Estimation of segregation variance for birth weight in beef cattle

Autores
Birchmeier, A.N.; Cantet, Rodolfo Juan Carlos; Fernando, R.L.; Morris, C.A.; Holgado, F.; Jara, A.; Santos Cristal, M.
Año de publicación
2002
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Genetic evaluation using multibreed covariance theory requires estimating the segregation variance. The segregation variance is the amount by which the additive variance in the F2 exceeds that in F1. The goal of this research was to obtain REML estimates of the additive variances plus segregation variance, assuming equal environmental variances for all genetic groups. The data were originated in two experimental herds of beef cattle from New Zealand (NZ) and Argentina (AR). Records were birth weights of 4082 Angus-Hereford (NZ) and 6963 Nellore-Hereford (AR) cross calves, including purebreds, F1, backcrosses, F2, and advanced generations (F3, F4, F5). Variance components were estimated using an additive animal model by REML, with a first-derivative algorithm. The asymptotic standard errors of the REML estimates were calculated using the inverse of the information matrix. After 400 iterations, estimates of the additive variances (in kg2) were 7.77±0.91 (Angus) and 10.02±1.11 (Hereford), and estimate of the segregation variance was 1.14±0.85, in NZ data. Whereas in AR data, estimates of the additive variances were 6.59±0.71 (Nellore) and 8.97±0.75 (Hereford), and estimate of the segregation variance was 1.48±0.74. The error variances were estimated to be 7.92±0.06 in NZ and 6.86±0.06 in AR. Asymptotic tests (Likelihood Ratio and Lagrange Multiplier) of the hypothesis of null segregation variance suggested that this was not the case in these data.
Fil: Birchmeier, A.N.. Universidad de Buenos Aires; Argentina
Fil: Cantet, Rodolfo Juan Carlos. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Fernando, R.L.. IOWA STATE UNIVERSITY (ISU);
Fil: Morris, C.A.. Agresearch Ruakura Research Centre; Nueva Zelanda
Fil: Holgado, F.. Instituto Nacional de Tecnología Agropecuaria; Argentina
Fil: Jara, A.. Universidad de Chile; Chile
Fil: Santos Cristal, M.. Universidad de Buenos Aires; Argentina
Materia
BEEF CATTLE
COMPOSITE POPULATION
REML
SEGREGATION VARIANCE
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/149772

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network_name_str CONICET Digital (CONICET)
spelling Estimation of segregation variance for birth weight in beef cattleBirchmeier, A.N.Cantet, Rodolfo Juan CarlosFernando, R.L.Morris, C.A.Holgado, F.Jara, A.Santos Cristal, M.BEEF CATTLECOMPOSITE POPULATIONREMLSEGREGATION VARIANCEhttps://purl.org/becyt/ford/4.3https://purl.org/becyt/ford/4Genetic evaluation using multibreed covariance theory requires estimating the segregation variance. The segregation variance is the amount by which the additive variance in the F2 exceeds that in F1. The goal of this research was to obtain REML estimates of the additive variances plus segregation variance, assuming equal environmental variances for all genetic groups. The data were originated in two experimental herds of beef cattle from New Zealand (NZ) and Argentina (AR). Records were birth weights of 4082 Angus-Hereford (NZ) and 6963 Nellore-Hereford (AR) cross calves, including purebreds, F1, backcrosses, F2, and advanced generations (F3, F4, F5). Variance components were estimated using an additive animal model by REML, with a first-derivative algorithm. The asymptotic standard errors of the REML estimates were calculated using the inverse of the information matrix. After 400 iterations, estimates of the additive variances (in kg2) were 7.77±0.91 (Angus) and 10.02±1.11 (Hereford), and estimate of the segregation variance was 1.14±0.85, in NZ data. Whereas in AR data, estimates of the additive variances were 6.59±0.71 (Nellore) and 8.97±0.75 (Hereford), and estimate of the segregation variance was 1.48±0.74. The error variances were estimated to be 7.92±0.06 in NZ and 6.86±0.06 in AR. Asymptotic tests (Likelihood Ratio and Lagrange Multiplier) of the hypothesis of null segregation variance suggested that this was not the case in these data.Fil: Birchmeier, A.N.. Universidad de Buenos Aires; ArgentinaFil: Cantet, Rodolfo Juan Carlos. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Fernando, R.L.. IOWA STATE UNIVERSITY (ISU);Fil: Morris, C.A.. Agresearch Ruakura Research Centre; Nueva ZelandaFil: Holgado, F.. Instituto Nacional de Tecnología Agropecuaria; ArgentinaFil: Jara, A.. Universidad de Chile; ChileFil: Santos Cristal, M.. Universidad de Buenos Aires; ArgentinaElsevier2002-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/149772Birchmeier, A.N.; Cantet, Rodolfo Juan Carlos; Fernando, R.L.; Morris, C.A.; Holgado, F.; et al.; Estimation of segregation variance for birth weight in beef cattle; Elsevier; Livestock Production Science; 76; 1-2; 8-2002; 27-350301-6226CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0301622602000131info:eu-repo/semantics/altIdentifier/doi/10.1016/S0301-6226(02)00013-1info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:35:56Zoai:ri.conicet.gov.ar:11336/149772instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:35:57.068CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Estimation of segregation variance for birth weight in beef cattle
title Estimation of segregation variance for birth weight in beef cattle
spellingShingle Estimation of segregation variance for birth weight in beef cattle
Birchmeier, A.N.
