Soybean productivity, stability, and adaptability through mixed model methodology.

Detalhes bibliográficos
Autor(a) principal: EVANGELISTA, J. S. P. C.
Data de Publicação: 2021
Outros Autores: ALVES, R. S., PEIXOTO, M. A., RESENDE, M. D. V. de, TEODORO, P. E., SILVA, F. L. da, BHERING, L. L.
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/1129445
https://doi.org/10.1590/0103-8478cr20200406
Resumo: The genotype × environment (G×E) interaction plays an essential role in phenotypic expression and can lead to difficulties in genetic selection. Thus, the present study aimed to estimate genetic parameters and to compare different selection strategies in the context of mixed models for soybean breeding. For this, data referring to the evaluation of 30 genotypes in 10 environments, regarding the grain yield trait, were used. The variance components were estimated through restricted maximum likelihood (REML) and genotypic values were predicted through best linear unbiased prediction (BLUP). Significant effects of genotypes and G×E interaction were detected by the likelihood ratio test (LRT). Low genotypic correlation was obtained across environments, indicating complex G×E interaction. The selective accuracy was very high, indicating high reliability. Our results showed that the most productive soybean genotypes have high adaptability and stability.
id EMBR_55860fdc5a25ea65a0df977a44882103
oai_identifier_str oai:www.alice.cnptia.embrapa.br:doc/1129445
network_acronym_str EMBR
network_name_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository_id_str 2154
spelling Soybean productivity, stability, and adaptability through mixed model methodology.Interação GenéticaMelhoramento Genético VegetalSeleção GenéticaSojaPlant breedingGenotypeGenotype-environment interactionSoybeansThe genotype × environment (G×E) interaction plays an essential role in phenotypic expression and can lead to difficulties in genetic selection. Thus, the present study aimed to estimate genetic parameters and to compare different selection strategies in the context of mixed models for soybean breeding. For this, data referring to the evaluation of 30 genotypes in 10 environments, regarding the grain yield trait, were used. The variance components were estimated through restricted maximum likelihood (REML) and genotypic values were predicted through best linear unbiased prediction (BLUP). Significant effects of genotypes and G×E interaction were detected by the likelihood ratio test (LRT). Low genotypic correlation was obtained across environments, indicating complex G×E interaction. The selective accuracy was very high, indicating high reliability. Our results showed that the most productive soybean genotypes have high adaptability and stability.Título em português: Produtividade, estabilidade e adaptabilidade da soja por meio de metodologia de modelo misto.JENIFFER SANTANA PINTO COELHO EVANGELISTA, UFV; RODRIGO SILVA ALVES, UFV; MARCO ANTÔNIO PEIXOTO, UFV; MARCOS DEON VILELA DE RESENDE, CNPCa; PAULO EDUARDO TEODORO, UFMS; FELIPE LOPES DA SILVA, UFV; LEONARDO LOPES BHERING, UFV.EVANGELISTA, J. S. P. C.ALVES, R. S.PEIXOTO, M. A.RESENDE, M. D. V. deTEODORO, P. E.SILVA, F. L. daBHERING, L. L.2021-01-20T09:04:55Z2021-01-20T09:04:55Z2021-01-192021info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleCiência Rural, v. 51, n. 2, e20200406, 2021.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1129445https://doi.org/10.1590/0103-8478cr20200406enginfo: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:EMBRAPA2021-01-20T09:05:02Zoai:www.alice.cnptia.embrapa.br:doc/1129445Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542021-01-20T09:05:02falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542021-01-20T09:05:02Repositório 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 Soybean productivity, stability, and adaptability through mixed model methodology.
title Soybean productivity, stability, and adaptability through mixed model methodology.
spellingShingle Soybean productivity, stability, and adaptability through mixed model methodology.
EVANGELISTA, J. S. P. C.
Interação Genética
Melhoramento Genético Vegetal
Seleção Genética
Soja
Plant breeding
Genotype
Genotype-environment interaction
Soybeans
title_short Soybean productivity, stability, and adaptability through mixed model methodology.
title_full Soybean productivity, stability, and adaptability through mixed model methodology.
title_fullStr Soybean productivity, stability, and adaptability through mixed model methodology.
title_full_unstemmed Soybean productivity, stability, and adaptability through mixed model methodology.
title_sort Soybean productivity, stability, and adaptability through mixed model methodology.
author EVANGELISTA, J. S. P. C.
author_facet EVANGELISTA, J. S. P. C.
ALVES, R. S.
PEIXOTO, M. A.
RESENDE, M. D. V. de
TEODORO, P. E.
SILVA, F. L. da
BHERING, L. L.
author_role author
author2 ALVES, R. S.
PEIXOTO, M. A.
RESENDE, M. D. V. de
TEODORO, P. E.
SILVA, F. L. da
BHERING, L. L.
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv JENIFFER SANTANA PINTO COELHO EVANGELISTA, UFV; RODRIGO SILVA ALVES, UFV; MARCO ANTÔNIO PEIXOTO, UFV; MARCOS DEON VILELA DE RESENDE, CNPCa; PAULO EDUARDO TEODORO, UFMS; FELIPE LOPES DA SILVA, UFV; LEONARDO LOPES BHERING, UFV.
dc.contributor.author.fl_str_mv EVANGELISTA, J. S. P. C.
ALVES, R. S.
PEIXOTO, M. A.
RESENDE, M. D. V. de
TEODORO, P. E.
SILVA, F. L. da
BHERING, L. L.
dc.subject.por.fl_str_mv Interação Genética
Melhoramento Genético Vegetal
Seleção Genética
Soja
Plant breeding
Genotype
Genotype-environment interaction
Soybeans
topic Interação Genética
Melhoramento Genético Vegetal
Seleção Genética
Soja
Plant breeding
Genotype
Genotype-environment interaction
Soybeans
description The genotype × environment (G×E) interaction plays an essential role in phenotypic expression and can lead to difficulties in genetic selection. Thus, the present study aimed to estimate genetic parameters and to compare different selection strategies in the context of mixed models for soybean breeding. For this, data referring to the evaluation of 30 genotypes in 10 environments, regarding the grain yield trait, were used. The variance components were estimated through restricted maximum likelihood (REML) and genotypic values were predicted through best linear unbiased prediction (BLUP). Significant effects of genotypes and G×E interaction were detected by the likelihood ratio test (LRT). Low genotypic correlation was obtained across environments, indicating complex G×E interaction. The selective accuracy was very high, indicating high reliability. Our results showed that the most productive soybean genotypes have high adaptability and stability.
publishDate 2021
dc.date.none.fl_str_mv 2021-01-20T09:04:55Z
2021-01-20T09:04:55Z
2021-01-19
2021
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 Ciência Rural, v. 51, n. 2, e20200406, 2021.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1129445
https://doi.org/10.1590/0103-8478cr20200406
identifier_str_mv Ciência Rural, v. 51, n. 2, e20200406, 2021.
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1129445
https://doi.org/10.1590/0103-8478cr20200406
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.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
_version_ 1794503501366165504

Registros relacionados