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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-8781736 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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