Fuzzy logic applied to simultaneous selection of sweet potato genotypes

Detalhes bibliográficos
Autor(a) principal: Ana Clara Gonçalves Fernandes
Data de Publicação: 2022
Outros Autores: Alcinei Mistico Azevedo, Nermy Ribeiro Valadares, Clovis Henrique Oliveira Rodrigues, Orlando Gonçalves Brito, Valter Carvalho de Andrade Júnior, Ignacio Aspiazú
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFMG
Texto Completo: http://dx.doi.org/10.1590/s0102-0536-20220108
http://hdl.handle.net/1843/59704
https://orcid.org/0000-0002-8161-8130
https://orcid.org/0000-0001-5196-0851
https://orcid.org/0000-0001-7854-8111
https://orcid.org/0000-0001-6756-7835
https://orcid.org/0000-0001-6238-1644
https://orcid.org/0000-0002-5010-7725
https://orcid.org/0000-0002-0042-3324
Resumo: The objective of this work was to perform simultaneous selection in sweet potato genotypes and to verify the efficiency of fuzzy systems when compared to the Mulamba & Mock (MM) method. The experiment was carried out in randomized blocks, with 24 sweet potato genotypes, four replications and ten plants per plot. The breeding values were obtained by the mixed model methodology (REML/BLUP), and then the MM index and the gains obtained by the developed fuzzy systems were estimated. There was a predominance of environmental effects over genotypic effects for all traits. These estimates suggest an expressive contribution of the environment for these traits and, consequently, greater difficulty for genetic improvement. Through this, the fuzzy systems stood out in relation to the MM method, as they presented superior selection gains for characters related to human and animal food. The genotypes with potential for human and animal food selected by the fuzzy system were: UFVJM07, UFVJM05, UFVJM09, UFVJM40, UFVJM01, UFVJM25, UFVJM15. The fuzzy logic was efficient in the simultaneous selection of sweet potato genotypes, allowing the selection of plants similar to the desirable ideotype than the MM method.
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spelling 2023-10-19T15:09:48Z2023-10-19T15:09:48Z20224016370http://dx.doi.org/10.1590/s0102-0536-2022010801020536http://hdl.handle.net/1843/59704https://orcid.org/0000-0002-8161-8130https://orcid.org/0000-0001-5196-0851https://orcid.org/0000-0001-7854-8111https://orcid.org/0000-0001-6756-7835https://orcid.org/0000-0001-6238-1644https://orcid.org/0000-0002-5010-7725https://orcid.org/0000-0002-0042-3324The objective of this work was to perform simultaneous selection in sweet potato genotypes and to verify the efficiency of fuzzy systems when compared to the Mulamba & Mock (MM) method. The experiment was carried out in randomized blocks, with 24 sweet potato genotypes, four replications and ten plants per plot. The breeding values were obtained by the mixed model methodology (REML/BLUP), and then the MM index and the gains obtained by the developed fuzzy systems were estimated. There was a predominance of environmental effects over genotypic effects for all traits. These estimates suggest an expressive contribution of the environment for these traits and, consequently, greater difficulty for genetic improvement. Through this, the fuzzy systems stood out in relation to the MM method, as they presented superior selection gains for characters related to human and animal food. The genotypes with potential for human and animal food selected by the fuzzy system were: UFVJM07, UFVJM05, UFVJM09, UFVJM40, UFVJM01, UFVJM25, UFVJM15. The fuzzy logic was efficient in the simultaneous selection of sweet potato genotypes, allowing the selection of plants similar to the desirable ideotype than the MM method.O objetivo deste trabalho foi realizar a seleção simultânea em genótipos de batata-doce e verificar a eficiência de sistemas fuzzy quando comparados ao método Mulamba & Mock (MM). O experimento foi em blocos casualizados, com 24 genótipos de batata-doce, quatro repetições e dez plantas por parcela. Os valores genéticos foram obtidos pela metodologia dos modelos mistos (REML/BLUP), e posteriormente estimados o índice MM e os ganhos obtidos pelos sistemas fuzzy desenvolvidos. Houve predomínio de efeitos ambientais sobre os efeitos genotípicos para todas as características. Essas estimativas sugerem expressiva contribuição do ambiente para esses caracteres e, consequentemente, maior dificuldade para o melhoramento genético. Através disso, os sistemas fuzzy se destacaram em relação ao método de MM, já que apresentaram ganhos de seleção superiores para os caracteres relacionados à alimentação humana e animal. Os genótipos com potencial para alimentação humana e animal selecionados pelo sistema fuzzy foram: UFVJM07, UFVJM05, UFVJM09, UFVJM40, UFVJM01, UFVJM25, UFVJM15. A lógica fuzzy foi eficiente na seleção simultânea de genótipos de batata-doce, permitindo a seleção de plantas semelhantes ao ideótipo desejável do que o método MM.CNPq - Conselho Nacional de Desenvolvimento Científico e TecnológicoFAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas GeraisCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorengUniversidade Federal de Minas GeraisUFMGBrasilICA - INSTITUTO DE CIÊNCIAS AGRÁRIASHorticultura BrasileiraBatata-doceSeleção de plantas -- Melhoramento genéticoInteligência computacionalFuzzy logic applied to simultaneous selection of sweet potato genotypesLógica fuzzy aplicada à seleção simultânea de genótipos de batata-doceinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://www.scielo.br/j/hb/a/WnfRMz4th7q3pFGxrcvMy9C/?format=pdf&lang=enAna