Biplot analysis of phenotypic stability in upland cotton genotypes in Mato Grosso.
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , |
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/1065921 |
Resumo: | Seed cotton yield is a trait governed by multiple genes that cause changes in the performance of genotypes depending on the cultivation environment. Breeding programs examine the genotype x environment interaction (GE) using precise statistical methods, such as AMMI (additive main effects and multiplicative interaction) and GGE biplot (genotype main effects + genotype x environment interaction). The AMMI method combines the analysis of variance and principal components, to adjust the main effects (genotypes and environments) and the effects of GE interaction, respectively. The GGE biplot groups the genotype additive effect together with the multiplicative effect of the GE interaction, and submits both of these to the principal components analysis. The aim of this study was to investigate the association between the AMMI and GGE biplot methods and select cotton genotypes that simultaneously showed high productivity of seed cotton and stability in Mato Grosso environments. Trials were conducted with cotton cultivars in eight environments across Mato Grosso State in the 2008/2009 crop season. The experiment used a randomized block design with 16 genotypes and four replicates per genotype x environment combination. Data for seeds cotton productivity were analyzed by AMMI and GGE biplot methods. Both methods were concordant in the discrimination of environments and genotypes for phenotypic stability. The genotypes BRS ARAÇÁ and LD 05 CV had high seed cotton productivity and phenotypic stability, and could be grown in all environments across Mato Grosso State. |
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Biplot analysis of phenotypic stability in upland cotton genotypes in Mato Grosso.GenótipoGossypium hirsutumAlgodãoCottonSeed cotton yield is a trait governed by multiple genes that cause changes in the performance of genotypes depending on the cultivation environment. Breeding programs examine the genotype x environment interaction (GE) using precise statistical methods, such as AMMI (additive main effects and multiplicative interaction) and GGE biplot (genotype main effects + genotype x environment interaction). The AMMI method combines the analysis of variance and principal components, to adjust the main effects (genotypes and environments) and the effects of GE interaction, respectively. The GGE biplot groups the genotype additive effect together with the multiplicative effect of the GE interaction, and submits both of these to the principal components analysis. The aim of this study was to investigate the association between the AMMI and GGE biplot methods and select cotton genotypes that simultaneously showed high productivity of seed cotton and stability in Mato Grosso environments. Trials were conducted with cotton cultivars in eight environments across Mato Grosso State in the 2008/2009 crop season. The experiment used a randomized block design with 16 genotypes and four replicates per genotype x environment combination. Data for seeds cotton productivity were analyzed by AMMI and GGE biplot methods. Both methods were concordant in the discrimination of environments and genotypes for phenotypic stability. The genotypes BRS ARAÇÁ and LD 05 CV had high seed cotton productivity and phenotypic stability, and could be grown in all environments across Mato Grosso State.FRANCISCO JOSE CORREIA FARIAS, CNPA; LUIZ PAULO DE CARVALHO, CNPA; JOAO LUIS DA SILVA FILHO, CNPA; PAULO EDUARDO TEODORO, UFV.FARIAS, F. J. C.CARVALHO, L. P. deSILVA FILHO, J. L. daTEODORO, P. E.2017-03-03T11:11:11Z2017-03-03T11:11:11Z2017-03-0320162017-03-03T11:11:11Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleGenetics and Molecular Research, v. 15, n. 2, 2016.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1065921enginfo: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:EMBRAPA2017-08-16T04:15:54Zoai:www.alice.cnptia.embrapa.br:doc/1065921Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542017-08-16T04:15:54falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542017-08-16T04:15:54Repositório 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 |
Biplot analysis of phenotypic stability in upland cotton genotypes in Mato Grosso. |
title |
Biplot analysis of phenotypic stability in upland cotton genotypes in Mato Grosso. |
spellingShingle |
Biplot analysis of phenotypic stability in upland cotton genotypes in Mato Grosso. FARIAS, F. J. C. Genótipo Gossypium hirsutum Algodão Cotton |
title_short |
Biplot analysis of phenotypic stability in upland cotton genotypes in Mato Grosso. |
title_full |
Biplot analysis of phenotypic stability in upland cotton genotypes in Mato Grosso. |
title_fullStr |
Biplot analysis of phenotypic stability in upland cotton genotypes in Mato Grosso. |
title_full_unstemmed |
Biplot analysis of phenotypic stability in upland cotton genotypes in Mato Grosso. |
title_sort |
Biplot analysis of phenotypic stability in upland cotton genotypes in Mato Grosso. |
author |
FARIAS, F. J. C. |
author_facet |
FARIAS, F. J. C. CARVALHO, L. P. de SILVA FILHO, J. L. da TEODORO, P. E. |
author_role |
author |
author2 |
CARVALHO, L. P. de SILVA FILHO, J. L. da TEODORO, P. E. |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
FRANCISCO JOSE CORREIA FARIAS, CNPA; LUIZ PAULO DE CARVALHO, CNPA; JOAO LUIS DA SILVA FILHO, CNPA; PAULO EDUARDO TEODORO, UFV. |
dc.contributor.author.fl_str_mv |
FARIAS, F. J. C. CARVALHO, L. P. de SILVA FILHO, J. L. da TEODORO, P. E. |
dc.subject.por.fl_str_mv |
Genótipo Gossypium hirsutum Algodão Cotton |
topic |
Genótipo Gossypium hirsutum Algodão Cotton |
description |
Seed cotton yield is a trait governed by multiple genes that cause changes in the performance of genotypes depending on the cultivation environment. Breeding programs examine the genotype x environment interaction (GE) using precise statistical methods, such as AMMI (additive main effects and multiplicative interaction) and GGE biplot (genotype main effects + genotype x environment interaction). The AMMI method combines the analysis of variance and principal components, to adjust the main effects (genotypes and environments) and the effects of GE interaction, respectively. The GGE biplot groups the genotype additive effect together with the multiplicative effect of the GE interaction, and submits both of these to the principal components analysis. The aim of this study was to investigate the association between the AMMI and GGE biplot methods and select cotton genotypes that simultaneously showed high productivity of seed cotton and stability in Mato Grosso environments. Trials were conducted with cotton cultivars in eight environments across Mato Grosso State in the 2008/2009 crop season. The experiment used a randomized block design with 16 genotypes and four replicates per genotype x environment combination. Data for seeds cotton productivity were analyzed by AMMI and GGE biplot methods. Both methods were concordant in the discrimination of environments and genotypes for phenotypic stability. The genotypes BRS ARAÇÁ and LD 05 CV had high seed cotton productivity and phenotypic stability, and could be grown in all environments across Mato Grosso State. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016 2017-03-03T11:11:11Z 2017-03-03T11:11:11Z 2017-03-03 2017-03-03T11:11:11Z |
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. 15, n. 2, 2016. http://www.alice.cnptia.embrapa.br/alice/handle/doc/1065921 |
identifier_str_mv |
Genetics and Molecular Research, v. 15, n. 2, 2016. |
url |
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1065921 |
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 |
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1794503433494986752 |