Genetic improvement of silage maize: predicting genetic gain using selection indexes and best linear unbiased prediction

Detalhes bibliográficos
Autor(a) principal: Crevelari,Jocarla Ambrosim
Data de Publicação: 2019
Outros Autores: Pereira,Messias Gonzaga, Azevedo,Flávio Henrique Vidal, Vieira,Ricardo Augusto Mendonça
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista ciência agronômica (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902019000200197
Resumo: ABSTRACT The objective of this study was to evaluate four selection indexes and best linear unbiased prediction (BLUP) for predicting genetic gain in maize hybrids used for silage. The genetic gain was compared between four selection indexes and BLUP. Nineteen topcross hybrids and five controls were evaluated using a completely randomized block design with four replicates in two areas located in Campos dos Goytacazes and Itaocara, Rio de Janeiro, Brazil, in the growing season 2013-2014. Plant height, first ear height, average stem diameter, grain yield at the silage stage, and green mass yield were evaluated. The genetic gain was predicted using the selection indexes proposed by Pesek and Baker, Smith and Hazel, Mulamba and Mock, Willians, and BLUP. The index of Mulamba and Mock provided higher gain estimates for selecting hybrids. BLUP was efficient and selected hybrids with higher performance than hybrids obtained using the four selection indexes. Hybrids UENF-2205, UENF-2208, UENF-2209, and UENF-2210 presented better performance, indicating the high potential of these dent hybrids for silage production in the north and northwest regions of Rio de Janeiro.
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spelling Genetic improvement of silage maize: predicting genetic gain using selection indexes and best linear unbiased predictionTopcrossesTesterHybridsYieldABSTRACT The objective of this study was to evaluate four selection indexes and best linear unbiased prediction (BLUP) for predicting genetic gain in maize hybrids used for silage. The genetic gain was compared between four selection indexes and BLUP. Nineteen topcross hybrids and five controls were evaluated using a completely randomized block design with four replicates in two areas located in Campos dos Goytacazes and Itaocara, Rio de Janeiro, Brazil, in the growing season 2013-2014. Plant height, first ear height, average stem diameter, grain yield at the silage stage, and green mass yield were evaluated. The genetic gain was predicted using the selection indexes proposed by Pesek and Baker, Smith and Hazel, Mulamba and Mock, Willians, and BLUP. The index of Mulamba and Mock provided higher gain estimates for selecting hybrids. BLUP was efficient and selected hybrids with higher performance than hybrids obtained using the four selection indexes. Hybrids UENF-2205, UENF-2208, UENF-2209, and UENF-2210 presented better performance, indicating the high potential of these dent hybrids for silage production in the north and northwest regions of Rio de Janeiro.Universidade Federal do Ceará2019-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902019000200197Revista Ciência Agronômica v.50 n.2 2019reponame:Revista ciência agronômica (Online)instname:Universidade Federal do Ceará (UFC)instacron:UFC10.5935/1806-6690.20190023info:eu-repo/semantics/openAccessCrevelari,Jocarla AmbrosimPereira,Messias GonzagaAzevedo,Flávio Henrique VidalVieira,Ricardo Augusto Mendonçaeng2019-01-23T00:00:00Zoai:scielo:S1806-66902019000200197Revistahttp://www.ccarevista.ufc.br/PUBhttps://old.scielo.br/oai/scielo-oai.php||alekdutra@ufc.br|| ccarev@ufc.br1806-66900045-6888opendoar:2019-01-23T00:00Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC)false
dc.title.none.fl_str_mv Genetic improvement of silage maize: predicting genetic gain using selection indexes and best linear unbiased prediction
title Genetic improvement of silage maize: predicting genetic gain using selection indexes and best linear unbiased prediction
spellingShingle Genetic improvement of silage maize: predicting genetic gain using selection indexes and best linear unbiased prediction
Crevelari,Jocarla Ambrosim
Topcrosses
Tester
Hybrids
Yield
title_short Genetic improvement of silage maize: predicting genetic gain using selection indexes and best linear unbiased prediction
title_full Genetic improvement of silage maize: predicting genetic gain using selection indexes and best linear unbiased prediction
title_fullStr Genetic improvement of silage maize: predicting genetic gain using selection indexes and best linear unbiased prediction
title_full_unstemmed Genetic improvement of silage maize: predicting genetic gain using selection indexes and best linear unbiased prediction
title_sort Genetic improvement of silage maize: predicting genetic gain using selection indexes and best linear unbiased prediction
author Crevelari,Jocarla Ambrosim
author_facet Crevelari,Jocarla Ambrosim
Pereira,Messias Gonzaga
Azevedo,Flávio Henrique Vidal
Vieira,Ricardo Augusto Mendonça
author_role author
author2 Pereira,Messias Gonzaga
Azevedo,Flávio Henrique Vidal
Vieira,Ricardo Augusto Mendonça
author2_role author
author
author
dc.contributor.author.fl_str_mv Crevelari,Jocarla Ambrosim
Pereira,Messias Gonzaga
Azevedo,Flávio Henrique Vidal
Vieira,Ricardo Augusto Mendonça
dc.subject.por.fl_str_mv Topcrosses
Tester
Hybrids
Yield
topic Topcrosses
Tester
Hybrids
Yield
description ABSTRACT The objective of this study was to evaluate four selection indexes and best linear unbiased prediction (BLUP) for predicting genetic gain in maize hybrids used for silage. The genetic gain was compared between four selection indexes and BLUP. Nineteen topcross hybrids and five controls were evaluated using a completely randomized block design with four replicates in two areas located in Campos dos Goytacazes and Itaocara, Rio de Janeiro, Brazil, in the growing season 2013-2014. Plant height, first ear height, average stem diameter, grain yield at the silage stage, and green mass yield were evaluated. The genetic gain was predicted using the selection indexes proposed by Pesek and Baker, Smith and Hazel, Mulamba and Mock, Willians, and BLUP. The index of Mulamba and Mock provided higher gain estimates for selecting hybrids. BLUP was efficient and selected hybrids with higher performance than hybrids obtained using the four selection indexes. Hybrids UENF-2205, UENF-2208, UENF-2209, and UENF-2210 presented better performance, indicating the high potential of these dent hybrids for silage production in the north and northwest regions of Rio de Janeiro.
publishDate 2019
dc.date.none.fl_str_mv 2019-06-01
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=S1806-66902019000200197
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902019000200197
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.5935/1806-6690.20190023
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 Universidade Federal do Ceará
publisher.none.fl_str_mv Universidade Federal do Ceará
dc.source.none.fl_str_mv Revista Ciência Agronômica v.50 n.2 2019
reponame:Revista ciência agronômica (Online)
instname:Universidade Federal do Ceará (UFC)
instacron:UFC
instname_str Universidade Federal do Ceará (UFC)
instacron_str UFC
institution UFC
reponame_str Revista ciência agronômica (Online)
collection Revista ciência agronômica (Online)
repository.name.fl_str_mv Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC)
repository.mail.fl_str_mv ||alekdutra@ufc.br|| ccarev@ufc.br
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