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Spatio-Temporal Modeling and Simulation of Asian Soybean Rust Based on Fuzzy System

Mato Grosso, Brazil, is the largest soy producer in the country. Asian Soy Rust is a disease that has already caused a lot of damage to Brazilian agribusiness. The plant matures prematurely, hindering the filling of the pod, drastically reducing productivity. It is caused by the Phakopsora pachyrhiz...

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Autores principales: Zagui, Nayara Longo Sartor, Krindges, André, Lotufo, Anna Diva Plasencia, Minussi, Carlos Roberto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8781736/
https://www.ncbi.nlm.nih.gov/pubmed/35062631
http://dx.doi.org/10.3390/s22020668
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author Zagui, Nayara Longo Sartor
Krindges, André
Lotufo, Anna Diva Plasencia
Minussi, Carlos Roberto
author_facet Zagui, Nayara Longo Sartor
Krindges, André
Lotufo, Anna Diva Plasencia
Minussi, Carlos Roberto
author_sort Zagui, Nayara Longo Sartor
collection PubMed
description Mato Grosso, Brazil, is the largest soy producer in the country. Asian Soy Rust is a disease that has already caused a lot of damage to Brazilian agribusiness. The plant matures prematurely, hindering the filling of the pod, drastically reducing productivity. It is caused by the Phakopsora pachyrhizi fungus. For a plant disease to establish itself, the presence of a pathogen, a susceptible plant, and favorable environmental conditions are necessary. This research developed a fuzzy system gathering these three variables as inputs, having as an output the vulnerability of the region to the disease. The presence of the pathogen was measured using a diffusion-advection equation appropriate to the problem. Some coefficients were based on the literature, others were measured by a fuzzy system and others were obtained by real data. From the mapping of producing properties, the locations where there are susceptible plants were established. And the favorable environmental conditions were also obtained from a fuzzy system, whose inputs were temperature and leaf wetness. Data provided by IBGE, INMET, and Antirust Consortium were used to fuel the model, and all treatments, tests, and simulations were carried out within the Matlab(®) environment. Although Asian Soybean Rust was the chosen disease here, the model was general in nature, so could be reproduced for any disease of plants with the same profile.
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spelling pubmed-87817362022-01-22 Spatio-Temporal Modeling and Simulation of Asian Soybean Rust Based on Fuzzy System Zagui, Nayara Longo Sartor Krindges, André Lotufo, Anna Diva Plasencia Minussi, Carlos Roberto Sensors (Basel) Article Mato Grosso, Brazil, is the largest soy producer in the country. Asian Soy Rust is a disease that has already caused a lot of damage to Brazilian agribusiness. The plant matures prematurely, hindering the filling of the pod, drastically reducing productivity. It is caused by the Phakopsora pachyrhizi fungus. For a plant disease to establish itself, the presence of a pathogen, a susceptible plant, and favorable environmental conditions are necessary. This research developed a fuzzy system gathering these three variables as inputs, having as an output the vulnerability of the region to the disease. The presence of the pathogen was measured using a diffusion-advection equation appropriate to the problem. Some coefficients were based on the literature, others were measured by a fuzzy system and others were obtained by real data. From the mapping of producing properties, the locations where there are susceptible plants were established. And the favorable environmental conditions were also obtained from a fuzzy system, whose inputs were temperature and leaf wetness. Data provided by IBGE, INMET, and Antirust Consortium were used to fuel the model, and all treatments, tests, and simulations were carried out within the Matlab(®) environment. Although Asian Soybean Rust was the chosen disease here, the model was general in nature, so could be reproduced for any disease of plants with the same profile. MDPI 2022-01-16 /pmc/articles/PMC8781736/ /pubmed/35062631 http://dx.doi.org/10.3390/s22020668 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zagui, Nayara Longo Sartor
Krindges, André
Lotufo, Anna Diva Plasencia
Minussi, Carlos Roberto
Spatio-Temporal Modeling and Simulation of Asian Soybean Rust Based on Fuzzy System
title Spatio-Temporal Modeling and Simulation of Asian Soybean Rust Based on Fuzzy System
title_full Spatio-Temporal Modeling and Simulation of Asian Soybean Rust Based on Fuzzy System
title_fullStr Spatio-Temporal Modeling and Simulation of Asian Soybean Rust Based on Fuzzy System
title_full_unstemmed Spatio-Temporal Modeling and Simulation of Asian Soybean Rust Based on Fuzzy System
title_short Spatio-Temporal Modeling and Simulation of Asian Soybean Rust Based on Fuzzy System
title_sort spatio-temporal modeling and simulation of asian soybean rust based on fuzzy system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8781736/
https://www.ncbi.nlm.nih.gov/pubmed/35062631
http://dx.doi.org/10.3390/s22020668
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