Mega-environment analysis of maize breeding data from Brazil
Autor(a) principal: | |
---|---|
Data de Publicação: | 2022 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://repositorio.ufla.br/jspui/handle/1/53334 |
Resumo: | The development and recommendation of single cross maize hybrids (SH) to be used in extensive land areas (mega-environments), and in different crop seasons requires many experiments under numerous environmental conditions. The question we asked is if the data from these multi-environment experiments are sufficient to identify the best hybrid combinations. The aim of this study was to critically analyze the phenotype data of experiments of yield, established by a large seed producing company, under a high level of imbalance. Data from evaluation of 2770 SH were used from experiments conducted over four years, involving the first and second crop seasons, in 50 locations of different years and regions of Brazil. Different types of analysis were carried out and genetic and non-genetic components were estimated, with emphasis on the different interactions of the SH with the environments. Results showed that the coincidence of common hybrids in these experiments is normally small. The estimates of the correlations between of the hybrids coinciding in the environments two by two is of low magnitude. The hybrid × crop season interaction was always expressive; however, the interactions of hybrids and other environmental variables were also important. Under these conditions, alternatives were discussed for making with the information obtained from the experiments, can be more efficient on the process to obtain new hybrids by companies. |
id |
UFLA_56dacc1cb26deff94801d1a7d2cf4fc0 |
---|---|
oai_identifier_str |
oai:localhost:1/53334 |
network_acronym_str |
UFLA |
network_name_str |
Repositório Institucional da UFLA |
repository_id_str |
|
spelling |
Mega-environment analysis of maize breeding data from BrazilGenotype × environment interactionUnbalance dataHybrid recommendation processVariance componentsPlant breedingInteração genótipo x ambienteDados não balanceadosProcesso de recomendação híbridoComponentes de variaçãoMelhoramento de plantasThe development and recommendation of single cross maize hybrids (SH) to be used in extensive land areas (mega-environments), and in different crop seasons requires many experiments under numerous environmental conditions. The question we asked is if the data from these multi-environment experiments are sufficient to identify the best hybrid combinations. The aim of this study was to critically analyze the phenotype data of experiments of yield, established by a large seed producing company, under a high level of imbalance. Data from evaluation of 2770 SH were used from experiments conducted over four years, involving the first and second crop seasons, in 50 locations of different years and regions of Brazil. Different types of analysis were carried out and genetic and non-genetic components were estimated, with emphasis on the different interactions of the SH with the environments. Results showed that the coincidence of common hybrids in these experiments is normally small. The estimates of the correlations between of the hybrids coinciding in the environments two by two is of low magnitude. The hybrid × crop season interaction was always expressive; however, the interactions of hybrids and other environmental variables were also important. Under these conditions, alternatives were discussed for making with the information obtained from the experiments, can be more efficient on the process to obtain new hybrids by companies.Escola Superior de Agricultura "Luiz de Queiroz"2022-08-19T19:41:29Z2022-08-19T19:41:29Z2022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfPEREIRA, F. de C. et al. Mega-environment analysis of maize breeding data from Brazil. Scientia Agricola, Piracicaba, v. 79, n. 2, e20200314, 2022. DOI: 10.1590/1678-992X-2020-0314 .http://repositorio.ufla.br/jspui/handle/1/53334Scientia Agricolareponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessPereira, Francielly de CássiaRamalho, Magno Antonio PattoResende Junior, Marcio Fernando Ribeiro deVon Pinho, Renzo Garciaeng2023-05-26T18:57:07Zoai:localhost:1/53334Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2023-05-26T18:57:07Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Mega-environment analysis of maize breeding data from Brazil |
title |
Mega-environment analysis of maize breeding data from Brazil |
spellingShingle |
Mega-environment analysis of maize breeding data from Brazil Pereira, Francielly de Cássia Genotype × environment interaction Unbalance data Hybrid recommendation process Variance components Plant breeding Interação genótipo x ambiente Dados não balanceados Processo de recomendação híbrido Componentes de variação Melhoramento de plantas |
title_short |
Mega-environment analysis of maize breeding data from Brazil |
title_full |
Mega-environment analysis of maize breeding data from Brazil |
title_fullStr |
Mega-environment analysis of maize breeding data from Brazil |
title_full_unstemmed |
Mega-environment analysis of maize breeding data from Brazil |
title_sort |
Mega-environment analysis of maize breeding data from Brazil |
author |
Pereira, Francielly de Cássia |
author_facet |
Pereira, Francielly de Cássia Ramalho, Magno Antonio Patto Resende Junior, Marcio Fernando Ribeiro de Von Pinho, Renzo Garcia |
author_role |
author |
author2 |
Ramalho, Magno Antonio Patto Resende Junior, Marcio Fernando Ribeiro de Von Pinho, Renzo Garcia |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Pereira, Francielly de Cássia Ramalho, Magno Antonio Patto Resende Junior, Marcio Fernando Ribeiro de Von Pinho, Renzo Garcia |
dc.subject.por.fl_str_mv |
Genotype × environment interaction Unbalance data Hybrid recommendation process Variance components Plant breeding Interação genótipo x ambiente Dados não balanceados Processo de recomendação híbrido Componentes de variação Melhoramento de plantas |
topic |
Genotype × environment interaction Unbalance data Hybrid recommendation process Variance components Plant breeding Interação genótipo x ambiente Dados não balanceados Processo de recomendação híbrido Componentes de variação Melhoramento de plantas |
description |
The development and recommendation of single cross maize hybrids (SH) to be used in extensive land areas (mega-environments), and in different crop seasons requires many experiments under numerous environmental conditions. The question we asked is if the data from these multi-environment experiments are sufficient to identify the best hybrid combinations. The aim of this study was to critically analyze the phenotype data of experiments of yield, established by a large seed producing company, under a high level of imbalance. Data from evaluation of 2770 SH were used from experiments conducted over four years, involving the first and second crop seasons, in 50 locations of different years and regions of Brazil. Different types of analysis were carried out and genetic and non-genetic components were estimated, with emphasis on the different interactions of the SH with the environments. Results showed that the coincidence of common hybrids in these experiments is normally small. The estimates of the correlations between of the hybrids coinciding in the environments two by two is of low magnitude. The hybrid × crop season interaction was always expressive; however, the interactions of hybrids and other environmental variables were also important. Under these conditions, alternatives were discussed for making with the information obtained from the experiments, can be more efficient on the process to obtain new hybrids by companies. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-08-19T19:41:29Z 2022-08-19T19:41:29Z 2022 |
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 |
PEREIRA, F. de C. et al. Mega-environment analysis of maize breeding data from Brazil. Scientia Agricola, Piracicaba, v. 79, n. 2, e20200314, 2022. DOI: 10.1590/1678-992X-2020-0314 . http://repositorio.ufla.br/jspui/handle/1/53334 |
identifier_str_mv |
PEREIRA, F. de C. et al. Mega-environment analysis of maize breeding data from Brazil. Scientia Agricola, Piracicaba, v. 79, n. 2, e20200314, 2022. DOI: 10.1590/1678-992X-2020-0314 . |
url |
http://repositorio.ufla.br/jspui/handle/1/53334 |
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 |
Escola Superior de Agricultura "Luiz de Queiroz" |
publisher.none.fl_str_mv |
Escola Superior de Agricultura "Luiz de Queiroz" |
dc.source.none.fl_str_mv |
Scientia Agricola 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_ |
1807835138065694720 |