Clara Gonçalves FernandesAlcinei Mistico AzevedoNermy Ribeiro ValadaresClovis Henrique Oliveira RodriguesOrlando Gonçalves BritoValter Carvalho de Andrade JúniorIgnacio Aspiazúinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGLICENSELicense.txtLicense.txttext/plain; charset=utf-82042https://repositorio.ufmg.br/bitstream/1843/59704/1/License.txtfa505098d172de0bc8864fc1287ffe22MD51ORIGINALFuzzy logic is a powerful tool for the automation of milk classification.pdfFuzzy logic is a powerful tool for the automation of milk classification.pdfapplication/pdf418918https://repositorio.ufmg.br/bitstream/1843/59704/2/Fuzzy%20logic%20is%20a%20powerful%20tool%20for%20the%20automation%20of%20milk%20classification.pdf54c856f338bea5b5d2a168fb3ee13aaeMD521843/597042023-10-19 16:32:59.819oai:repositorio.ufmg.br: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Repositório de PublicaçõesPUBhttps://repositorio.ufmg.br/oaiopendoar:2023-10-19T19:32:59Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
dc.title.pt_BR.fl_str_mv Fuzzy logic applied to simultaneous selection of sweet potato genotypes
dc.title.alternative.pt_BR.fl_str_mv Lógica fuzzy aplicada à seleção simultânea de genótipos de batata-doce
title Fuzzy logic applied to simultaneous selection of sweet potato genotypes
spellingShingle Fuzzy logic applied to simultaneous selection of sweet potato genotypes
Ana Clara Gonçalves Fernandes
Batata-doce
Seleção de plantas -- Melhoramento genético
Inteligência computacional
title_short Fuzzy logic applied to simultaneous selection of sweet potato genotypes
title_full Fuzzy logic applied to simultaneous selection of sweet potato genotypes
title_fullStr Fuzzy logic applied to simultaneous selection of sweet potato genotypes
title_full_unstemmed Fuzzy logic applied to simultaneous selection of sweet potato genotypes
title_sort Fuzzy logic applied to simultaneous selection of sweet potato genotypes
author Ana Clara Gonçalves Fernandes
author_facet Ana Clara Gonçalves Fernandes
Alcinei Mistico Azevedo
Nermy Ribeiro Valadares
Clovis Henrique Oliveira Rodrigues
Orlando Gonçalves Brito
Valter Carvalho de Andrade Júnior
Ignacio Aspiazú
author_role author
author2 Alcinei Mistico Azevedo
Nermy Ribeiro Valadares
Clovis Henrique Oliveira Rodrigues
Orlando Gonçalves Brito
Valter Carvalho de Andrade Júnior
Ignacio Aspiazú
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Ana Clara Gonçalves Fernandes
Alcinei Mistico Azevedo
Nermy Ribeiro Valadares
Clovis Henrique Oliveira Rodrigues
Orlando Gonçalves Brito
Valter Carvalho de Andrade Júnior
Ignacio Aspiazú
dc.subject.other.pt_BR.fl_str_mv Batata-doce
Seleção de plantas -- Melhoramento genético
Inteligência computacional
topic Batata-doce
Seleção de plantas -- Melhoramento genético
Inteligência computacional
description The objective of this work was to perform simultaneous selection in sweet potato genotypes and to verify the efficiency of fuzzy systems when compared to the Mulamba & Mock (MM) method. The experiment was carried out in randomized blocks, with 24 sweet potato genotypes, four replications and ten plants per plot. The breeding values were obtained by the mixed model methodology (REML/BLUP), and then the MM index and the gains obtained by the developed fuzzy systems were estimated. There was a predominance of environmental effects over genotypic effects for all traits. These estimates suggest an expressive contribution of the environment for these traits and, consequently, greater difficulty for genetic improvement. Through this, the fuzzy systems stood out in relation to the MM method, as they presented superior selection gains for characters related to human and animal food. The genotypes with potential for human and animal food selected by the fuzzy system were: UFVJM07, UFVJM05, UFVJM09, UFVJM40, UFVJM01, UFVJM25, UFVJM15. The fuzzy logic was efficient in the simultaneous selection of sweet potato genotypes, allowing the selection of plants similar to the desirable ideotype than the MM method.
publishDate 2022
dc.date.issued.fl_str_mv 2022
dc.date.accessioned.fl_str_mv 2023-10-19T15:09:48Z
dc.date.available.fl_str_mv 2023-10-19T15:09:48Z
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://hdl.handle.net/1843/59704
dc.identifier.doi.pt_BR.fl_str_mv http://dx.doi.org/10.1590/s0102-0536-20220108
dc.identifier.issn.pt_BR.fl_str_mv 01020536
dc.identifier.orcid.pt_BR.fl_str_mv https://orcid.org/0000-0002-8161-8130
https://orcid.org/0000-0001-5196-0851
https://orcid.org/0000-0001-7854-8111
https://orcid.org/0000-0001-6756-7835
https://orcid.org/0000-0001-6238-1644
https://orcid.org/0000-0002-5010-7725
https://orcid.org/0000-0002-0042-3324
url http://dx.doi.org/10.1590/s0102-0536-20220108
http://hdl.handle.net/1843/59704
https://orcid.org/0000-0002-8161-8130
https://orcid.org/0000-0001-5196-0851
https://orcid.org/0000-0001-7854-8111
https://orcid.org/0000-0001-6756-7835
https://orcid.org/0000-0001-6238-1644
https://orcid.org/0000-0002-5010-7725
https://orcid.org/0000-0002-0042-3324
identifier_str_mv 01020536
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv Horticultura Brasileira
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Universidade Federal de Minas Gerais
dc.publisher.initials.fl_str_mv UFMG
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv ICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS
publisher.none.fl_str_mv Universidade Federal de Minas Gerais
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFMG
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