Evaluation of genotype x environment interactions in cotton using the method proposed by Eberhart and Russell and reaction norm models.

Detalhes bibliográficos
Autor(a) principal: ALVES, R. S.
Data de Publicação: 2017
Outros Autores: TEODORO, P. E., FARIAS, F. C., FARIAS, F. J. C., CARVALHO, L. P. de, RODRIGUES, J. I. S., BHERING, L. L., RESENDE, M. D. V. de
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/1083385
Resumo: Cotton produces one of the most important textile fibers of the world and has great relevance in the world economy. It is an economically important crop in Brazil, which is the world?s fifth largest producer. However, studies evaluating the genotype x environment (G x E) interactions in cotton are scarce in this country. Therefore, the goal of this study was to evaluate the G x E interactions in two important traits in cotton (fiber yield and fiber length) using the method proposed by Eberhart and Russell (simple linear regression) and reaction norm models (random regression). Eight trials with sixteen upland cotton genotypes, conducted in a randomized block design, were used. It was possible to identify a genotype with wide adaptability and stability for both traits. Reaction norm models have excellent theoretical and practical properties and led to more informative and accurate results than the method proposed by Eberhart and Russell and should, therefore, be preferred. Curves of genotypic values as a function of the environmental gradient, which predict the behavior of the genotypes along the environmental gradient, were generated. These curves make possible the recommendation to untested environmental levels.
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spelling Evaluation of genotype x environment interactions in cotton using the method proposed by Eberhart and Russell and reaction norm models.Genetic selectionStability and adaptabilityMixed model methodologyRandom regressionGossypium hirsutumSeleção genéticaNatural selectionCotton produces one of the most important textile fibers of the world and has great relevance in the world economy. It is an economically important crop in Brazil, which is the world?s fifth largest producer. However, studies evaluating the genotype x environment (G x E) interactions in cotton are scarce in this country. Therefore, the goal of this study was to evaluate the G x E interactions in two important traits in cotton (fiber yield and fiber length) using the method proposed by Eberhart and Russell (simple linear regression) and reaction norm models (random regression). Eight trials with sixteen upland cotton genotypes, conducted in a randomized block design, were used. It was possible to identify a genotype with wide adaptability and stability for both traits. Reaction norm models have excellent theoretical and practical properties and led to more informative and accurate results than the method proposed by Eberhart and Russell and should, therefore, be preferred. Curves of genotypic values as a function of the environmental gradient, which predict the behavior of the genotypes along the environmental gradient, were generated. These curves make possible the recommendation to untested environmental levels.R. S. Alves, UFV; P. E. Teodoro, UFV; F. C. Farias, Universidade Federal de Goiás; FRANCISCO JOSE CORREIA FARIAS, CNPA; LUIZ PAULO DE CARVALHO, CNPA; J. I. S. Rodrigues; L. L. Bhering, UFV; MARCOS DEON VILELA DE RESENDE, CNPF.ALVES, R. S.TEODORO, P. E.FARIAS, F. C.FARIAS, F. J. C.CARVALHO, L. P. deRODRIGUES, J. I. S.BHERING, L. L.RESENDE, M. D. V. de2017-12-23T23:29:58Z2017-12-23T23:29:58Z2017-12-2220172017-12-23T23:29:58Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article12 p.Genetics and Molecular Research, v. 16, n. 3, gmr16039726, 2017.http://www.alice.cnptia.embrapa.br/alice/handle/doc/108338510.4238/gmr16039726enginfo: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:EMBRAPA2017-12-23T23:30:05Zoai:www.alice.cnptia.embrapa.br:doc/1083385Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542017-12-23T23:30:05falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542017-12-23T23:30:05Repositório 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 Evaluation of genotype x environment interactions in cotton using the method proposed by Eberhart and Russell and reaction norm models.
title Evaluation of genotype x environment interactions in cotton using the method proposed by Eberhart and Russell and reaction norm models.
spellingShingle Evaluation of genotype x environment interactions in cotton using the method proposed by Eberhart and Russell and reaction norm models.
