Adaptability and stability of maize hybrids in unreplicated multienvironment trials

Detalhes bibliográficos
Autor(a) principal: Santos, Diego
Data de Publicação: 2018
Outros Autores: Pereira, Carlos, Nunes, José Airton, Lepre, André
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista ciência agronômica (Online)
Texto Completo: http://periodicos.ufc.br/revistacienciaagronomica/article/view/84818
Resumo: In maize breeding programs conducted by private companies, it is common to perform the product advanced trials (PAT) in several cultivation environments in order to better recommend the new hybrids, as well as to provide opportunities for the farmers to evaluate their products. The aim of this study was to describe the adaptability and stability of maize hybrids from unreplicated PATs using a multivariate approach combined with univariate methods. We considered the grain yield data of twelve maize hybrids evaluated in a PATs network conducted by the company DuPont Pioneer in 80 cultivation environments in the states of Minas Gerais and Goias, in second-crop of 2014. The AMMI analysis was employed and additionally we applied the methods based on bisegmented linear regression, Lin and Binns index (1988) and Annicchiarico index (1992). Significant differences were verified among the tested hybrids. The macro-environmental variation and the effect of hybrid by environment (H x E) interaction were expressive. The application of the AMMI method allowed the study of the H x E interaction based on maize PATs. Hybrids 7 and 8 are recommended for higher quality environments, while hybrids 3, 5 and 12 present wide adaptability. The Lin and Binns (1988) and Annicchiarico (1992) indexes highlight the hybrid 8 as the most promising for associating high productivity and lower risk in the tested cultivation environments.
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spelling Adaptability and stability of maize hybrids in unreplicated multienvironment trialsZea mays Product Advancement Trials Genotype by Environment Interaction AMMI Reliability IndexIn maize breeding programs conducted by private companies, it is common to perform the product advanced trials (PAT) in several cultivation environments in order to better recommend the new hybrids, as well as to provide opportunities for the farmers to evaluate their products. The aim of this study was to describe the adaptability and stability of maize hybrids from unreplicated PATs using a multivariate approach combined with univariate methods. We considered the grain yield data of twelve maize hybrids evaluated in a PATs network conducted by the company DuPont Pioneer in 80 cultivation environments in the states of Minas Gerais and Goias, in second-crop of 2014. The AMMI analysis was employed and additionally we applied the methods based on bisegmented linear regression, Lin and Binns index (1988) and Annicchiarico index (1992). Significant differences were verified among the tested hybrids. The macro-environmental variation and the effect of hybrid by environment (H x E) interaction were expressive. The application of the AMMI method allowed the study of the H x E interaction based on maize PATs. Hybrids 7 and 8 are recommended for higher quality environments, while hybrids 3, 5 and 12 present wide adaptability. The Lin and Binns (1988) and Annicchiarico (1992) indexes highlight the hybrid 8 as the most promising for associating high productivity and lower risk in the tested cultivation environments.Revista Ciência Agronômica2018-10-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://periodicos.ufc.br/revistacienciaagronomica/article/view/84818Revista Ciência Agronômica; v. 50 n. 1 (2019)1806-66900045-6888reponame:Revista ciência agronômica (Online)instname:Universidade Federal do Ceará (UFC)instacron:UFCenghttp://periodicos.ufc.br/revistacienciaagronomica/article/view/84818/228970Santos, DiegoPereira, CarlosNunes, José AirtonLepre, Andréinfo:eu-repo/semantics/openAccess2023-03-01T05:04:34Zoai:periodicos.ufc:article/84818Revistahttps://periodicos.ufc.br/revistacienciaagronomicaPUBhttps://periodicos.ufc.br/revistacienciaagronomica/oai||alekdutra@ufc.br|| ccarev@ufc.br1806-66900045-6888opendoar:2025-03-10T10:26:58.573343Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC)true
dc.title.none.fl_str_mv Adaptability and stability of maize hybrids in unreplicated multienvironment trials
title Adaptability and stability of maize hybrids in unreplicated multienvironment trials
spellingShingle Adaptability and stability of maize hybrids in unreplicated multienvironment trials
Santos, Diego
Zea mays
Product Advancement Trials
Genotype by Environment Interaction
AMMI
Reliability Index
title_short Adaptability and stability of maize hybrids in unreplicated multienvironment trials
title_full Adaptability and stability of maize hybrids in unreplicated multienvironment trials
title_fullStr Adaptability and stability of maize hybrids in unreplicated multienvironment trials
title_full_unstemmed Adaptability and stability of maize hybrids in unreplicated multienvironment trials
title_sort Adaptability and stability of maize hybrids in unreplicated multienvironment trials
author Santos, Diego
author_facet Santos, Diego
Pereira, Carlos
Nunes, José Airton
Lepre, André
author_role author
author2 Pereira, Carlos
Nunes, José Airton
Lepre, André
author2_role author
author
author
dc.contributor.author.fl_str_mv Santos, Diego
Pereira, Carlos
Nunes, José Airton
Lepre, André
dc.subject.por.fl_str_mv Zea mays
Product Advancement Trials
Genotype by Environment Interaction
AMMI
Reliability Index
topic Zea mays
Product Advancement Trials
Genotype by Environment Interaction
AMMI
Reliability Index
description In maize breeding programs conducted by private companies, it is common to perform the product advanced trials (PAT) in several cultivation environments in order to better recommend the new hybrids, as well as to provide opportunities for the farmers to evaluate their products. The aim of this study was to describe the adaptability and stability of maize hybrids from unreplicated PATs using a multivariate approach combined with univariate methods. We considered the grain yield data of twelve maize hybrids evaluated in a PATs network conducted by the company DuPont Pioneer in 80 cultivation environments in the states of Minas Gerais and Goias, in second-crop of 2014. The AMMI analysis was employed and additionally we applied the methods based on bisegmented linear regression, Lin and Binns index (1988) and Annicchiarico index (1992). Significant differences were verified among the tested hybrids. The macro-environmental variation and the effect of hybrid by environment (H x E) interaction were expressive. The application of the AMMI method allowed the study of the H x E interaction based on maize PATs. Hybrids 7 and 8 are recommended for higher quality environments, while hybrids 3, 5 and 12 present wide adaptability. The Lin and Binns (1988) and Annicchiarico (1992) indexes highlight the hybrid 8 as the most promising for associating high productivity and lower risk in the tested cultivation environments.
publishDate 2018
dc.date.none.fl_str_mv 2018-10-11
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://periodicos.ufc.br/revistacienciaagronomica/article/view/84818
url http://periodicos.ufc.br/revistacienciaagronomica/article/view/84818
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://periodicos.ufc.br/revistacienciaagronomica/article/view/84818/228970
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Revista Ciência Agronômica
publisher.none.fl_str_mv Revista Ciência Agronômica
dc.source.none.fl_str_mv Revista Ciência Agronômica; v. 50 n. 1 (2019)
1806-6690
0045-6888
reponame:Revista ciência agronômica (Online)
instname:Universidade Federal do Ceará (UFC)
instacron:UFC
instname_str Universidade Federal do Ceará (UFC)
instacron_str UFC
institution UFC
reponame_str Revista ciência agronômica (Online)
collection Revista ciência agronômica (Online)
repository.name.fl_str_mv Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC)
repository.mail.fl_str_mv ||alekdutra@ufc.br|| ccarev@ufc.br
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