Hybrid maize selection through GGE biplot analysis.

Detalhes bibliográficos
Autor(a) principal: OLIVEIRA, T. R. A. de
Data de Publicação: 2019
Outros Autores: CARVALHO, H. W. L. de, OLIVEIRA, G. H. F., COSTA, E. F. N., GRAVINA, G. de A., SANTOS, R. D. dos, CARVALHO FILHO, J. L. S. 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/1117410
Resumo: The cultivation of genotypes non-adapted to the cultivation region of interest is among the main factors responsible for low yield. The aim of the present study is to select hybrid maize through GGE biplot analysis and to assess its adaptability and stability in different environments in Northeastern Brazil. Twenty-five hybrid maize cultivars were assessed in ten different environments in Northeastern Brazil in 2012 and 2013 based on the randomized block design, with two replications. The analysis of variance and assessment of genotype adaptability and stability were made through GGE biplot analysis, based on grain yield. Analysis of variance results showed different performances depending on the genotype, as well as genotype/environment interaction. The biplot analysis was efficient on data interpretation and represented 63.73% of the total variation in the first two main components, it also allowed classifying the ten environments into three macro-environments. Most environments were positively correlated. Hybrids 2 B 604 HX, 30 A 95 HX, 2 B 587 HX and 2 B 710 HX were responsive and stable. Hybrid 30 A 16 HX was recommended for macro-environments2 and 3. Cultivar 30 A 68 HX was recommended to environment 1. São Raimundo das Mangabeiras and Nova Santa Rosa counties were discriminating and representative. Nossa Senhora das Dores, Umbaúba, Teresina, Brejo, Frei Paulo, Colinas and Balsa counties were ambiguous and non-recommended for further evaluations.
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spelling Hybrid maize selection through GGE biplot analysis.Melhoramento de plantasAnálise biplot GGEAnalise multivariadaSeleção híbridaMilhoMelhoramento Genético VegetalPlant breedingThe cultivation of genotypes non-adapted to the cultivation region of interest is among the main factors responsible for low yield. The aim of the present study is to select hybrid maize through GGE biplot analysis and to assess its adaptability and stability in different environments in Northeastern Brazil. Twenty-five hybrid maize cultivars were assessed in ten different environments in Northeastern Brazil in 2012 and 2013 based on the randomized block design, with two replications. The analysis of variance and assessment of genotype adaptability and stability were made through GGE biplot analysis, based on grain yield. Analysis of variance results showed different performances depending on the genotype, as well as genotype/environment interaction. The biplot analysis was efficient on data interpretation and represented 63.73% of the total variation in the first two main components, it also allowed classifying the ten environments into three macro-environments. Most environments were positively correlated. Hybrids 2 B 604 HX, 30 A 95 HX, 2 B 587 HX and 2 B 710 HX were responsive and stable. Hybrid 30 A 16 HX was recommended for macro-environments2 and 3. Cultivar 30 A 68 HX was recommended to environment 1. São Raimundo das Mangabeiras and Nova Santa Rosa counties were discriminating and representative. Nossa Senhora das Dores, Umbaúba, Teresina, Brejo, Frei Paulo, Colinas and Balsa counties were ambiguous and non-recommended for further evaluations.Tâmara Rebecca Albuquerque de Oliveira; Hélio Wilson Lemos de Carvalho; Gustavo Hugo Ferreira Oliveira; Emiliano Fernandes Nassau Costa; Geraldo de Amaral Gravina; RAFAEL DANTAS DOS SANTOS, CPATSA; José Luiz Sandes de Carvalho Filho.OLIVEIRA, T. R. A. deCARVALHO, H. W. L. deOLIVEIRA, G. H. F.COSTA, E. F. N.GRAVINA, G. de A.SANTOS, R. D. dosCARVALHO FILHO, J. L. S. de2019-12-20T18:09:23Z2019-12-20T18:09:23Z2019-12-2020192019-12-20T18:09:23Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleBragantia, v. 78, n. 2, p. 166-174, 2019.http://www.alice.cnptia.embrapa.br/alice/handle/doc/111741010.1590/1678-4499.20170438enginfo: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:EMBRAPA2019-12-20T18:09:30Zoai:www.alice.cnptia.embrapa.br:doc/1117410Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542019-12-20T18:09:30falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542019-12-20T18:09:30Repositório 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 Hybrid maize selection through GGE biplot analysis.
title Hybrid maize selection through GGE biplot analysis.
spellingShingle Hybrid maize selection through GGE biplot analysis.
