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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/149772
Ver los metadatos del registro completo
id |
CONICETDig_4b5a0519bf88e25b6441c17d97305b9d |
---|---|
oai_identifier_str |
oai:ri.conicet.gov.ar:11336/149772 |
network_acronym_str |
CONICETDig |
repository_id_str |
3498 |
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 |
_version_ |
1844613123774873600 |
score |
13.070432 |