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

Detalhes bibliográficos
Autor(a) principal: Almeida,Samira L. H. de
Data de Publicação: 2020
Outros Autores: Silva,Samuel de A., Lima,Julião S. de S., Rosas,Jorge T. F., Capelini,Vinicius A.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Brasileira de Engenharia Agrícola e Ambiental (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662020000400225
Resumo: ABSTRACT 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 phytopathologyABSTRACT 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.Departamento de Engenharia Agrícola - UFCG2020-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662020000400225Revista Brasileira de Engenharia Agrícola e Ambiental v.24 n.4 2020reponame:Revista Brasileira de Engenharia Agrícola e Ambiental (Online)instname:Universidade Federal de Campina Grande (UFCG)instacron:UFCG10.1590/1807-1929/agriambi.v24n4p225-230info:eu-repo/semantics/openAccessAlmeida,Samira L. H. deSilva,Samuel de A.Lima,Julião S. de S.Rosas,Jorge T. F.Capelini,Vinicius A.eng2020-03-12T00:00:00Zoai:scielo:S1415-43662020000400225Revistahttp://www.scielo.br/rbeaaPUBhttps://old.scielo.br/oai/scielo-oai.php||agriambi@agriambi.com.br1807-19291415-4366opendoar:2020-03-12T00:00Revista Brasileira de Engenharia Agrícola e Ambiental (Online) - Universidade Federal de Campina Grande (UFCG)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
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
author_facet Almeida,Samira L. H. de
Silva,Samuel de A.
Lima,Julião S. de S.
Rosas,Jorge T. F.
Capelini,Vinicius A.
author_role author
author2 Silva,Samuel de A.
Lima,Julião S. de S.
Rosas,Jorge T. F.
Capelini,Vinicius A.
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Almeida,Samira L. H. de
Silva,Samuel de A.
Lima,Julião 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 ABSTRACT 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 2020-04-01
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dc.language.iso.fl_str_mv eng
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dc.relation.none.fl_str_mv 10.1590/1807-1929/agriambi.v24n4p225-230
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dc.publisher.none.fl_str_mv Departamento de Engenharia Agrícola - UFCG
publisher.none.fl_str_mv Departamento de Engenharia Agrícola - UFCG
dc.source.none.fl_str_mv Revista Brasileira de Engenharia Agrícola e Ambiental v.24 n.4 2020
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instname_str Universidade Federal de Campina Grande (UFCG)
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