ALVES, R. S.
Genetic selection
Stability and adaptability
Mixed model methodology
Random regression
Gossypium hirsutum
Seleção genética
Natural selection
title_short Evaluation of genotype x environment interactions in cotton using the method proposed by Eberhart and Russell and reaction norm models.
title_full Evaluation of genotype x environment interactions in cotton using the method proposed by Eberhart and Russell and reaction norm models.
title_fullStr Evaluation of genotype x environment interactions in cotton using the method proposed by Eberhart and Russell and reaction norm models.
title_full_unstemmed Evaluation of genotype x environment interactions in cotton using the method proposed by Eberhart and Russell and reaction norm models.
title_sort Evaluation of genotype x environment interactions in cotton using the method proposed by Eberhart and Russell and reaction norm models.
author ALVES, R. S.
author_facet ALVES, R. S.
TEODORO, P. E.
FARIAS, F. C.
FARIAS, F. J. C.
CARVALHO, L. P. de
RODRIGUES, J. I. S.
BHERING, L. L.
RESENDE, M. D. V. de
author_role author
author2 TEODORO, P. E.
FARIAS, F. C.
FARIAS, F. J. C.
CARVALHO, L. P. de
RODRIGUES, J. I. S.
BHERING, L. L.
RESENDE, M. D. V. de
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv R. S. Alves, UFV; P. E. Teodoro, UFV; F. C. Farias, Universidade Federal de Goiás; FRANCISCO JOSE CORREIA FARIAS, CNPA; LUIZ PAULO DE CARVALHO, CNPA; J. I. S. Rodrigues; L. L. Bhering, UFV; MARCOS DEON VILELA DE RESENDE, CNPF.
dc.contributor.author.fl_str_mv ALVES, R. S.
TEODORO, P. E.
FARIAS, F. C.
FARIAS, F. J. C.
CARVALHO, L. P. de
RODRIGUES, J. I. S.
BHERING, L. L.
RESENDE, M. D. V. de
dc.subject.por.fl_str_mv Genetic selection
Stability and adaptability
Mixed model methodology
Random regression
Gossypium hirsutum
Seleção genética
Natural selection
topic Genetic selection
Stability and adaptability
Mixed model methodology
Random regression
Gossypium hirsutum
Seleção genética
Natural selection
description Cotton produces one of the most important textile fibers of the world and has great relevance in the world economy. It is an economically important crop in Brazil, which is the world?s fifth largest producer. However, studies evaluating the genotype x environment (G x E) interactions in cotton are scarce in this country. Therefore, the goal of this study was to evaluate the G x E interactions in two important traits in cotton (fiber yield and fiber length) using the method proposed by Eberhart and Russell (simple linear regression) and reaction norm models (random regression). Eight trials with sixteen upland cotton genotypes, conducted in a randomized block design, were used. It was possible to identify a genotype with wide adaptability and stability for both traits. Reaction norm models have excellent theoretical and practical properties and led to more informative and accurate results than the method proposed by Eberhart and Russell and should, therefore, be preferred. Curves of genotypic values as a function of the environmental gradient, which predict the behavior of the genotypes along the environmental gradient, were generated. These curves make possible the recommendation to untested environmental levels.
publishDate 2017
dc.date.none.fl_str_mv 2017-12-23T23:29:58Z
2017-12-23T23:29:58Z
2017-12-22
2017
2017-12-23T23:29:58Z
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 Genetics and Molecular Research, v. 16, n. 3, gmr16039726, 2017.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1083385
10.4238/gmr16039726
identifier_str_mv Genetics and Molecular Research, v. 16, n. 3, gmr16039726, 2017.
10.4238/gmr16039726
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1083385
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 12 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)
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instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
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reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
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