Genetic progress in popcorn recurrent selection by a multivariate mixed-model approach
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Ciência e Agrotecnologia (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542018000200159 |
Resumo: | 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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Ciência e Agrotecnologia (Online) |
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|
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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:2022-11-22T16:31:34.483553Ciência e Agrotecnologia (Online) - Universidade Federal de Lavras (UFLA)true |
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 |
_version_ |
1799874970724073472 |