Random regression models to estimate genetic parameters for fat and milk yield considering different residual variance structure
Autor(a) principal: | |
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Data de Publicação: | 2010 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/227831 |
Resumo: | Random regression models are an alternatively to adjust milk and fat yield test-day records along lactation curve. A total of 7,908 test-day records from 1,463 first lactation buffaloes were analyzed. The model included the additive genetic, permanent environmental and residual as random effects. As fixed effects the contemporary groups (herd, year-month of records), the linear and quadratic effect of age of cow at calving and the fixed curve of the population were considered. Residual variances were modeled trough a step function with 1, 4, 6 and 10 classes. Random effects were modeled through Legendre polynomials from third to sixth order. Residual variances were modeled with a step function with 4 classes. The models adjusting Legendre polynomials of fourth order for the additive genetic and permanent environmental (LEG4,4_4) and fourth and third order for the additive genetic and permanent environmental (LEG4,3_4), respectively, were the most adequate to described the trajectory of milk and fat yield, respectively. Milk yield heritability estimates obtained with LEG4,4_4 varied from 0.18 (first month) to 0.28 (10th month). Fat yield heritability estimates obtained with LEG4,3_4 varied from 0.20 (2nd month) to 0.27 (10th month). The residual variances for fat and milk yield should be modeled through heterogeneous classes, being four classes of residual variances the most adequate. |
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Random regression models to estimate genetic parameters for fat and milk yield considering different residual variance structureGenetic parametersHeritabilityLegendre polynomialsRandom regression models are an alternatively to adjust milk and fat yield test-day records along lactation curve. A total of 7,908 test-day records from 1,463 first lactation buffaloes were analyzed. The model included the additive genetic, permanent environmental and residual as random effects. As fixed effects the contemporary groups (herd, year-month of records), the linear and quadratic effect of age of cow at calving and the fixed curve of the population were considered. Residual variances were modeled trough a step function with 1, 4, 6 and 10 classes. Random effects were modeled through Legendre polynomials from third to sixth order. Residual variances were modeled with a step function with 4 classes. The models adjusting Legendre polynomials of fourth order for the additive genetic and permanent environmental (LEG4,4_4) and fourth and third order for the additive genetic and permanent environmental (LEG4,3_4), respectively, were the most adequate to described the trajectory of milk and fat yield, respectively. Milk yield heritability estimates obtained with LEG4,4_4 varied from 0.18 (first month) to 0.28 (10th month). Fat yield heritability estimates obtained with LEG4,3_4 varied from 0.20 (2nd month) to 0.27 (10th month). The residual variances for fat and milk yield should be modeled through heterogeneous classes, being four classes of residual variances the most adequate.University of São Paulo State-Jabotical, FCAV/UNESP, Department of Animal Sciences, São Paulo StateUniversity of São Paulo State-Jabotical, FCAV/UNESP, Department of Animal Sciences, São Paulo StateUniversidade Estadual Paulista (UNESP)Aspilcueta Borquis, R. [UNESP]Baldi, F. [UNESP]Albuqueruqe, L. G. [UNESP]Tonhati, H. [UNESP]2022-04-29T07:20:23Z2022-04-29T07:20:23Z2010-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article420-422Revista Veterinaria, v. 21, n. SUPPL.1, p. 420-422, 2010.1669-68401668-4834http://hdl.handle.net/11449/2278312-s2.0-84904757676Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengRevista Veterinariainfo:eu-repo/semantics/openAccess2022-04-29T07:20:23Zoai:repositorio.unesp.br:11449/227831Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462022-04-29T07:20:23Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Random regression models to estimate genetic parameters for fat and milk yield considering different residual variance structure |
title |
Random regression models to estimate genetic parameters for fat and milk yield considering different residual variance structure |
spellingShingle |
Random regression models to estimate genetic parameters for fat and milk yield considering different residual variance structure Aspilcueta Borquis, R. [UNESP] Genetic parameters Heritability Legendre polynomials |
title_short |
Random regression models to estimate genetic parameters for fat and milk yield considering different residual variance structure |
title_full |
Random regression models to estimate genetic parameters for fat and milk yield considering different residual variance structure |
title_fullStr |
Random regression models to estimate genetic parameters for fat and milk yield considering different residual variance structure |
title_full_unstemmed |
Random regression models to estimate genetic parameters for fat and milk yield considering different residual variance structure |
title_sort |
Random regression models to estimate genetic parameters for fat and milk yield considering different residual variance structure |
author |
Aspilcueta Borquis, R. [UNESP] |
author_facet |
Aspilcueta Borquis, R. [UNESP] Baldi, F. [UNESP] Albuqueruqe, L. G. [UNESP] Tonhati, H. [UNESP] |
author_role |
author |
author2 |
Baldi, F. [UNESP] Albuqueruqe, L. G. [UNESP] Tonhati, H. [UNESP] |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Aspilcueta Borquis, R. [UNESP] Baldi, F. [UNESP] Albuqueruqe, L. G. [UNESP] Tonhati, H. [UNESP] |
dc.subject.por.fl_str_mv |
Genetic parameters Heritability Legendre polynomials |
topic |
Genetic parameters Heritability Legendre polynomials |
description |
Random regression models are an alternatively to adjust milk and fat yield test-day records along lactation curve. A total of 7,908 test-day records from 1,463 first lactation buffaloes were analyzed. The model included the additive genetic, permanent environmental and residual as random effects. As fixed effects the contemporary groups (herd, year-month of records), the linear and quadratic effect of age of cow at calving and the fixed curve of the population were considered. Residual variances were modeled trough a step function with 1, 4, 6 and 10 classes. Random effects were modeled through Legendre polynomials from third to sixth order. Residual variances were modeled with a step function with 4 classes. The models adjusting Legendre polynomials of fourth order for the additive genetic and permanent environmental (LEG4,4_4) and fourth and third order for the additive genetic and permanent environmental (LEG4,3_4), respectively, were the most adequate to described the trajectory of milk and fat yield, respectively. Milk yield heritability estimates obtained with LEG4,4_4 varied from 0.18 (first month) to 0.28 (10th month). Fat yield heritability estimates obtained with LEG4,3_4 varied from 0.20 (2nd month) to 0.27 (10th month). The residual variances for fat and milk yield should be modeled through heterogeneous classes, being four classes of residual variances the most adequate. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010-01-01 2022-04-29T07:20:23Z 2022-04-29T07:20:23Z |
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 |
Revista Veterinaria, v. 21, n. SUPPL.1, p. 420-422, 2010. 1669-6840 1668-4834 http://hdl.handle.net/11449/227831 2-s2.0-84904757676 |
identifier_str_mv |
Revista Veterinaria, v. 21, n. SUPPL.1, p. 420-422, 2010. 1669-6840 1668-4834 2-s2.0-84904757676 |
url |
http://hdl.handle.net/11449/227831 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Revista Veterinaria |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
420-422 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1797789736542142464 |