Fuzzy logic applied to simultaneous selection of sweet potato genotypes

Detalhes bibliográficos
Autor(a) principal: Fernandes, Ana Clara G.
Data de Publicação: 2022
Outros Autores: Azevedo, Alcinei M., Valadares, Nermy R., Rodrigues, Clóvis H. O., Brito, Orlando G., Andrade Júnior, Valter C. de, Aspiazú, Ignacio
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/50815
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 Fuzzy logic applied to simultaneous selection of sweet potato genotypesLógica fuzzy aplicada à seleção simultânea de genótipos de batata-doceIpomoea batatasSweet potato - Genetic improvementMultiple selectionComputational intelligenceBatata doce - Melhoramento genéticoSeleção múltiplaInteligência computacionalThe 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.Associação Brasileira de Horticultura2022-08-03T21:51:46Z2022-08-03T21:51:46Z2022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfFERNANDES, A. C. G. et al. Fuzzy logic applied to simultaneous selection of sweet potato genotypes. Horticultura Brasileira, Brasília, DF, v. 40, n. 1, p. 63-70, 2022. DOI: 10.1590/s0102-0536-20220108.http://repositorio.ufla.br/jspui/handle/1/50815Horticultura Brasileirareponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessFernandes, Ana Clara G.Azevedo, Alcinei M.Valadares, Nermy R.Rodrigues, Clóvis H. O.Brito, Orlando G.Andrade Júnior, Valter C. deAspiazú, Ignacioeng2023-05-26T18:55:44Zoai:localhost:1/50815Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2023-05-26T18:55:44Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Fuzzy logic applied to simultaneous selection of sweet potato genotypes
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
Fernandes, Ana Clara G.
Ipomoea batatas
Sweet potato - Genetic improvement
Multiple selection
Computational intelligence
Batata doce - Melhoramento genético
Seleção múltipla
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 Fernandes, Ana Clara G.
author_facet Fernandes, Ana Clara G.
Azevedo, Alcinei M.
Valadares, Nermy R.
Rodrigues, Clóvis H. O.
Brito, Orlando G.
Andrade Júnior, Valter C. de
Aspiazú, Ignacio
author_role author
author2 Azevedo, Alcinei M.
Valadares, Nermy R.
Rodrigues, Clóvis H. O.
Brito, Orlando G.
Andrade Júnior, Valter C. de
Aspiazú, Ignacio
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Fernandes, Ana Clara G.
Azevedo, Alcinei M.
Valadares, Nermy R.
Rodrigues, Clóvis H. O.
Brito, Orlando G.
Andrade Júnior, Valter C. de
Aspiazú, Ignacio
dc.subject.por.fl_str_mv Ipomoea batatas
Sweet potato - Genetic improvement
Multiple selection
Computational intelligence
Batata doce - Melhoramento genético
Seleção múltipla
Inteligência computacional
topic Ipomoea batatas
Sweet potato - Genetic improvement
Multiple selection
Computational intelligence
Batata doce - Melhoramento genético
Seleção múltipla
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.none.fl_str_mv 2022-08-03T21:51:46Z
2022-08-03T21:51:46Z
2022
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 FERNANDES, A. C. G. et al. Fuzzy logic applied to simultaneous selection of sweet potato genotypes. Horticultura Brasileira, Brasília, DF, v. 40, n. 1, p. 63-70, 2022. DOI: 10.1590/s0102-0536-20220108.
http://repositorio.ufla.br/jspui/handle/1/50815
identifier_str_mv FERNANDES, A. C. G. et al. Fuzzy logic applied to simultaneous selection of sweet potato genotypes. Horticultura Brasileira, Brasília, DF, v. 40, n. 1, p. 63-70, 2022. DOI: 10.1590/s0102-0536-20220108.
url http://repositorio.ufla.br/jspui/handle/1/50815
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Associação Brasileira de Horticultura
publisher.none.fl_str_mv Associação Brasileira de Horticultura
dc.source.none.fl_str_mv Horticultura Brasileira
reponame:Repositório Institucional da UFLA
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Repositório Institucional da UFLA
collection Repositório Institucional da UFLA
repository.name.fl_str_mv Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv nivaldo@ufla.br || repositorio.biblioteca@ufla.br
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