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Major yield losses in maize fields are being caused by a variety of foliar diseases. Early detection of these diseases can lower the possibility of extensive crop damage and assist farmers with setting up the ideal treatment schedule. Starting early and performing preventative steps before it's too late are crucial. Therefore, we investigate a model of maize foliar disease that captures the dynamics between the maize population and the pathogen population by employing the fractional derivative in the Caputo sense. In this study, we first compute the model's basic reproduction number with the control terms included, and then perform a sensitivity analysis. Second, we give the existence and uniqueness properties of this model. In order to achieve the intended goal, that is to predict the future of the disease and prevent its spread we examine this model using optimal control theory. The fractional optimal control structure is applied for the first time to the maize leaf disease model considered in this study. The results obtained from this application demonstrate the potential effectiveness and robustness of fractional optimal control strategies and make a significant contribution to the existing literature in this area. Numerical simulations are then carried out using the forward-backward sweep method. The results clearly illustrate the effectiveness and importance of the proposed combined control strategy in completely preventing the disease.
Evirgen et al. (Tue,) studied this question.