || sct.pab@embrapa.br1678-39210100-204Xopendoar:2014-07-01T19:03:19Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials Modelos de regressão aleatória para estimação de parâmetros genéticos para produção de leite da raça Guzerá com uso de polinômios ortogonais de Legendre |
title |
Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials |
spellingShingle |
Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials Peixoto, Maria Gabriela Campolina Diniz Bos indicus; covariance functions; lactation curve; test‑day model Bos indicus; covariance functions; lactation curve; test‑day model |
title_short |
Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials |
title_full |
Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials |
title_fullStr |
Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials |
title_full_unstemmed |
Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials |
title_sort |
Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials |
author |
Peixoto, Maria Gabriela Campolina Diniz |
author_facet |
Peixoto, Maria Gabriela Campolina Diniz Santos, Daniel Jordan de Abreu Borquis, Rusbel Raul Aspilcueta Bruneli, Frank Ângelo Tomita Panetto, João Cláudio do Carmo Tonhati, Humberto |
author_role |
author |
author2 |
Santos, Daniel Jordan de Abreu Borquis, Rusbel Raul Aspilcueta Bruneli, Frank Ângelo Tomita Panetto, João Cláudio do Carmo Tonhati, Humberto |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
CNPq FAPEMIG |
dc.contributor.author.fl_str_mv |
Peixoto, Maria Gabriela Campolina Diniz Santos, Daniel Jordan de Abreu Borquis, Rusbel Raul Aspilcueta Bruneli, Frank Ângelo Tomita Panetto, João Cláudio do Carmo Tonhati, Humberto |
dc.subject.por.fl_str_mv |
Bos indicus; covariance functions; lactation curve; test‑day model Bos indicus; covariance functions; lactation curve; test‑day model |
topic |
Bos indicus; covariance functions; lactation curve; test‑day model Bos indicus; covariance functions; lactation curve; test‑day model |
description |
The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test‑day milk yield (TDMY) from 2,816 first‑lactation Guzerat cows were used. TDMY grouped into 10‑monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second‑order Legendre polynomial for the additive genetic effect, and a fifth‑order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second‑order Legendre polynomial for the additive genetic effect, and that with a fourth‑order for the permanent environmental effect could also be employed in these analyses. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-06-18 |
dc.type.none.fl_str_mv |
|
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://seer.sct.embrapa.br/index.php/pab/article/view/18731 |
url |
https://seer.sct.embrapa.br/index.php/pab/article/view/18731 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://seer.sct.embrapa.br/index.php/pab/article/view/18731/12651 https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/18731/11926 https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/18731/11927 https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/18731/11928 https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/18731/11929 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira Pesquisa Agropecuária Brasileira |
publisher.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira Pesquisa Agropecuária Brasileira |
dc.source.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira; v.49, n.5, maio 2014; 372-383 Pesquisa Agropecuária Brasileira; v.49, n.5, maio 2014; 372-383 1678-3921 0100-104x reponame:Pesquisa Agropecuária Brasileira (Online) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Pesquisa Agropecuária Brasileira (Online) |
collection |
Pesquisa Agropecuária Brasileira (Online) |
repository.name.fl_str_mv |
Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
pab@sct.embrapa.br || sct.pab@embrapa.br |
_version_ |
1793416655283421184 |