Mega-environment analysis of maize breeding data from Brazil

Detalhes bibliográficos
Autor(a) principal: Pereira,Francielly de Cássia
Data de Publicação: 2022
Outros Autores: Ramalho,Magno Antonio Patto, Resende Junior,Marcio Fernando Ribeiro de, Pinho,Renzo Garcia Von
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Agrícola (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162022000201102
Resumo: ABSTRACT: 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.
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spelling Mega-environment analysis of maize breeding data from Brazilgenotype × environment interactionunbalance datahybrid recommendation processvariance componentsplant breedingABSTRACT: 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.Escola Superior de Agricultura "Luiz de Queiroz"2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162022000201102Scientia Agricola v.79 n.2 2022reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USP10.1590/1678-992x-2020-0314info:eu-repo/semantics/openAccessPereira,Francielly de CássiaRamalho,Magno Antonio PattoResende Junior,Marcio Fernando Ribeiro dePinho,Renzo Garcia Voneng2021-05-14T00:00:00Zoai:scielo:S0103-90162022000201102Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2021-05-14T00:00Scientia Agrícola (Online) - Universidade de São Paulo (USP)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
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
Pinho,Renzo Garcia Von
author_role author
author2 Ramalho,Magno Antonio Patto
Resende Junior,Marcio Fernando Ribeiro de
Pinho,Renzo Garcia Von
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
Pinho,Renzo Garcia Von
dc.subject.por.fl_str_mv genotype × environment interaction
unbalance data
hybrid recommendation process
variance components
plant breeding
topic genotype × environment interaction
unbalance data
hybrid recommendation process
variance components
plant breeding
description ABSTRACT: 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 2022-01-01
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=S0103-90162022000201102
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162022000201102
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1678-992x-2020-0314
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 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 v.79 n.2 2022
reponame:Scientia Agrícola (Online)
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Scientia Agrícola (Online)
collection Scientia Agrícola (Online)
repository.name.fl_str_mv Scientia Agrícola (Online) - Universidade de São Paulo (USP)
repository.mail.fl_str_mv scientia@usp.br||alleoni@usp.br
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