Bayesian random regression threshold models for genetic evaluation of pregnancy probability in Red Sindhi heifers

Detalhes bibliográficos
Autor(a) principal: Silva, Fabyano Fonseca e
Data de Publicação: 2017
Outros Autores: Oliveira, Hinayah Rojas de, Viana, José Marcelo Soriano, Oliveira, Lorena Tavares de, Bonafé, Cristina Moreira, Ventura, Henrique Torres, Menezes, Gilberto Romeiro de Oliveira, Resende, Marcos Deon Vilela de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: LOCUS Repositório Institucional da UFV
Texto Completo: https://doi.org/10.1016/j.livsci.2017.06.005
http://www.locus.ufv.br/handle/123456789/21706
Resumo: We proposed a Bayesian random regression threshold model for genetic evaluation of pregnancy probability (PP) in Red Sindhi heifers over different months. Since this breed was recently introduced in Brazil, the age of 14 months usually preconized for Nellore cattle may not reflect the reality of the fertility indicator. In this context, the pregnancy success was evaluated at other ages aiming to understand its genetic variability pattern over time. A total of 4828 phenotyped heifers belong to 657 contemporary groups were used for the analysis. The estimated connectedness was equal to 99.75% considering 6189 individuals in the final pedigree. The random regression threshold models were implemented by combining second, third and fourth order Legendre polynomials to describe the average, the additive genetic and the permanent environmental curves. Additionally, the heterogeneity of the residual variance was also tested here. Based on DIC (deviance information criterion) and posterior model probabilities, the fourth order Legendre polynomials (LEG_4441) for the average, the additive genetic and the permanent environmental effects, assuming homogeneity of the residual variance, outperformed the simplest models. Thus, the fitting quality compensated the increased in the model complexity. The negative genetic correlations between PP at 15 months with PP at latter months indicates that rankings of animals for selection would be few similar in advanced ages. The high values for heritability (varying from 0.32 to 0.45) suggest that PP, mainly until 19 months, can be used as selection criterion for reproductive female performance in breeding programs for Red Sindhi cattle in Brazil. These practical results were only obtained due to the advantages of the proposed random regression threshold models to describe PP over different months.
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spelling Silva, Fabyano Fonseca eOliveira, Hinayah Rojas deViana, José Marcelo SorianoOliveira, Lorena Tavares deBonafé, Cristina MoreiraVentura, Henrique TorresMenezes, Gilberto Romeiro de OliveiraResende, Marcos Deon Vilela de2018-09-09T22:35:21Z2018-09-09T22:35:21Z2017-06-151871-1413https://doi.org/10.1016/j.livsci.2017.06.005http://www.locus.ufv.br/handle/123456789/21706We proposed a Bayesian random regression threshold model for genetic evaluation of pregnancy probability (PP) in Red Sindhi heifers over different months. Since this breed was recently introduced in Brazil, the age of 14 months usually preconized for Nellore cattle may not reflect the reality of the fertility indicator. In this context, the pregnancy success was evaluated at other ages aiming to understand its genetic variability pattern over time. A total of 4828 phenotyped heifers belong to 657 contemporary groups were used for the analysis. The estimated connectedness was equal to 99.75% considering 6189 individuals in the final pedigree. The random regression threshold models were implemented by combining second, third and fourth order Legendre polynomials to describe the average, the additive genetic and the permanent environmental curves. Additionally, the heterogeneity of the residual variance was also tested here. Based on DIC (deviance information criterion) and posterior model probabilities, the fourth order Legendre polynomials (LEG_4441) for the average, the additive genetic and the permanent environmental effects, assuming homogeneity of the residual variance, outperformed the simplest models. Thus, the fitting quality compensated the increased in the model complexity. The negative genetic correlations between PP at 15 months with PP at latter months indicates that rankings of animals for selection would be few similar in advanced ages. The high values for heritability (varying from 0.32 to 0.45) suggest that PP, mainly until 19 months, can be used as selection criterion for reproductive female performance in breeding programs for Red Sindhi cattle in Brazil. These practical results were only obtained due to the advantages of the proposed random regression threshold models to describe PP over different months.engLivestock ScienceVolume 202, Pages 166-170, August 2017Elsevier B.V.info:eu-repo/semantics/openAccessBos indicusHeifer pregnancyLegendre polynomialsBayesian random regression threshold models for genetic evaluation of pregnancy probability in Red Sindhi heifersinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALartigo.pdfartigo.pdfTexto completoapplication/pdf359152https://locus.ufv.br//bitstream/123456789/21706/1/artigo.pdffd43ca86cd46a1a702095828f696f4d0MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://locus.ufv.br//bitstream/123456789/21706/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52THUMBNAILartigo.pdf.jpgartigo.pdf.jpgIM Thumbnailimage/jpeg5848https://locus.ufv.br//bitstream/123456789/21706/3/artigo.pdf.jpg4f902780848811cf56ac7d51c8fd14f8MD53123456789/217062018-09-09 23:00:41.926oai:locus.ufv.br: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Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452018-09-10T02:00:41LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false
