Fuzzy modeling of the risk of cacao moniliasis occurrence in Bahia state, Brazil

Detalhes bibliográficos
Autor(a) principal: Almeida, Samira L. H. de [UNESP]
Data de Publicação: 2020
Outros Autores: Silva, Samuel de A., Lima, Juliao S. de S., Rosas, Jorge T. F., Capelini, Vinicius A.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1590/1807-1929/agriambi.v24n4p225-230
http://hdl.handle.net/11449/196699
Resumo: This work aimed to determine potential areas for the establishment of cocoa moniliasis in Bahia state, Brazil, by means of fuzzy logic, based on historical datasets of temperature and air relative humidity, available for 519 measurement points distributed throughout the state of Bahia. The data were initially submitted to a descriptive statistical analysis. The spatial variability was determined through geostatistical analysis, followed by interpolation to map the spatial-temporal structure dependence of the phenomenon. Simulations of continuous pixel-to-pixel classification of variables were performed using fuzzy mapping to model the climatic risk of disease establishment. The exponential fuzzy model was applied to temperature data, while the linear model was used for air relative humidity data. The potential areas were defined for each month, using data of temperature and air relative humidity. The fuzzy models used allowed for modeling of the climatic risk of cocoa moniliasis establishment. A large area of the state is at high risk of disease, thus requiring mitigating measures to avoid the pathogen's introduction and dissemination.
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spelling Fuzzy modeling of the risk of cacao moniliasis occurrence in Bahia state, BrazilMoniliophthora roreriTheobroma cacaoclimate changegeostatisticsprecision phytopathologyThis work aimed to determine potential areas for the establishment of cocoa moniliasis in Bahia state, Brazil, by means of fuzzy logic, based on historical datasets of temperature and air relative humidity, available for 519 measurement points distributed throughout the state of Bahia. The data were initially submitted to a descriptive statistical analysis. The spatial variability was determined through geostatistical analysis, followed by interpolation to map the spatial-temporal structure dependence of the phenomenon. Simulations of continuous pixel-to-pixel classification of variables were performed using fuzzy mapping to model the climatic risk of disease establishment. The exponential fuzzy model was applied to temperature data, while the linear model was used for air relative humidity data. The potential areas were defined for each month, using data of temperature and air relative humidity. The fuzzy models used allowed for modeling of the climatic risk of cocoa moniliasis establishment. A large area of the state is at high risk of disease, thus requiring mitigating measures to avoid the pathogen's introduction and dissemination.Univ Estadual Paulista, Fac Ciencias Agr & Vet, Dept Engn Rural, Jaboticabal, SP, BrazilUniv Fed Espirito Santo, Dept Engn Rural, Alegre, ES, BrazilUniv Sao Paulo, Escola Super Agr Luiz de Queiroz, Dept Solos & Nutr Plantas, Piracicaba, SP, BrazilUniv Estadual Paulista, Fac Ciencias Agr & Vet, Dept Engn Rural, Jaboticabal, SP, BrazilUniv Federal Campina GrandeUniversidade Estadual Paulista (Unesp)Universidade Federal do Espírito Santo (UFES)Universidade de São Paulo (USP)Almeida, Samira L. H. de [UNESP]Silva, Samuel de A.Lima, Juliao S. de S.Rosas, Jorge T. F.Capelini, Vinicius A.2020-12-10T19:53:23Z2020-12-10T19:53:23Z2020-04-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article225-230application/pdfhttp://dx.doi.org/10.1590/1807-1929/agriambi.v24n4p225-230Revista Brasileira De Engenharia Agricola E Ambiental. Campina Grande Pb: Univ Federal Campina Grande, v. 24, n. 4, p. 225-230, 2020.1415-4366http://hdl.handle.net/11449/19669910.1590/1807-1929/agriambi.v24n4p225-230S1415-43662020000400225WOS:000520404800002S1415-43662020000400225.pdfWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengRevista Brasileira De Engenharia Agricola E Ambientalinfo:eu-repo/semantics/openAccess2023-10-08T06:09:10Zoai:repositorio.unesp.br:11449/196699Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-10-08T06:09:10Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Fuzzy modeling of the risk of cacao moniliasis occurrence in Bahia state, Brazil
title Fuzzy modeling of the risk of cacao moniliasis occurrence in Bahia state, Brazil
spellingShingle Fuzzy modeling of the risk of cacao moniliasis occurrence in Bahia state, Brazil
Almeida, Samira L. H. de [UNESP]
Moniliophthora roreri
Theobroma cacao
climate change
geostatistics
precision phytopathology
title_short Fuzzy modeling of the risk of cacao moniliasis occurrence in Bahia state, Brazil
title_full Fuzzy modeling of the risk of cacao moniliasis occurrence in Bahia state, Brazil
title_fullStr Fuzzy modeling of the risk of cacao moniliasis occurrence in Bahia state, Brazil
title_full_unstemmed Fuzzy modeling of the risk of cacao moniliasis occurrence in Bahia state, Brazil
title_sort Fuzzy modeling of the risk of cacao moniliasis occurrence in Bahia state, Brazil
author Almeida, Samira L. H. de [UNESP]
author_facet Almeida, Samira L. H. de [UNESP]
Silva, Samuel de A.
