Selection to high productivity and stink bugs resistance by multivariate data analyses in soybean

Detalhes bibliográficos
Autor(a) principal: Bermudez,Felipe
Data de Publicação: 2020
Outros Autores: Pinheiro,José Baldin
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Bragantia
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052020000200250
Resumo: ABSTRACT Stink bugs that affect soybeans are responsible for significant losses in seed production, quality and germination potential, in addition to hindering the mechanized harvest. To develop insect resistant materials, the breeder can compile a selection index by factor analysis. Therefore, the objective of this work was to validate the use of factor analysis, by means of its estimated gains, for the selection of highly productive and stink bugs resistant genotypes in two soybean segregating populations. For this, the phenotypic evaluation was performed in the generation F2:3, in two distinct experiments, being the populations from the crosses between IAC-100 × PI 295952 and IAC-100 × PI 306712. The experiments were installed in an 18 × 9 alpha-lattice design, with three replicates for each population. Agronomic and resistance characters were evaluated. The factorial scores for each character were obtained for the creation of “supercharacters”. These were designed to check if the selection in the new characters could provide satisfactory simultaneous gains in the original characters. Subsequently, the analysis of variance was performed for all factors, in both populations. The F test showed the presence of variability among genotypes, allowing the selection of superior genotypes. None of the factors selected progenies with all the characters favorably, and their use was not interesting for both populations. With this, complementary studies should be performed with other selection indices in these populations.
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spelling Selection to high productivity and stink bugs resistance by multivariate data analyses in soybeanGlycine maxfactor analysisEuschistus herosPiezodorus guildiniiNezara viridulaABSTRACT Stink bugs that affect soybeans are responsible for significant losses in seed production, quality and germination potential, in addition to hindering the mechanized harvest. To develop insect resistant materials, the breeder can compile a selection index by factor analysis. Therefore, the objective of this work was to validate the use of factor analysis, by means of its estimated gains, for the selection of highly productive and stink bugs resistant genotypes in two soybean segregating populations. For this, the phenotypic evaluation was performed in the generation F2:3, in two distinct experiments, being the populations from the crosses between IAC-100 × PI 295952 and IAC-100 × PI 306712. The experiments were installed in an 18 × 9 alpha-lattice design, with three replicates for each population. Agronomic and resistance characters were evaluated. The factorial scores for each character were obtained for the creation of “supercharacters”. These were designed to check if the selection in the new characters could provide satisfactory simultaneous gains in the original characters. Subsequently, the analysis of variance was performed for all factors, in both populations. The F test showed the presence of variability among genotypes, allowing the selection of superior genotypes. None of the factors selected progenies with all the characters favorably, and their use was not interesting for both populations. With this, complementary studies should be performed with other selection indices in these populations.Instituto Agronômico de Campinas2020-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052020000200250Bragantia v.79 n.2 2020reponame:Bragantiainstname:Instituto Agronômico de Campinas (IAC)instacron:IAC10.1590/1678-4499.20190380info:eu-repo/semantics/openAccessBermudez,FelipePinheiro,José Baldineng2020-05-28T00:00:00Zoai:scielo:S0006-87052020000200250Revistahttps://www.scielo.br/j/brag/https://old.scielo.br/oai/scielo-oai.phpbragantia@iac.sp.gov.br||bragantia@iac.sp.gov.br1678-44990006-8705opendoar:2020-05-28T00:00Bragantia - Instituto Agronômico de Campinas (IAC)false
dc.title.none.fl_str_mv Selection to high productivity and stink bugs resistance by multivariate data analyses in soybean
title Selection to high productivity and stink bugs resistance by multivariate data analyses in soybean
spellingShingle Selection to high productivity and stink bugs resistance by multivariate data analyses in soybean
Bermudez,Felipe
Glycine max
factor analysis
Euschistus heros
Piezodorus guildinii
Nezara viridula
title_short Selection to high productivity and stink bugs resistance by multivariate data analyses in soybean
title_full Selection to high productivity and stink bugs resistance by multivariate data analyses in soybean
title_fullStr Selection to high productivity and stink bugs resistance by multivariate data analyses in soybean
title_full_unstemmed Selection to high productivity and stink bugs resistance by multivariate data analyses in soybean
title_sort Selection to high productivity and stink bugs resistance by multivariate data analyses in soybean
author Bermudez,Felipe
author_facet Bermudez,Felipe
Pinheiro,José Baldin
author_role author
author2 Pinheiro,José Baldin
author2_role author
dc.contributor.author.fl_str_mv Bermudez,Felipe
Pinheiro,José Baldin
dc.subject.por.fl_str_mv Glycine max
factor analysis
Euschistus heros
Piezodorus guildinii
Nezara viridula
topic Glycine max
factor analysis
Euschistus heros
Piezodorus guildinii
Nezara viridula
description ABSTRACT Stink bugs that affect soybeans are responsible for significant losses in seed production, quality and germination potential, in addition to hindering the mechanized harvest. To develop insect resistant materials, the breeder can compile a selection index by factor analysis. Therefore, the objective of this work was to validate the use of factor analysis, by means of its estimated gains, for the selection of highly productive and stink bugs resistant genotypes in two soybean segregating populations. For this, the phenotypic evaluation was performed in the generation F2:3, in two distinct experiments, being the populations from the crosses between IAC-100 × PI 295952 and IAC-100 × PI 306712. The experiments were installed in an 18 × 9 alpha-lattice design, with three replicates for each population. Agronomic and resistance characters were evaluated. The factorial scores for each character were obtained for the creation of “supercharacters”. These were designed to check if the selection in the new characters could provide satisfactory simultaneous gains in the original characters. Subsequently, the analysis of variance was performed for all factors, in both populations. The F test showed the presence of variability among genotypes, allowing the selection of superior genotypes. None of the factors selected progenies with all the characters favorably, and their use was not interesting for both populations. With this, complementary studies should be performed with other selection indices in these populations.
publishDate 2020
dc.date.none.fl_str_mv 2020-06-01
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=S0006-87052020000200250
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052020000200250
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1678-4499.20190380
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.79 n.2 2020
reponame:Bragantia
instname:Instituto Agronômico de Campinas (IAC)
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instname_str Instituto Agronômico de Campinas (IAC)
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repository.name.fl_str_mv Bragantia - Instituto Agronômico de Campinas (IAC)
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