Self-organizing maps in the study of genetic diversity among irrigated rice genotypes

Detalhes bibliográficos
Autor(a) principal: Santos, Iara Gonçalves dos
Data de Publicação: 2019
Outros Autores: Carneiro, Vinícius Quintão, Silva Junior, Antônio Carlos da, Cruz, Cosme Damião, Soares, Plínio César
Tipo de documento: Artigo
Idioma: eng
Título da fonte: LOCUS Repositório Institucional da UFV
Texto Completo: http://dx.doi.org/10.4025/actasciagron.v41i1.39803
http://www.locus.ufv.br/handle/123456789/25416
Resumo: This study presents self-organizing maps (SOM) as an alternative method to evaluate genetic diversity in plant breeding programs. Twenty-five genotypes were evaluated in two environments for 11 phenotypic traits. The genotypes were clustered according to the SOM technique, with variable topology and numbers of neurons. In addition to the SOM analysis, unweighted pair group method with arithmetic mean clustering (UPGMA) was performed to observe the behavior of the clustering when submitted to these techniques and to evaluate their complementarities. Genotype ordering according to SOM was consistent with UPGMA results, evidenced by the basic structure of UPGMA groups being preserved in each group of the maps. Regarding genotype arrangement and the group neighbors, maps involving five neurons presented inferior organization efficiency compared to the six-map arrangements in both environments. It was observed that the organization pattern among the rice genotypes evaluated by the maps was complementary to the UPGMA approach, as observed in all scenarios. It can be concluded that self-organizing maps have the potential to be useful for genetic diversity studies in breeding programs.
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spelling Santos, Iara Gonçalves dosCarneiro, Vinícius QuintãoSilva Junior, Antônio Carlos daCruz, Cosme DamiãoSoares, Plínio César2019-05-23T11:57:53Z2019-05-23T11:57:53Z2019-121807-8621http://dx.doi.org/10.4025/actasciagron.v41i1.39803http://www.locus.ufv.br/handle/123456789/25416This study presents self-organizing maps (SOM) as an alternative method to evaluate genetic diversity in plant breeding programs. Twenty-five genotypes were evaluated in two environments for 11 phenotypic traits. The genotypes were clustered according to the SOM technique, with variable topology and numbers of neurons. In addition to the SOM analysis, unweighted pair group method with arithmetic mean clustering (UPGMA) was performed to observe the behavior of the clustering when submitted to these techniques and to evaluate their complementarities. Genotype ordering according to SOM was consistent with UPGMA results, evidenced by the basic structure of UPGMA groups being preserved in each group of the maps. Regarding genotype arrangement and the group neighbors, maps involving five neurons presented inferior organization efficiency compared to the six-map arrangements in both environments. It was observed that the organization pattern among the rice genotypes evaluated by the maps was complementary to the UPGMA approach, as observed in all scenarios. It can be concluded that self-organizing maps have the potential to be useful for genetic diversity studies in breeding programs.engActa Scientiarum. Agronomyv. 41, e39803, p. 1-9, dez. 2019Oriza sativa L.Computational intelligenceClustering techniqueSomSelf-organizing maps in the study of genetic diversity among irrigated rice genotypesinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfinfo:eu-repo/semantics/openAccessreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALartigo.pdfartigo.pdfartigoapplication/pdf773713https://locus.ufv.br//bitstream/123456789/25416/1/artigo.pdff51868e1d1bbdec5cf264d02d9c5864cMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://locus.ufv.br//bitstream/123456789/25416/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52123456789/254162019-05-23 09:01:17.612oai:locus.ufv.br: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Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452019-05-23T12:01:17LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false
dc.title.en.fl_str_mv Self-organizing maps in the study of genetic diversity among irrigated rice genotypes
title Self-organizing maps in the study of genetic diversity among irrigated rice genotypes
spellingShingle Self-organizing maps in the study of genetic diversity among irrigated rice genotypes
Santos, Iara Gonçalves dos
Oriza sativa L.
Computational intelligence
Clustering technique
Som
title_short Self-organizing maps in the study of genetic diversity among irrigated rice genotypes
title_full Self-organizing maps in the study of genetic diversity among irrigated rice genotypes
title_fullStr Self-organizing maps in the study of genetic diversity among irrigated rice genotypes
title_full_unstemmed Self-organizing maps in the study of genetic diversity among irrigated rice genotypes
title_sort Self-organizing maps in the study of genetic diversity among irrigated rice genotypes
author Santos, Iara Gonçalves dos
author_facet Santos, Iara Gonçalves dos
Carneiro, Vinícius Quintão
Silva Junior, Antônio Carlos da
Cruz, Cosme Damião
Soares, Plínio César
author_role author
author2 Carneiro, Vinícius Quintão
Silva Junior, Antônio Carlos da
Cruz, Cosme Damião
Soares, Plínio César
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Santos, Iara Gonçalves dos
Carneiro, Vinícius Quintão
Silva Junior, Antônio Carlos da
Cruz, Cosme Damião
Soares, Plínio César
dc.subject.pt-BR.fl_str_mv Oriza sativa L.
Computational intelligence
Clustering technique
Som
topic Oriza sativa L.
Computational intelligence
Clustering technique
Som
description This study presents self-organizing maps (SOM) as an alternative method to evaluate genetic diversity in plant breeding programs. Twenty-five genotypes were evaluated in two environments for 11 phenotypic traits. The genotypes were clustered according to the SOM technique, with variable topology and numbers of neurons. In addition to the SOM analysis, unweighted pair group method with arithmetic mean clustering (UPGMA) was performed to observe the behavior of the clustering when submitted to these techniques and to evaluate their complementarities. Genotype ordering according to SOM was consistent with UPGMA results, evidenced by the basic structure of UPGMA groups being preserved in each group of the maps. Regarding genotype arrangement and the group neighbors, maps involving five neurons presented inferior organization efficiency compared to the six-map arrangements in both environments. It was observed that the organization pattern among the rice genotypes evaluated by the maps was complementary to the UPGMA approach, as observed in all scenarios. It can be concluded that self-organizing maps have the potential to be useful for genetic diversity studies in breeding programs.
publishDate 2019
dc.date.accessioned.fl_str_mv 2019-05-23T11:57:53Z
dc.date.available.fl_str_mv 2019-05-23T11:57:53Z
dc.date.issued.fl_str_mv 2019-12
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.4025/actasciagron.v41i1.39803
http://www.locus.ufv.br/handle/123456789/25416
dc.identifier.issn.none.fl_str_mv 1807-8621
identifier_str_mv 1807-8621
url http://dx.doi.org/10.4025/actasciagron.v41i1.39803
http://www.locus.ufv.br/handle/123456789/25416
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartofseries.pt-BR.fl_str_mv v. 41, e39803, p. 1-9, dez. 2019
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv Acta Scientiarum. Agronomy
publisher.none.fl_str_mv Acta Scientiarum. Agronomy
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