Fuzzy modeling of the risk of cacao moniliasis occurrence in Bahia state, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , |
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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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 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662020000400225 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662020000400225 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1807-1929/agriambi.v24n4p225-230 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
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 reponame:Revista Brasileira de Engenharia Agrícola e Ambiental (Online) instname:Universidade Federal de Campina Grande (UFCG) instacron:UFCG |
instname_str |
Universidade Federal de Campina Grande (UFCG) |
instacron_str |
UFCG |
institution |
UFCG |
reponame_str |
Revista Brasileira de Engenharia Agrícola e Ambiental (Online) |
collection |
Revista Brasileira de Engenharia Agrícola e Ambiental (Online) |
repository.name.fl_str_mv |
Revista Brasileira de Engenharia Agrícola e Ambiental (Online) - Universidade Federal de Campina Grande (UFCG) |
repository.mail.fl_str_mv |
||agriambi@agriambi.com.br |
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1750297687323836416 |