Lima, Juliao S. de S.
Rosas, Jorge T. F.
Capelini, Vinicius A.
author_role author
author2 Silva, Samuel de A.
Lima, Juliao S. de S.
Rosas, Jorge T. F.
Capelini, Vinicius A.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Universidade Federal do Espírito Santo (UFES)
Universidade de São Paulo (USP)
dc.contributor.author.fl_str_mv Almeida, Samira L. H. de [UNESP]
Silva, Samuel de A.
Lima, Juliao S. de S.
Rosas, Jorge T. F.
Capelini, Vinicius A.
dc.subject.por.fl_str_mv Moniliophthora roreri
Theobroma cacao
climate change
geostatistics
precision phytopathology
topic Moniliophthora roreri
Theobroma cacao
climate change
geostatistics
precision phytopathology
description This work aimed to determine potential areas for the establishment of cocoa moniliasis in Bahia state, Brazil, by means of fuzzy logic, based on historical datasets of temperature and air relative humidity, available for 519 measurement points distributed throughout the state of Bahia. The data were initially submitted to a descriptive statistical analysis. The spatial variability was determined through geostatistical analysis, followed by interpolation to map the spatial-temporal structure dependence of the phenomenon. Simulations of continuous pixel-to-pixel classification of variables were performed using fuzzy mapping to model the climatic risk of disease establishment. The exponential fuzzy model was applied to temperature data, while the linear model was used for air relative humidity data. The potential areas were defined for each month, using data of temperature and air relative humidity. The fuzzy models used allowed for modeling of the climatic risk of cocoa moniliasis establishment. A large area of the state is at high risk of disease, thus requiring mitigating measures to avoid the pathogen's introduction and dissemination.
publishDate 2020
dc.date.none.fl_str_mv 2020-12-10T19:53:23Z
2020-12-10T19:53:23Z
2020-04-01
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/10.1590/1807-1929/agriambi.v24n4p225-230
Revista Brasileira De Engenharia Agricola E Ambiental. Campina Grande Pb: Univ Federal Campina Grande, v. 24, n. 4, p. 225-230, 2020.
1415-4366
http://hdl.handle.net/11449/196699
10.1590/1807-1929/agriambi.v24n4p225-230
S1415-43662020000400225
WOS:000520404800002
S1415-43662020000400225.pdf
url http://dx.doi.org/10.1590/1807-1929/agriambi.v24n4p225-230
http://hdl.handle.net/11449/196699
identifier_str_mv Revista Brasileira De Engenharia Agricola E Ambiental. Campina Grande Pb: Univ Federal Campina Grande, v. 24, n. 4, p. 225-230, 2020.
1415-4366
10.1590/1807-1929/agriambi.v24n4p225-230
S1415-43662020000400225
WOS:000520404800002
S1415-43662020000400225.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Revista Brasileira De Engenharia Agricola E Ambiental
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 225-230
application/pdf
dc.publisher.none.fl_str_mv Univ Federal Campina Grande
publisher.none.fl_str_mv Univ Federal Campina Grande
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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