Factor analysis applied to the G+GE matrix via REML/BLUP for multi-environment data
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 UFLA |
Texto Completo: | http://repositorio.ufla.br/jspui/handle/1/29957 |
Resumo: | 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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Factor analysis applied to the G+GE matrix via REML/BLUP for multi-environment dataGenotype x Environment interactionAdaptabilityEnvironmental stratificationMultivariate analysisThe 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 Biotechnology2018-08-13T13:40:16Z2018-08-13T13:40:16Z2016info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfPEIXOUTO, L. S.; NUNES, J. A. R.; FURTADO, D. F. Factor analysis applied to the G+GE matrix via REML/BLUP for multi-environment data. Crop Breeding and Applied Biotechnology, Viçosa, MG, v. 16, n. 1, p. 1-6, 2016.http://repositorio.ufla.br/jspui/handle/1/29957Crop Breeding and Applied Biotechnologyreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessPeixouto, Leandro SantosNunes, José Airton RodriguesFurtado; Daniel Ferreiraeng2023-05-19T18:48:07Zoai:localhost:1/29957Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2023-05-19T18:48:07Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
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 |
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 2018-08-13T13:40:16Z 2018-08-13T13:40:16Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
PEIXOUTO, L. S.; NUNES, J. A. R.; FURTADO, D. F. Factor analysis applied to the G+GE matrix via REML/BLUP for multi-environment data. Crop Breeding and Applied Biotechnology, Viçosa, MG, v. 16, n. 1, p. 1-6, 2016. http://repositorio.ufla.br/jspui/handle/1/29957 |
identifier_str_mv |
PEIXOUTO, L. S.; NUNES, J. A. R.; FURTADO, D. F. Factor analysis applied to the G+GE matrix via REML/BLUP for multi-environment data. Crop Breeding and Applied Biotechnology, Viçosa, MG, v. 16, n. 1, p. 1-6, 2016. |
url |
http://repositorio.ufla.br/jspui/handle/1/29957 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
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 reponame:Repositório Institucional da UFLA instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Repositório Institucional da UFLA |
collection |
Repositório Institucional da UFLA |
repository.name.fl_str_mv |
Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
nivaldo@ufla.br || repositorio.biblioteca@ufla.br |
_version_ |
1815438945469595648 |