Papaya recombinant inbred lines selection by image-based phenotyping
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 expensi...
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doaj-6368f30b7ce3420fa25afefd0a66db2e2020-11-25T00:54:25ZengUniversidade de São PauloScientia Agricola1678-992X75320821510.1590/1678-992x-2016-0482S0103-90162018000300208Papaya recombinant inbred lines selection by image-based phenotypingDiego Fernando Marmolejo CortesRenato Santa-CatarinaAlinne Oliveira Nunes AzevedoTathianne Pastana de Sousa PoltronieriJulio Cesar Fiorio VettorazziNádia Fernandes MoreiraGeraldo Antônio FerreguettiHelaine Christine Cancela RamosAlexandre Pio VianaMessias Gonzaga PereiraABSTRACT: 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.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162018000300208&lng=en&tlng=enCarica papayadigital phenotypinggenetic gainsgenetic parameters |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Diego Fernando Marmolejo Cortes Renato Santa-Catarina Alinne Oliveira Nunes Azevedo Tathianne Pastana de Sousa Poltronieri Julio Cesar Fiorio Vettorazzi Nádia Fernandes Moreira Geraldo Antônio Ferreguetti Helaine Christine Cancela Ramos Alexandre Pio Viana Messias Gonzaga Pereira |
spellingShingle |
Diego Fernando Marmolejo Cortes Renato Santa-Catarina Alinne Oliveira Nunes Azevedo Tathianne Pastana de Sousa Poltronieri Julio Cesar Fiorio Vettorazzi Nádia Fernandes Moreira Geraldo Antônio Ferreguetti Helaine Christine Cancela Ramos Alexandre Pio Viana Messias Gonzaga Pereira Papaya recombinant inbred lines selection by image-based phenotyping Scientia Agricola Carica papaya digital phenotyping genetic gains genetic parameters |
author_facet |
Diego Fernando Marmolejo Cortes Renato Santa-Catarina Alinne Oliveira Nunes Azevedo Tathianne Pastana de Sousa Poltronieri Julio Cesar Fiorio Vettorazzi Nádia Fernandes Moreira Geraldo Antônio Ferreguetti Helaine Christine Cancela Ramos Alexandre Pio Viana Messias Gonzaga Pereira |
author_sort |
Diego Fernando Marmolejo Cortes |
title |
Papaya recombinant inbred lines selection by image-based phenotyping |
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 |
publisher |
Universidade de São Paulo |
series |
Scientia Agricola |
issn |
1678-992X |
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. |
topic |
Carica papaya digital phenotyping genetic gains genetic parameters |
url |
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162018000300208&lng=en&tlng=en |
work_keys_str_mv |
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