Papaya recombinant inbred lines selection by image-based phenotyping
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Scientia Agrícola (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162018000300208 |
Resumo: | ABSTRACT: The selection of superior Carica papaya (L) genotypes depends on the availability of genetic variability and on the favorable and simultaneous response of the genotypes to those traits of most interest. However, manual phenotyping (MP) demands intensive labor, is time-consuming and expensive. The aim of the current study is to access the efficiency of image-based phenotyping (IBP) in estimating genetic parameters and in selecting F4 recombinant inbred lines. The genetic parameters and values were estimated in accordance with the REML/BLUB procedure and combined selection using the selection index based on standardized genetic values. The majority of traits accessed through IBP showed experimental coefficients of variation similar to those found through MP. Both methodologies showed genetic parameters of similar magnitude, indicating expressive genetic variability between lines in the traits accessed in this study. The same superior lines were indicated in both methodologies and expressive genetic gains obtained through the lines were selected for all traits. IBP performance was similar to that of MP with respect to the estimates of breeding-relevant traits such as commercial fruits and yield. Thus, IBP showed efficient phenotypic assessment, as well as selective accuracy in accessing genetic variability and genetic gains, when it was compared to MP. Since IBP is far less dependent on labor, it is expected to be incorporated into the routine of papaya breeding programs as a way of increasing the number of accessed lines and, consequently, increasing genetic gains. |
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Scientia Agrícola (Online) |
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Papaya recombinant inbred lines selection by image-based phenotypingCarica papayadigital phenotypinggenetic gainsgenetic parametersABSTRACT: The selection of superior Carica papaya (L) genotypes depends on the availability of genetic variability and on the favorable and simultaneous response of the genotypes to those traits of most interest. However, manual phenotyping (MP) demands intensive labor, is time-consuming and expensive. The aim of the current study is to access the efficiency of image-based phenotyping (IBP) in estimating genetic parameters and in selecting F4 recombinant inbred lines. The genetic parameters and values were estimated in accordance with the REML/BLUB procedure and combined selection using the selection index based on standardized genetic values. The majority of traits accessed through IBP showed experimental coefficients of variation similar to those found through MP. Both methodologies showed genetic parameters of similar magnitude, indicating expressive genetic variability between lines in the traits accessed in this study. The same superior lines were indicated in both methodologies and expressive genetic gains obtained through the lines were selected for all traits. IBP performance was similar to that of MP with respect to the estimates of breeding-relevant traits such as commercial fruits and yield. Thus, IBP showed efficient phenotypic assessment, as well as selective accuracy in accessing genetic variability and genetic gains, when it was compared to MP. Since IBP is far less dependent on labor, it is expected to be incorporated into the routine of papaya breeding programs as a way of increasing the number of accessed lines and, consequently, increasing genetic gains.Escola Superior de Agricultura "Luiz de Queiroz"2018-05-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162018000300208Scientia Agricola v.75 n.3 2018reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USP10.1590/1678-992x-2016-0482info:eu-repo/semantics/openAccessCortes,Diego Fernando MarmolejoSanta-Catarina,RenatoAzevedo,Alinne Oliveira NunesPoltronieri,Tathianne Pastana de SousaVettorazzi,Julio Cesar FiorioMoreira,Nádia FernandesFerreguetti,Geraldo AntônioRamos,Helaine Christine CancelaViana,Alexandre PioPereira,Messias Gonzagaeng2018-01-29T00:00:00Zoai:scielo:S0103-90162018000300208Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2018-01-29T00:00Scientia Agrícola (Online) - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Papaya recombinant inbred lines selection by image-based phenotyping |
title |
Papaya recombinant inbred lines selection by image-based phenotyping |
spellingShingle |
Papaya recombinant inbred lines selection by image-based phenotyping Cortes,Diego Fernando Marmolejo Carica papaya digital phenotyping genetic gains genetic parameters |
title_short |
Papaya recombinant inbred lines selection by image-based phenotyping |
title_full |
Papaya recombinant inbred lines selection by image-based phenotyping |
title_fullStr |
Papaya recombinant inbred lines selection by image-based phenotyping |
title_full_unstemmed |
Papaya recombinant inbred lines selection by image-based phenotyping |
title_sort |
Papaya recombinant inbred lines selection by image-based phenotyping |
author |
Cortes,Diego Fernando Marmolejo |
author_facet |
Cortes,Diego Fernando Marmolejo Santa-Catarina,Renato Azevedo,Alinne Oliveira Nunes Poltronieri,Tathianne Pastana de Sousa Vettorazzi,Julio Cesar Fiorio Moreira,Nádia Fernandes Ferreguetti,Geraldo Antônio Ramos,Helaine Christine Cancela Viana,Alexandre Pio Pereira,Messias Gonzaga |
author_role |
author |
author2 |
Santa-Catarina,Renato Azevedo,Alinne Oliveira Nunes Poltronieri,Tathianne Pastana de Sousa Vettorazzi,Julio Cesar Fiorio Moreira,Nádia Fernandes Ferreguetti,Geraldo Antônio Ramos,Helaine Christine Cancela Viana,Alexandre Pio Pereira,Messias Gonzaga |
author2_role |
author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Cortes,Diego Fernando Marmolejo Santa-Catarina,Renato Azevedo,Alinne Oliveira Nunes Poltronieri,Tathianne Pastana de Sousa Vettorazzi,Julio Cesar Fiorio Moreira,Nádia Fernandes Ferreguetti,Geraldo Antônio Ramos,Helaine Christine Cancela Viana,Alexandre Pio Pereira,Messias Gonzaga |
dc.subject.por.fl_str_mv |
Carica papaya digital phenotyping genetic gains genetic parameters |
topic |
Carica papaya digital phenotyping genetic gains genetic parameters |
description |
ABSTRACT: The selection of superior Carica papaya (L) genotypes depends on the availability of genetic variability and on the favorable and simultaneous response of the genotypes to those traits of most interest. However, manual phenotyping (MP) demands intensive labor, is time-consuming and expensive. The aim of the current study is to access the efficiency of image-based phenotyping (IBP) in estimating genetic parameters and in selecting F4 recombinant inbred lines. The genetic parameters and values were estimated in accordance with the REML/BLUB procedure and combined selection using the selection index based on standardized genetic values. The majority of traits accessed through IBP showed experimental coefficients of variation similar to those found through MP. Both methodologies showed genetic parameters of similar magnitude, indicating expressive genetic variability between lines in the traits accessed in this study. The same superior lines were indicated in both methodologies and expressive genetic gains obtained through the lines were selected for all traits. IBP performance was similar to that of MP with respect to the estimates of breeding-relevant traits such as commercial fruits and yield. Thus, IBP showed efficient phenotypic assessment, as well as selective accuracy in accessing genetic variability and genetic gains, when it was compared to MP. Since IBP is far less dependent on labor, it is expected to be incorporated into the routine of papaya breeding programs as a way of increasing the number of accessed lines and, consequently, increasing genetic gains. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-05-01 |
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=S0103-90162018000300208 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162018000300208 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1678-992x-2016-0482 |
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.75 n.3 2018 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 |
_version_ |
1748936464704471040 |