BEEF CATTLE
COMPOSITE POPULATION
REML
SEGREGATION VARIANCE
title_short Estimation of segregation variance for birth weight in beef cattle
title_full Estimation of segregation variance for birth weight in beef cattle
title_fullStr Estimation of segregation variance for birth weight in beef cattle
title_full_unstemmed Estimation of segregation variance for birth weight in beef cattle
title_sort Estimation of segregation variance for birth weight in beef cattle
dc.creator.none.fl_str_mv Birchmeier, A.N.
Cantet, Rodolfo Juan Carlos
Fernando, R.L.
Morris, C.A.
Holgado, F.
Jara, A.
Santos Cristal, M.
author Birchmeier, A.N.
author_facet Birchmeier, A.N.
Cantet, Rodolfo Juan Carlos
Fernando, R.L.
Morris, C.A.
Holgado, F.
Jara, A.
Santos Cristal, M.
author_role author
author2 Cantet, Rodolfo Juan Carlos
Fernando, R.L.
Morris, C.A.
Holgado, F.
Jara, A.
Santos Cristal, M.
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv BEEF CATTLE
COMPOSITE POPULATION
REML
SEGREGATION VARIANCE
topic BEEF CATTLE
COMPOSITE POPULATION
REML
SEGREGATION VARIANCE
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.3
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv Genetic evaluation using multibreed covariance theory requires estimating the segregation variance. The segregation variance is the amount by which the additive variance in the F2 exceeds that in F1. The goal of this research was to obtain REML estimates of the additive variances plus segregation variance, assuming equal environmental variances for all genetic groups. The data were originated in two experimental herds of beef cattle from New Zealand (NZ) and Argentina (AR). Records were birth weights of 4082 Angus-Hereford (NZ) and 6963 Nellore-Hereford (AR) cross calves, including purebreds, F1, backcrosses, F2, and advanced generations (F3, F4, F5). Variance components were estimated using an additive animal model by REML, with a first-derivative algorithm. The asymptotic standard errors of the REML estimates were calculated using the inverse of the information matrix. After 400 iterations, estimates of the additive variances (in kg2) were 7.77±0.91 (Angus) and 10.02±1.11 (Hereford), and estimate of the segregation variance was 1.14±0.85, in NZ data. Whereas in AR data, estimates of the additive variances were 6.59±0.71 (Nellore) and 8.97±0.75 (Hereford), and estimate of the segregation variance was 1.48±0.74. The error variances were estimated to be 7.92±0.06 in NZ and 6.86±0.06 in AR. Asymptotic tests (Likelihood Ratio and Lagrange Multiplier) of the hypothesis of null segregation variance suggested that this was not the case in these data.
Fil: Birchmeier, A.N.. Universidad de Buenos Aires; Argentina
Fil: Cantet, Rodolfo Juan Carlos. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Fernando, R.L.. IOWA STATE UNIVERSITY (ISU);
Fil: Morris, C.A.. Agresearch Ruakura Research Centre; Nueva Zelanda
Fil: Holgado, F.. Instituto Nacional de Tecnología Agropecuaria; Argentina
Fil: Jara, A.. Universidad de Chile; Chile
Fil: Santos Cristal, M.. Universidad de Buenos Aires; Argentina
description Genetic evaluation using multibreed covariance theory requires estimating the segregation variance. The segregation variance is the amount by which the additive variance in the F2 exceeds that in F1. The goal of this research was to obtain REML estimates of the additive variances plus segregation variance, assuming equal environmental variances for all genetic groups. The data were originated in two experimental herds of beef cattle from New Zealand (NZ) and Argentina (AR). Records were birth weights of 4082 Angus-Hereford (NZ) and 6963 Nellore-Hereford (AR) cross calves, including purebreds, F1, backcrosses, F2, and advanced generations (F3, F4, F5). Variance components were estimated using an additive animal model by REML, with a first-derivative algorithm. The asymptotic standard errors of the REML estimates were calculated using the inverse of the information matrix. After 400 iterations, estimates of the additive variances (in kg2) were 7.77±0.91 (Angus) and 10.02±1.11 (Hereford), and estimate of the segregation variance was 1.14±0.85, in NZ data. Whereas in AR data, estimates of the additive variances were 6.59±0.71 (Nellore) and 8.97±0.75 (Hereford), and estimate of the segregation variance was 1.48±0.74. The error variances were estimated to be 7.92±0.06 in NZ and 6.86±0.06 in AR. Asymptotic tests (Likelihood Ratio and Lagrange Multiplier) of the hypothesis of null segregation variance suggested that this was not the case in these data.
publishDate 2002
dc.date.none.fl_str_mv 2002-08
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/149772
Birchmeier, A.N.; Cantet, Rodolfo Juan Carlos; Fernando, R.L.; Morris, C.A.; Holgado, F.; et al.; Estimation of segregation variance for birth weight in beef cattle; Elsevier; Livestock Production Science; 76; 1-2; 8-2002; 27-35
0301-6226
CONICET Digital
CONICET
url http://hdl.handle.net/11336/149772
identifier_str_mv Birchmeier, A.N.; Cantet, Rodolfo Juan Carlos; Fernando, R.L.; Morris, C.A.; Holgado, F.; et al.; Estimation of segregation variance for birth weight in beef cattle; Elsevier; Livestock Production Science; 76; 1-2; 8-2002; 27-35
0301-6226
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0301622602000131
info:eu-repo/semantics/altIdentifier/doi/10.1016/S0301-6226(02)00013-1
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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