Epidemiological models for plant diseases are very important for prediction, control and estimation of the infection incidence. Such models are fundamentally characterized by the influence of some meteorological variables. In this paper, we design a new model to predict incidence of infection by pathogens in function of the mixed effects of temperature and wetness. These deeply influential parameters are estimated and adjusted with regards to the disease caused by various infectious pathogens. In addition, we show that it is primordial to introduce bound constraints on the model’s location parameters. This allows to perform a more accurate minimization of the sum of residuals. The proposed optimization procedure is based on the trust-region method. Our methodological approach is simple and easy to implement for the prediction and / or control of diverse plant infections. In order to show its efficiency, our model is validated and compared for different plant diseases adapted from several studies published in the literature. As a matter of comparison, the results of goodness of fit demonstrate that our new model outperforms the other reported models.
Plant disease Epidemic Models Temperature and wetness duration Fitting Nonlinear optimization
Primary Language | English |
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Subjects | Engineering |
Journal Section | Articles |
Authors | |
Publication Date | December 10, 2019 |
Published in Issue | Year 2019Volume: 8 |