Abstract
ABSTRACT Late blight, caused by the oomycete Phytophthora infestans , significantly threatens tomato cultivation. In this work, we propose a modified SEIR‐type compartmental model with four epidemiological stages to capture the progression of the disease. A detailed mathematical analysis is carried out, establishing the model's positivity, boundedness, and the existence and stability of both disease‐free and endemic equilibria. Parameter estimation is performed using Bayesian inference via Markov chain Monte Carlo (MCMC), ensuring consistency with empirical data. We then formulate and solve an optimal control problem using Pontryagin's maximum principle, aiming to reduce disease prevalence and control‐related costs. The model incorporates a mobile app–based intervention strategy as a time‐dependent control variable. This study highlights the effectiveness of combining rigorous mathematical modeling, data‐driven calibration, and optimal control to inform the management of plant disease epidemics.
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Claims 1
Claim · model-written summary
Mathematical analysis established positivity, boundedness, and existence and stability of disease-free and endemic equilibria of the proposed model.
- Taxon
- tomato
Solanum lycopersicume0 - Outcome
- positivity, boundedness, and the existence and stabilitye1
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“significantly threatens tomato cultivation”
e1“positivity, boundedness, and the existence and stability of both disease”