Genetic progress in popcorn recurrent selection by a multivariate mixed-model approach

Bibliographic Details
Main Author: Ematné,Hugo Junqueira
Publication Date: 2018
Other Authors: Nunes,José Airton Rodrigues, Souza,João Cândido de, Muñoz,Patrício Ricardo
Format: Article
Language: eng
Source: Ciência e Agrotecnologia (Online)
Download full: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542018000200159
Summary: ABSTRACT Recurrent selection is a viable alternative for popcorn breeding. However, frequent verification of progress attained is required. The aim of this study was to estimate the genetic progress attained for popping expansion (PE) and grain yield (GY) after four cycles of recurrent selection and to compare this progress with the expected progress estimated at the end of each cycle while considering the genetic relationships between the progenies via univariate and multivariate mixed-model approaches. To estimate the genetic parameters and gains from indirect selection, cycles 1, 2, 3, and 4 of a UFLA population were used. To estimate the genetic gains achieved, the following cycles were used: UFLA (original) and cycles 0, 1, 2, 3, and 4, evaluated in three environments. The multivariate approach provided more accurate estimates than did the univariate approach. There was genetic gain for PE in the recurrent selection program. In contrast, gain was not observed for GY using the different estimation strategies.
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spelling Genetic progress in popcorn recurrent selection by a multivariate mixed-model approachPlant breedinggrain yieldpopping expansionABSTRACT Recurrent selection is a viable alternative for popcorn breeding. However, frequent verification of progress attained is required. The aim of this study was to estimate the genetic progress attained for popping expansion (PE) and grain yield (GY) after four cycles of recurrent selection and to compare this progress with the expected progress estimated at the end of each cycle while considering the genetic relationships between the progenies via univariate and multivariate mixed-model approaches. To estimate the genetic parameters and gains from indirect selection, cycles 1, 2, 3, and 4 of a UFLA population were used. To estimate the genetic gains achieved, the following cycles were used: UFLA (original) and cycles 0, 1, 2, 3, and 4, evaluated in three environments. The multivariate approach provided more accurate estimates than did the univariate approach. There was genetic gain for PE in the recurrent selection program. In contrast, gain was not observed for GY using the different estimation strategies.Editora da UFLA2018-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542018000200159Ciência e Agrotecnologia v.42 n.2 2018reponame:Ciência e Agrotecnologia (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLA10.1590/1413-70542018422016817info:eu-repo/semantics/openAccessEmatné,Hugo JunqueiraNunes,José Airton RodriguesSouza,João Cândido deMuñoz,Patrício Ricardoeng2018-06-18T00:00:00Zoai:scielo:S1413-70542018000200159Revistahttp://www.scielo.br/cagroPUBhttps://old.scielo.br/oai/scielo-oai.php||renpaiva@dbi.ufla.br|| editora@editora.ufla.br1981-18291413-7054opendoar:2018-06-18T00:00Ciência e Agrotecnologia (Online) - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Genetic progress in popcorn recurrent selection by a multivariate mixed-model approach
title Genetic progress in popcorn recurrent selection by a multivariate mixed-model approach
spellingShingle Genetic progress in popcorn recurrent selection by a multivariate mixed-model approach
Ematné,Hugo Junqueira
Plant breeding
grain yield
popping expansion
title_short Genetic progress in popcorn recurrent selection by a multivariate mixed-model approach
title_full Genetic progress in popcorn recurrent selection by a multivariate mixed-model approach
title_fullStr Genetic progress in popcorn recurrent selection by a multivariate mixed-model approach
title_full_unstemmed Genetic progress in popcorn recurrent selection by a multivariate mixed-model approach
title_sort Genetic progress in popcorn recurrent selection by a multivariate mixed-model approach
author Ematné,Hugo Junqueira
author_facet Ematné,Hugo Junqueira
Nunes,José Airton Rodrigues
Souza,João Cândido de
Muñoz,Patrício Ricardo
author_role author
author2 Nunes,José Airton Rodrigues
Souza,João Cândido de
Muñoz,Patrício Ricardo
author2_role author
author
author
dc.contributor.author.fl_str_mv Ematné,Hugo Junqueira
Nunes,José Airton Rodrigues
Souza,João Cândido de
Muñoz,Patrício Ricardo
dc.subject.por.fl_str_mv Plant breeding
grain yield
popping expansion
topic Plant breeding
grain yield
popping expansion
description ABSTRACT Recurrent selection is a viable alternative for popcorn breeding. However, frequent verification of progress attained is required. The aim of this study was to estimate the genetic progress attained for popping expansion (PE) and grain yield (GY) after four cycles of recurrent selection and to compare this progress with the expected progress estimated at the end of each cycle while considering the genetic relationships between the progenies via univariate and multivariate mixed-model approaches. To estimate the genetic parameters and gains from indirect selection, cycles 1, 2, 3, and 4 of a UFLA population were used. To estimate the genetic gains achieved, the following cycles were used: UFLA (original) and cycles 0, 1, 2, 3, and 4, evaluated in three environments. The multivariate approach provided more accurate estimates than did the univariate approach. There was genetic gain for PE in the recurrent selection program. In contrast, gain was not observed for GY using the different estimation strategies.
publishDate 2018
dc.date.none.fl_str_mv 2018-03-01
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=S1413-70542018000200159
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542018000200159
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1413-70542018422016817
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 Editora da UFLA
publisher.none.fl_str_mv Editora da UFLA
dc.source.none.fl_str_mv Ciência e Agrotecnologia v.42 n.2 2018
reponame:Ciência e Agrotecnologia (Online)
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Ciência e Agrotecnologia (Online)
collection Ciência e Agrotecnologia (Online)
repository.name.fl_str_mv Ciência e Agrotecnologia (Online) - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv ||renpaiva@dbi.ufla.br|| editora@editora.ufla.br
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