OLIVEIRA, T. R. A. de
Melhoramento de plantas
Análise biplot GGE
Analise multivariada
Seleção híbrida
Milho
Melhoramento Genético Vegetal
Plant breeding
title_short Hybrid maize selection through GGE biplot analysis.
title_full Hybrid maize selection through GGE biplot analysis.
title_fullStr Hybrid maize selection through GGE biplot analysis.
title_full_unstemmed Hybrid maize selection through GGE biplot analysis.
title_sort Hybrid maize selection through GGE biplot analysis.
author OLIVEIRA, T. R. A. de
author_facet OLIVEIRA, T. R. A. de
CARVALHO, H. W. L. de
OLIVEIRA, G. H. F.
COSTA, E. F. N.
GRAVINA, G. de A.
SANTOS, R. D. dos
CARVALHO FILHO, J. L. S. de
author_role author
author2 CARVALHO, H. W. L. de
OLIVEIRA, G. H. F.
COSTA, E. F. N.
GRAVINA, G. de A.
SANTOS, R. D. dos
CARVALHO FILHO, J. L. S. de
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Tâmara Rebecca Albuquerque de Oliveira; Hélio Wilson Lemos de Carvalho; Gustavo Hugo Ferreira Oliveira; Emiliano Fernandes Nassau Costa; Geraldo de Amaral Gravina; RAFAEL DANTAS DOS SANTOS, CPATSA; José Luiz Sandes de Carvalho Filho.
dc.contributor.author.fl_str_mv OLIVEIRA, T. R. A. de
CARVALHO, H. W. L. de
OLIVEIRA, G. H. F.
COSTA, E. F. N.
GRAVINA, G. de A.
SANTOS, R. D. dos
CARVALHO FILHO, J. L. S. de
dc.subject.por.fl_str_mv Melhoramento de plantas
Análise biplot GGE
Analise multivariada
Seleção híbrida
Milho
Melhoramento Genético Vegetal
Plant breeding
topic Melhoramento de plantas
Análise biplot GGE
Analise multivariada
Seleção híbrida
Milho
Melhoramento Genético Vegetal
Plant breeding
description The cultivation of genotypes non-adapted to the cultivation region of interest is among the main factors responsible for low yield. The aim of the present study is to select hybrid maize through GGE biplot analysis and to assess its adaptability and stability in different environments in Northeastern Brazil. Twenty-five hybrid maize cultivars were assessed in ten different environments in Northeastern Brazil in 2012 and 2013 based on the randomized block design, with two replications. The analysis of variance and assessment of genotype adaptability and stability were made through GGE biplot analysis, based on grain yield. Analysis of variance results showed different performances depending on the genotype, as well as genotype/environment interaction. The biplot analysis was efficient on data interpretation and represented 63.73% of the total variation in the first two main components, it also allowed classifying the ten environments into three macro-environments. Most environments were positively correlated. Hybrids 2 B 604 HX, 30 A 95 HX, 2 B 587 HX and 2 B 710 HX were responsive and stable. Hybrid 30 A 16 HX was recommended for macro-environments2 and 3. Cultivar 30 A 68 HX was recommended to environment 1. São Raimundo das Mangabeiras and Nova Santa Rosa counties were discriminating and representative. Nossa Senhora das Dores, Umbaúba, Teresina, Brejo, Frei Paulo, Colinas and Balsa counties were ambiguous and non-recommended for further evaluations.
publishDate 2019
dc.date.none.fl_str_mv 2019-12-20T18:09:23Z
2019-12-20T18:09:23Z
2019-12-20
2019
2019-12-20T18:09:23Z
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 Bragantia, v. 78, n. 2, p. 166-174, 2019.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1117410
10.1590/1678-4499.20170438
identifier_str_mv Bragantia, v. 78, n. 2, p. 166-174, 2019.
10.1590/1678-4499.20170438
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1117410
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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