Factor analysis applied to the G+GE matrix via REML/BLUP for multi-environment data

Detalhes bibliográficos
Autor(a) principal: Peixouto,Leandro Santos
Data de Publicação: 2016
Outros Autores: Nunes,José Airton Rodrigues, Furtado,Daniel Ferreira
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Crop Breeding and Applied Biotechnology
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1984-70332016000100001
Resumo: Abstract The genotype x environment interaction is frequently observed in many crops and studies on environmental stratification and genotype adaptability have been proposed to understand it. The aim of this study was to carry out factor analysis in data from multi-environment experiments by the mixed model approach (REML/BLUP). Instead of adjusted phenotypic means, a matrix containing the genotypic effects added to the effects of the genotype x environment interaction (G+GE) was used, predicted via REML/BLUP in joint analysis (designated as R-FGGE). In the study, data from 36 common bean lines evaluated in 15 environments were used. By this proposal, 46.7% of the environments were gathered in two groups, one with four and the other with three environments. The R-FGGE has the same characteristics as the previous proposals, that is, ease of identification of mega-environments and genotypes with broad adaptability, along with the advantages associated with the mixed model methodology.
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spelling Factor analysis applied to the G+GE matrix via REML/BLUP for multi-environment dataGenotype x environment interactionadaptabilityenvironmental stratificationmultivariate analysisAbstract The genotype x environment interaction is frequently observed in many crops and studies on environmental stratification and genotype adaptability have been proposed to understand it. The aim of this study was to carry out factor analysis in data from multi-environment experiments by the mixed model approach (REML/BLUP). Instead of adjusted phenotypic means, a matrix containing the genotypic effects added to the effects of the genotype x environment interaction (G+GE) was used, predicted via REML/BLUP in joint analysis (designated as R-FGGE). In the study, data from 36 common bean lines evaluated in 15 environments were used. By this proposal, 46.7% of the environments were gathered in two groups, one with four and the other with three environments. The R-FGGE has the same characteristics as the previous proposals, that is, ease of identification of mega-environments and genotypes with broad adaptability, along with the advantages associated with the mixed model methodology.Crop Breeding and Applied Biotechnology2016-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1984-70332016000100001Crop Breeding and Applied Biotechnology v.16 n.1 2016reponame:Crop Breeding and Applied Biotechnologyinstname:Sociedade Brasileira de Melhoramento de Plantasinstacron:CBAB10.1590/1984-70332016v16n1a1info:eu-repo/semantics/openAccessPeixouto,Leandro SantosNunes,José Airton RodriguesFurtado,Daniel Ferreiraeng2016-04-19T00:00:00Zoai:scielo:S1984-70332016000100001Revistahttps://cbab.sbmp.org.br/#ONGhttps://old.scielo.br/oai/scielo-oai.phpcbabjournal@gmail.com||cbab@ufv.br1984-70331518-7853opendoar:2016-04-19T00:00Crop Breeding and Applied Biotechnology - Sociedade Brasileira de Melhoramento de Plantasfalse
dc.title.none.fl_str_mv Factor analysis applied to the G+GE matrix via REML/BLUP for multi-environment data
title Factor analysis applied to the G+GE matrix via REML/BLUP for multi-environment data
spellingShingle Factor analysis applied to the G+GE matrix via REML/BLUP for multi-environment data
Peixouto,Leandro Santos
Genotype x environment interaction
adaptability
environmental stratification
multivariate analysis
title_short Factor analysis applied to the G+GE matrix via REML/BLUP for multi-environment data
title_full Factor analysis applied to the G+GE matrix via REML/BLUP for multi-environment data
title_fullStr Factor analysis applied to the G+GE matrix via REML/BLUP for multi-environment data
title_full_unstemmed Factor analysis applied to the G+GE matrix via REML/BLUP for multi-environment data
title_sort Factor analysis applied to the G+GE matrix via REML/BLUP for multi-environment data
author Peixouto,Leandro Santos
author_facet Peixouto,Leandro Santos
Nunes,José Airton Rodrigues
Furtado,Daniel Ferreira
author_role author
author2 Nunes,José Airton Rodrigues
Furtado,Daniel Ferreira
author2_role author
author
dc.contributor.author.fl_str_mv Peixouto,Leandro Santos
Nunes,José Airton Rodrigues
Furtado,Daniel Ferreira
dc.subject.por.fl_str_mv Genotype x environment interaction
adaptability
environmental stratification
multivariate analysis
topic Genotype x environment interaction
adaptability
environmental stratification
multivariate analysis
description Abstract The genotype x environment interaction is frequently observed in many crops and studies on environmental stratification and genotype adaptability have been proposed to understand it. The aim of this study was to carry out factor analysis in data from multi-environment experiments by the mixed model approach (REML/BLUP). Instead of adjusted phenotypic means, a matrix containing the genotypic effects added to the effects of the genotype x environment interaction (G+GE) was used, predicted via REML/BLUP in joint analysis (designated as R-FGGE). In the study, data from 36 common bean lines evaluated in 15 environments were used. By this proposal, 46.7% of the environments were gathered in two groups, one with four and the other with three environments. The R-FGGE has the same characteristics as the previous proposals, that is, ease of identification of mega-environments and genotypes with broad adaptability, along with the advantages associated with the mixed model methodology.
publishDate 2016
dc.date.none.fl_str_mv 2016-03-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1984-70332016000100001
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1984-70332016000100001
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1984-70332016v16n1a1
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Crop Breeding and Applied Biotechnology
publisher.none.fl_str_mv Crop Breeding and Applied Biotechnology
dc.source.none.fl_str_mv Crop Breeding and Applied Biotechnology v.16 n.1 2016
reponame:Crop Breeding and Applied Biotechnology
instname:Sociedade Brasileira de Melhoramento de Plantas
instacron:CBAB
instname_str Sociedade Brasileira de Melhoramento de Plantas
instacron_str CBAB
institution CBAB
reponame_str Crop Breeding and Applied Biotechnology
collection Crop Breeding and Applied Biotechnology
repository.name.fl_str_mv Crop Breeding and Applied Biotechnology - Sociedade Brasileira de Melhoramento de Plantas
repository.mail.fl_str_mv cbabjournal@gmail.com||cbab@ufv.br
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