Optimal alarm system applied in coffee rust
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Semina. Ciências Agrárias (Online) |
Texto Completo: | https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/12968 |
Resumo: | Alarm systems have very great utility in detecting and warning of catastrophes. This methodology was applied via TARSO model with Bayesian estimation, serving as a forecasting mechanism for coffee rust disease. The coffee culture is very susceptible to this disease causing several records of incidence in most cultivated crops. Researches involving this limiting factor for production are intense and frequent, indicating environmental factors as responsible for the epidemics spread, which does not occur if these factors are not favorable. The fitting type used by the a posteriori probability, allows the system to be updated each time point. The methodology was applied to the rust index series in the presence of the average temperature series. Thus, it is possible to verify the alarm resulted or in a high catastrophe detection in points at which the catastrophe has not occurred, or in the low detections if the point was already in the catastrophe state. |
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Optimal alarm system applied in coffee rustSistema de alarme ótimo aplicado na ferrugem do caféRustBayesian inferenceTARSO modelThreshold.FerrugemInferência bayesianaModelo TARSOLimiar.Ciências Agrárias IAlarm systems have very great utility in detecting and warning of catastrophes. This methodology was applied via TARSO model with Bayesian estimation, serving as a forecasting mechanism for coffee rust disease. The coffee culture is very susceptible to this disease causing several records of incidence in most cultivated crops. Researches involving this limiting factor for production are intense and frequent, indicating environmental factors as responsible for the epidemics spread, which does not occur if these factors are not favorable. The fitting type used by the a posteriori probability, allows the system to be updated each time point. The methodology was applied to the rust index series in the presence of the average temperature series. Thus, it is possible to verify the alarm resulted or in a high catastrophe detection in points at which the catastrophe has not occurred, or in the low detections if the point was already in the catastrophe state. Os sistemas de alarme ótimos têm tido grande utilidade na detecção e advertência de ocorrência de catástrofes. Essa metodologia foi aplicada via modelo TARSO com ajuste bayesiano, servindo como mais um mecanismo de previsão para a doença ferrugem do café. A cultura cafeeira é muito suscetível ao ataque dessa doença, existindo registros de incidência na maioria das lavouras cultivadas. Pesquisas envolvendo esse fator limitante para a produção são intensas e frequentes, indicando os fatores ambientais como responsáveis pelo alastramento de epidemias, que não ocorrem se esses fatores não forem favoráveis. O tipo de ajuste utilizado por meio das probabilidades a posteriori, permitem que o sistema seja atualizado a cada ponto do tempo. A metodologia foi aplicada à série de índice de ferrugem na presença da série de temperatura média sendo possível verificar que o alarme resultou em uma detecção de catástrofe alta em pontos nos quais a catástrofe ainda não ocorreu e em detecções baixas se o ponto já estava no estado de catástrofe. UEL2014-04-28info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPesquisa Empírica de Campoapplication/pdfhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/1296810.5433/1679-0359.2014v35n2p647Semina: Ciências Agrárias; Vol. 35 No. 2 (2014); 647-658Semina: Ciências Agrárias; v. 35 n. 2 (2014); 647-6581679-03591676-546Xreponame:Semina. Ciências Agrárias (Online)instname:Universidade Estadual de Londrina (UEL)instacron:UELporhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/12968/pdf_262Gonçalves, Luciene ResendeSáfadi, ThelmaOliveira, Anderson Castro Soares deinfo:eu-repo/semantics/openAccess2015-11-19T18:35:51Zoai:ojs.pkp.sfu.ca:article/12968Revistahttp://www.uel.br/revistas/uel/index.php/semagrariasPUBhttps://ojs.uel.br/revistas/uel/index.php/semagrarias/oaisemina.agrarias@uel.br1679-03591676-546Xopendoar:2015-11-19T18:35:51Semina. Ciências Agrárias (Online) - Universidade Estadual de Londrina (UEL)false |
dc.title.none.fl_str_mv |
Optimal alarm system applied in coffee rust Sistema de alarme ótimo aplicado na ferrugem do café |
title |
Optimal alarm system applied in coffee rust |
spellingShingle |
Optimal alarm system applied in coffee rust Gonçalves, Luciene Resende Rust Bayesian inference TARSO model Threshold. Ferrugem Inferência bayesiana Modelo TARSO Limiar. Ciências Agrárias I |
title_short |
Optimal alarm system applied in coffee rust |
title_full |
Optimal alarm system applied in coffee rust |
title_fullStr |
Optimal alarm system applied in coffee rust |
title_full_unstemmed |
Optimal alarm system applied in coffee rust |
title_sort |
Optimal alarm system applied in coffee rust |
author |
Gonçalves, Luciene Resende |
author_facet |
Gonçalves, Luciene Resende Sáfadi, Thelma Oliveira, Anderson Castro Soares de |
author_role |
author |
author2 |
Sáfadi, Thelma Oliveira, Anderson Castro Soares de |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Gonçalves, Luciene Resende Sáfadi, Thelma Oliveira, Anderson Castro Soares de |
dc.subject.por.fl_str_mv |
Rust Bayesian inference TARSO model Threshold. Ferrugem Inferência bayesiana Modelo TARSO Limiar. Ciências Agrárias I |
topic |
Rust Bayesian inference TARSO model Threshold. Ferrugem Inferência bayesiana Modelo TARSO Limiar. Ciências Agrárias I |
description |
Alarm systems have very great utility in detecting and warning of catastrophes. This methodology was applied via TARSO model with Bayesian estimation, serving as a forecasting mechanism for coffee rust disease. The coffee culture is very susceptible to this disease causing several records of incidence in most cultivated crops. Researches involving this limiting factor for production are intense and frequent, indicating environmental factors as responsible for the epidemics spread, which does not occur if these factors are not favorable. The fitting type used by the a posteriori probability, allows the system to be updated each time point. The methodology was applied to the rust index series in the presence of the average temperature series. Thus, it is possible to verify the alarm resulted or in a high catastrophe detection in points at which the catastrophe has not occurred, or in the low detections if the point was already in the catastrophe state. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-04-28 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Pesquisa Empírica de Campo |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/12968 10.5433/1679-0359.2014v35n2p647 |
url |
https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/12968 |
identifier_str_mv |
10.5433/1679-0359.2014v35n2p647 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/12968/pdf_262 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
UEL |
publisher.none.fl_str_mv |
UEL |
dc.source.none.fl_str_mv |
Semina: Ciências Agrárias; Vol. 35 No. 2 (2014); 647-658 Semina: Ciências Agrárias; v. 35 n. 2 (2014); 647-658 1679-0359 1676-546X reponame:Semina. Ciências Agrárias (Online) instname:Universidade Estadual de Londrina (UEL) instacron:UEL |
instname_str |
Universidade Estadual de Londrina (UEL) |
instacron_str |
UEL |
institution |
UEL |
reponame_str |
Semina. Ciências Agrárias (Online) |
collection |
Semina. Ciências Agrárias (Online) |
repository.name.fl_str_mv |
Semina. Ciências Agrárias (Online) - Universidade Estadual de Londrina (UEL) |
repository.mail.fl_str_mv |
semina.agrarias@uel.br |
_version_ |
1799306067915571200 |