Hybrid maize selection through GGE biplot analysis.
Autor(a) principal: | |
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Data de Publicação: | 2019 |
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/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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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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1794503486613749760 |