Characterization of tomato generations according to a three-way data analysis

Detalhes bibliográficos
Autor(a) principal: Medico,Ana Paula Del
Data de Publicação: 2020
Outros Autores: Cabodevila,Victoria Guadalupe, Vitelleschi,Maria Susana, Pratta,Guillermo Raúl
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Bragantia
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052020000100008
Resumo: ABSTRACT Availability of a three-way data analysis to characterize two consecutive tomato (Solanum lycopersicum) generations is necessary to continue a plant breeding program with less uncertainty. The aim of this work was to analyze tomato fruit quality from F2 and F3 populations by two three-way data analysis: multiple factorial analysis (MFA) and generalized procrustes analysis (GPA). These techniques have the same main objective, searching for a common structure, but they achieve it in different ways. This work evaluated 18 tomato genotypes, represented by individual plants in F2 and selfed families in F3. The same quantitative traits related to fruit quality were measured in both generations. The first two axes of the MFA represented 51.0% of the total variability. From the representation of the genotypes on these axes, traits differing from one generation to another were identified. The first two axes of the GPA represented 56.4% of the total variability. This analysis provided a table of analysis of variance (ANOVA), which corroborated the graphic and analytical interpretations of the MFA, a technique that provides the composition of the obtained axes. The comparison between the results obtained from these techniques indicated that both MFA and GPA allowed the detection of genotypes with discrepancies between the two generations. The MFA technique presented the advantage of studying graphically and analytically the nature and degree of phenotypic differences among genotypes in both generations, while the GPA complemented the analysis with an ANOVA, achieving the quantification of statistical significances for the discrepancies or similarities between them.
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spelling Characterization of tomato generations according to a three-way data analysisthree-way data analysismultiple factorial analysisgeneralized procrustes analysisplant breedingplant genetic resourcesABSTRACT Availability of a three-way data analysis to characterize two consecutive tomato (Solanum lycopersicum) generations is necessary to continue a plant breeding program with less uncertainty. The aim of this work was to analyze tomato fruit quality from F2 and F3 populations by two three-way data analysis: multiple factorial analysis (MFA) and generalized procrustes analysis (GPA). These techniques have the same main objective, searching for a common structure, but they achieve it in different ways. This work evaluated 18 tomato genotypes, represented by individual plants in F2 and selfed families in F3. The same quantitative traits related to fruit quality were measured in both generations. The first two axes of the MFA represented 51.0% of the total variability. From the representation of the genotypes on these axes, traits differing from one generation to another were identified. The first two axes of the GPA represented 56.4% of the total variability. This analysis provided a table of analysis of variance (ANOVA), which corroborated the graphic and analytical interpretations of the MFA, a technique that provides the composition of the obtained axes. The comparison between the results obtained from these techniques indicated that both MFA and GPA allowed the detection of genotypes with discrepancies between the two generations. The MFA technique presented the advantage of studying graphically and analytically the nature and degree of phenotypic differences among genotypes in both generations, while the GPA complemented the analysis with an ANOVA, achieving the quantification of statistical significances for the discrepancies or similarities between them.Instituto Agronômico de Campinas2020-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052020000100008Bragantia v.79 n.1 2020reponame:Bragantiainstname:Instituto Agronômico de Campinas (IAC)instacron:IAC10.1590/1678-4499.20190047info:eu-repo/semantics/openAccessMedico,Ana Paula DelCabodevila,Victoria GuadalupeVitelleschi,Maria SusanaPratta,Guillermo Raúleng2020-04-28T00:00:00Zoai:scielo:S0006-87052020000100008Revistahttps://www.scielo.br/j/brag/https://old.scielo.br/oai/scielo-oai.phpbragantia@iac.sp.gov.br||bragantia@iac.sp.gov.br1678-44990006-8705opendoar:2020-04-28T00:00Bragantia - Instituto Agronômico de Campinas (IAC)false
dc.title.none.fl_str_mv Characterization of tomato generations according to a three-way data analysis
title Characterization of tomato generations according to a three-way data analysis
spellingShingle Characterization of tomato generations according to a three-way data analysis
Medico,Ana Paula Del
three-way data analysis
multiple factorial analysis
generalized procrustes analysis
plant breeding
plant genetic resources
title_short Characterization of tomato generations according to a three-way data analysis
title_full Characterization of tomato generations according to a three-way data analysis
title_fullStr Characterization of tomato generations according to a three-way data analysis
title_full_unstemmed Characterization of tomato generations according to a three-way data analysis
title_sort Characterization of tomato generations according to a three-way data analysis
author Medico,Ana Paula Del
author_facet Medico,Ana Paula Del
Cabodevila,Victoria Guadalupe
Vitelleschi,Maria Susana
Pratta,Guillermo Raúl
author_role author
author2 Cabodevila,Victoria Guadalupe
Vitelleschi,Maria Susana
Pratta,Guillermo Raúl
author2_role author
author
author
dc.contributor.author.fl_str_mv Medico,Ana Paula Del
Cabodevila,Victoria Guadalupe
Vitelleschi,Maria Susana
Pratta,Guillermo Raúl
dc.subject.por.fl_str_mv three-way data analysis
multiple factorial analysis
generalized procrustes analysis
plant breeding
plant genetic resources
topic three-way data analysis
multiple factorial analysis
generalized procrustes analysis
plant breeding
plant genetic resources
description ABSTRACT Availability of a three-way data analysis to characterize two consecutive tomato (Solanum lycopersicum) generations is necessary to continue a plant breeding program with less uncertainty. The aim of this work was to analyze tomato fruit quality from F2 and F3 populations by two three-way data analysis: multiple factorial analysis (MFA) and generalized procrustes analysis (GPA). These techniques have the same main objective, searching for a common structure, but they achieve it in different ways. This work evaluated 18 tomato genotypes, represented by individual plants in F2 and selfed families in F3. The same quantitative traits related to fruit quality were measured in both generations. The first two axes of the MFA represented 51.0% of the total variability. From the representation of the genotypes on these axes, traits differing from one generation to another were identified. The first two axes of the GPA represented 56.4% of the total variability. This analysis provided a table of analysis of variance (ANOVA), which corroborated the graphic and analytical interpretations of the MFA, a technique that provides the composition of the obtained axes. The comparison between the results obtained from these techniques indicated that both MFA and GPA allowed the detection of genotypes with discrepancies between the two generations. The MFA technique presented the advantage of studying graphically and analytically the nature and degree of phenotypic differences among genotypes in both generations, while the GPA complemented the analysis with an ANOVA, achieving the quantification of statistical significances for the discrepancies or similarities between them.
publishDate 2020
dc.date.none.fl_str_mv 2020-03-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052020000100008
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1678-4499.20190047
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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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.79 n.1 2020
reponame:Bragantia
instname:Instituto Agronômico de Campinas (IAC)
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instname_str Instituto Agronômico de Campinas (IAC)
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collection Bragantia
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