Use of an index based on best linear unbiased prediction value for the selection of superior papaya lines for multiple traits
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Bragantia |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052022000100240 |
Resumo: | ABSTRACT Selection indexes represent the real efforts of a breeding program to obtain genetic gains for various significant traits simultaneously. As such, this study selected superior F5 lines by combined selection for fruit quality using an index based on predicted genotypic values via residual or restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) methodology weighted by agronomic weights. To do so, 97 F5 papaya lines obtained by the single seed descent method, resulting from the biparental cross between the genotypes JS-12 and Sekati, were evaluated for the main traits related to fruit quality. Results of the analysis of deviance and the genetic parameters indicated that there was genetic variability, indicating possible success in the selection process. Based on the selection index, 29 lines were selected as superior for fruit quality with ‘Formosa’ pattern. The strategy of the selection index combining BLUPs of multiple traits of interest associated with agronomic weights allows maximizing genetic progress while discarding less-promising genotypes. |
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Use of an index based on best linear unbiased prediction value for the selection of superior papaya lines for multiple traitssegregating populationmixed modelsdigital phenotypingfruit marketgenetic breedingABSTRACT Selection indexes represent the real efforts of a breeding program to obtain genetic gains for various significant traits simultaneously. As such, this study selected superior F5 lines by combined selection for fruit quality using an index based on predicted genotypic values via residual or restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) methodology weighted by agronomic weights. To do so, 97 F5 papaya lines obtained by the single seed descent method, resulting from the biparental cross between the genotypes JS-12 and Sekati, were evaluated for the main traits related to fruit quality. Results of the analysis of deviance and the genetic parameters indicated that there was genetic variability, indicating possible success in the selection process. Based on the selection index, 29 lines were selected as superior for fruit quality with ‘Formosa’ pattern. The strategy of the selection index combining BLUPs of multiple traits of interest associated with agronomic weights allows maximizing genetic progress while discarding less-promising genotypes.Instituto Agronômico de Campinas2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052022000100240Bragantia v.81 2022reponame:Bragantiainstname:Instituto Agronômico de Campinas (IAC)instacron:IAC10.1590/1678-4499.20220040info:eu-repo/semantics/openAccessSantana,Josefa Grasiela SilvaRamos,Helaine Christine CancelaSanta-Catarina,RenatoVettorazzi,Julio Cesar FiorioMiranda,Daniel PereiraPirovani,Adriana Azevedo VimercatiPoltronieri,Tathianne Pastana de SousaAzevedo,Alinne Oliveira NunesDuarte,Rafaela PereiraBohry,DieimesPereira,Messias Gonzagaeng2022-11-24T00:00:00Zoai:scielo:S0006-87052022000100240Revistahttps://www.scielo.br/j/brag/https://old.scielo.br/oai/scielo-oai.phpbragantia@iac.sp.gov.br||bragantia@iac.sp.gov.br1678-44990006-8705opendoar:2022-11-24T00:00Bragantia - Instituto Agronômico de Campinas (IAC)false |
dc.title.none.fl_str_mv |
Use of an index based on best linear unbiased prediction value for the selection of superior papaya lines for multiple traits |
title |
Use of an index based on best linear unbiased prediction value for the selection of superior papaya lines for multiple traits |
spellingShingle |
Use of an index based on best linear unbiased prediction value for the selection of superior papaya lines for multiple traits Santana,Josefa Grasiela Silva segregating population mixed models digital phenotyping fruit market genetic breeding |
title_short |
Use of an index based on best linear unbiased prediction value for the selection of superior papaya lines for multiple traits |
title_full |
Use of an index based on best linear unbiased prediction value for the selection of superior papaya lines for multiple traits |
title_fullStr |
Use of an index based on best linear unbiased prediction value for the selection of superior papaya lines for multiple traits |
title_full_unstemmed |
Use of an index based on best linear unbiased prediction value for the selection of superior papaya lines for multiple traits |
title_sort |
Use of an index based on best linear unbiased prediction value for the selection of superior papaya lines for multiple traits |
author |
Santana,Josefa Grasiela Silva |
author_facet |
Santana,Josefa Grasiela Silva Ramos,Helaine Christine Cancela Santa-Catarina,Renato Vettorazzi,Julio Cesar Fiorio Miranda,Daniel Pereira Pirovani,Adriana Azevedo Vimercati Poltronieri,Tathianne Pastana de Sousa Azevedo,Alinne Oliveira Nunes Duarte,Rafaela Pereira Bohry,Dieimes Pereira,Messias Gonzaga |
author_role |
author |
author2 |
Ramos,Helaine Christine Cancela Santa-Catarina,Renato Vettorazzi,Julio Cesar Fiorio Miranda,Daniel Pereira Pirovani,Adriana Azevedo Vimercati Poltronieri,Tathianne Pastana de Sousa Azevedo,Alinne Oliveira Nunes Duarte,Rafaela Pereira Bohry,Dieimes Pereira,Messias Gonzaga |
author2_role |
author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Santana,Josefa Grasiela Silva Ramos,Helaine Christine Cancela Santa-Catarina,Renato Vettorazzi,Julio Cesar Fiorio Miranda,Daniel Pereira Pirovani,Adriana Azevedo Vimercati Poltronieri,Tathianne Pastana de Sousa Azevedo,Alinne Oliveira Nunes Duarte,Rafaela Pereira Bohry,Dieimes Pereira,Messias Gonzaga |
dc.subject.por.fl_str_mv |
segregating population mixed models digital phenotyping fruit market genetic breeding |
topic |
segregating population mixed models digital phenotyping fruit market genetic breeding |
description |
ABSTRACT Selection indexes represent the real efforts of a breeding program to obtain genetic gains for various significant traits simultaneously. As such, this study selected superior F5 lines by combined selection for fruit quality using an index based on predicted genotypic values via residual or restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) methodology weighted by agronomic weights. To do so, 97 F5 papaya lines obtained by the single seed descent method, resulting from the biparental cross between the genotypes JS-12 and Sekati, were evaluated for the main traits related to fruit quality. Results of the analysis of deviance and the genetic parameters indicated that there was genetic variability, indicating possible success in the selection process. Based on the selection index, 29 lines were selected as superior for fruit quality with ‘Formosa’ pattern. The strategy of the selection index combining BLUPs of multiple traits of interest associated with agronomic weights allows maximizing genetic progress while discarding less-promising genotypes. |
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=S0006-87052022000100240 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052022000100240 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1678-4499.20220040 |
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 |
Instituto Agronômico de Campinas |
publisher.none.fl_str_mv |
Instituto Agronômico de Campinas |
dc.source.none.fl_str_mv |
Bragantia v.81 2022 reponame:Bragantia instname:Instituto Agronômico de Campinas (IAC) instacron:IAC |
instname_str |
Instituto Agronômico de Campinas (IAC) |
instacron_str |
IAC |
institution |
IAC |
reponame_str |
Bragantia |
collection |
Bragantia |
repository.name.fl_str_mv |
Bragantia - Instituto Agronômico de Campinas (IAC) |
repository.mail.fl_str_mv |
bragantia@iac.sp.gov.br||bragantia@iac.sp.gov.br |
_version_ |
1754193308456845312 |