dc.title.en.fl_str_mv Bayesian random regression threshold models for genetic evaluation of pregnancy probability in Red Sindhi heifers
title Bayesian random regression threshold models for genetic evaluation of pregnancy probability in Red Sindhi heifers
spellingShingle Bayesian random regression threshold models for genetic evaluation of pregnancy probability in Red Sindhi heifers
Silva, Fabyano Fonseca e
Bos indicus
Heifer pregnancy
Legendre polynomials
title_short Bayesian random regression threshold models for genetic evaluation of pregnancy probability in Red Sindhi heifers
title_full Bayesian random regression threshold models for genetic evaluation of pregnancy probability in Red Sindhi heifers
title_fullStr Bayesian random regression threshold models for genetic evaluation of pregnancy probability in Red Sindhi heifers
title_full_unstemmed Bayesian random regression threshold models for genetic evaluation of pregnancy probability in Red Sindhi heifers
title_sort Bayesian random regression threshold models for genetic evaluation of pregnancy probability in Red Sindhi heifers
author Silva, Fabyano Fonseca e
author_facet Silva, Fabyano Fonseca e
Oliveira, Hinayah Rojas de
Viana, José Marcelo Soriano
Oliveira, Lorena Tavares de
Bonafé, Cristina Moreira
Ventura, Henrique Torres
Menezes, Gilberto Romeiro de Oliveira
Resende, Marcos Deon Vilela de
author_role author
author2 Oliveira, Hinayah Rojas de
Viana, José Marcelo Soriano
Oliveira, Lorena Tavares de
Bonafé, Cristina Moreira
Ventura, Henrique Torres
Menezes, Gilberto Romeiro de Oliveira
Resende, Marcos Deon Vilela de
author2_role author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Silva, Fabyano Fonseca e
Oliveira, Hinayah Rojas de
Viana, José Marcelo Soriano
Oliveira, Lorena Tavares de
Bonafé, Cristina Moreira
Ventura, Henrique Torres
Menezes, Gilberto Romeiro de Oliveira
Resende, Marcos Deon Vilela de
dc.subject.pt-BR.fl_str_mv Bos indicus
Heifer pregnancy
Legendre polynomials
topic Bos indicus
Heifer pregnancy
Legendre polynomials
description We proposed a Bayesian random regression threshold model for genetic evaluation of pregnancy probability (PP) in Red Sindhi heifers over different months. Since this breed was recently introduced in Brazil, the age of 14 months usually preconized for Nellore cattle may not reflect the reality of the fertility indicator. In this context, the pregnancy success was evaluated at other ages aiming to understand its genetic variability pattern over time. A total of 4828 phenotyped heifers belong to 657 contemporary groups were used for the analysis. The estimated connectedness was equal to 99.75% considering 6189 individuals in the final pedigree. The random regression threshold models were implemented by combining second, third and fourth order Legendre polynomials to describe the average, the additive genetic and the permanent environmental curves. Additionally, the heterogeneity of the residual variance was also tested here. Based on DIC (deviance information criterion) and posterior model probabilities, the fourth order Legendre polynomials (LEG_4441) for the average, the additive genetic and the permanent environmental effects, assuming homogeneity of the residual variance, outperformed the simplest models. Thus, the fitting quality compensated the increased in the model complexity. The negative genetic correlations between PP at 15 months with PP at latter months indicates that rankings of animals for selection would be few similar in advanced ages. The high values for heritability (varying from 0.32 to 0.45) suggest that PP, mainly until 19 months, can be used as selection criterion for reproductive female performance in breeding programs for Red Sindhi cattle in Brazil. These practical results were only obtained due to the advantages of the proposed random regression threshold models to describe PP over different months.
publishDate 2017
dc.date.issued.fl_str_mv 2017-06-15
dc.date.accessioned.fl_str_mv 2018-09-09T22:35:21Z
dc.date.available.fl_str_mv 2018-09-09T22:35:21Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv https://doi.org/10.1016/j.livsci.2017.06.005
http://www.locus.ufv.br/handle/123456789/21706
dc.identifier.issn.none.fl_str_mv 1871-1413
identifier_str_mv 1871-1413
url https://doi.org/10.1016/j.livsci.2017.06.005
http://www.locus.ufv.br/handle/123456789/21706
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartofseries.pt-BR.fl_str_mv Volume 202, Pages 166-170, August 2017
dc.rights.driver.fl_str_mv Elsevier B.V.
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