Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach.

Detalhes bibliográficos
Autor(a) principal: MOKRY, F. B.
Data de Publicação: 2013
Outros Autores: HIGA, R. H., MUDADU, M. de A., LIMA, A. O. de, MEIRELLES, S. L. C., SILVA, M. V. G. B., CARDOSO, F. F., OLIVEIRA, M. M. de, URBINATI, I., NICIURA, S. C. M., TULLIO, R. R., ALENCAR, M. M. de, REGITANO, L. C. de A.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/959968
Resumo: Meat quality involves many traits, such as marbling, tenderness, juiciness, and backfat thickness, all of which require attention from livestock producers. Backfat thickness improvement by means of traditional selection techniques in Canchim beef cattle has been challenging due to its low heritability, and it is measured late in an animal?s life. Therefore, the implementation of new methodologies for identification of single nucleotide polymorphisms (SNPs) linked to backfat thickness are an important strategy for genetic improvement of carcass and meat quality.
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spelling Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach.Machine learningTropical composition cattleBovinolipid metabolismsubcutaneous fatMeat quality involves many traits, such as marbling, tenderness, juiciness, and backfat thickness, all of which require attention from livestock producers. Backfat thickness improvement by means of traditional selection techniques in Canchim beef cattle has been challenging due to its low heritability, and it is measured late in an animal?s life. Therefore, the implementation of new methodologies for identification of single nucleotide polymorphisms (SNPs) linked to backfat thickness are an important strategy for genetic improvement of carcass and meat quality.FABIANA BARICHELLO MOKRY, UFSCAR; ROBERTO HIROSHI HIGA, CNPTIA; MAURICIO DE ALVARENGA MUDADU, CPPSE; ANDRESSA OLIVEIRA DE LIMA, UFSCAR; SARAH LAGUNA CONCEIÇÃO MEIRELLES, UFLA; MARCOS VINICIUS GUALBERTO B SILVA, CNPGL; FERNANDO FLORES CARDOSO, CPPSUL; MAURÍCIO MORGADO DE OLIVEIRA, Embrapa Southern Region Animal Husbandry; ISMAEL URBINATI, USP; SIMONE CRISTINA MEO NICIURA, CPPSE; RYMER RAMIZ TULLIO, CPPSE; MAURICIO MELLO DE ALENCAR, CPPSE; LUCIANA CORREIA DE ALMEIDA REGITANO, CPPSE.MOKRY, F. B.HIGA, R. H.MUDADU, M. de A.LIMA, A. O. deMEIRELLES, S. L. C.SILVA, M. V. G. B.CARDOSO, F. F.OLIVEIRA, M. M. deURBINATI, I.NICIURA, S. C. M.TULLIO, R. R.ALENCAR, M. M. deREGITANO, L. C. de A.2023-04-11T14:24:30Z2023-04-11T14:24:30Z2013-06-142013info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article11 p.BMC Genetics, London v. 14, n. 47, 2013.http://www.alice.cnptia.embrapa.br/alice/handle/doc/959968enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2023-04-11T14:24:30Zoai:www.alice.cnptia.embrapa.br:doc/959968Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542023-04-11T14:24:30falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542023-04-11T14:24:30Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach.
title Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach.
spellingShingle Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach.
MOKRY, F. B.
Machine learning
Tropical composition cattle
Bovino
lipid metabolism
subcutaneous fat
title_short Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach.
title_full Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach.
title_fullStr Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach.
title_full_unstemmed Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach.
title_sort Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach.
author MOKRY, F. B.
author_facet MOKRY, F. B.
HIGA, R. H.
MUDADU, M. de A.
LIMA, A. O. de
MEIRELLES, S. L. C.
SILVA, M. V. G. B.
CARDOSO, F. F.
OLIVEIRA, M. M. de
URBINATI, I.
NICIURA, S. C. M.
TULLIO, R. R.
ALENCAR, M. M. de
REGITANO, L. C. de A.
author_role author
author2 HIGA, R. H.
MUDADU, M. de A.
LIMA, A. O. de
MEIRELLES, S. L. C.
SILVA, M. V. G. B.
CARDOSO, F. F.
OLIVEIRA, M. M. de
URBINATI, I.
NICIURA, S. C. M.
TULLIO, R. R.
ALENCAR, M. M. de
REGITANO, L. C. de A.
author2_role author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv FABIANA BARICHELLO MOKRY, UFSCAR; ROBERTO HIROSHI HIGA, CNPTIA; MAURICIO DE ALVARENGA MUDADU, CPPSE; ANDRESSA OLIVEIRA DE LIMA, UFSCAR; SARAH LAGUNA CONCEIÇÃO MEIRELLES, UFLA; MARCOS VINICIUS GUALBERTO B SILVA, CNPGL; FERNANDO FLORES CARDOSO, CPPSUL; MAURÍCIO MORGADO DE OLIVEIRA, Embrapa Southern Region Animal Husbandry; ISMAEL URBINATI, USP; SIMONE CRISTINA MEO NICIURA, CPPSE; RYMER RAMIZ TULLIO, CPPSE; MAURICIO MELLO DE ALENCAR, CPPSE; LUCIANA CORREIA DE ALMEIDA REGITANO, CPPSE.
dc.contributor.author.fl_str_mv MOKRY, F. B.
HIGA, R. H.
MUDADU, M. de A.
LIMA, A. O. de
MEIRELLES, S. L. C.
SILVA, M. V. G. B.
CARDOSO, F. F.
OLIVEIRA, M. M. de
URBINATI, I.
NICIURA, S. C. M.
TULLIO, R. R.
ALENCAR, M. M. de
REGITANO, L. C. de A.
dc.subject.por.fl_str_mv Machine learning
Tropical composition cattle
Bovino
lipid metabolism
subcutaneous fat
topic Machine learning
Tropical composition cattle
Bovino
lipid metabolism
subcutaneous fat
description Meat quality involves many traits, such as marbling, tenderness, juiciness, and backfat thickness, all of which require attention from livestock producers. Backfat thickness improvement by means of traditional selection techniques in Canchim beef cattle has been challenging due to its low heritability, and it is measured late in an animal?s life. Therefore, the implementation of new methodologies for identification of single nucleotide polymorphisms (SNPs) linked to backfat thickness are an important strategy for genetic improvement of carcass and meat quality.
publishDate 2013
dc.date.none.fl_str_mv 2013-06-14
2013
2023-04-11T14:24:30Z
2023-04-11T14:24:30Z
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv BMC Genetics, London v. 14, n. 47, 2013.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/959968
identifier_str_mv BMC Genetics, London v. 14, n. 47, 2013.
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/959968
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 11 p.
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
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