Modelling the dynamics of Spodoptera frugiperda infestation in maize production with control strategies

The ongoing demand for maize is driven by its nutritional value, ability to meet the food re quirements of a increasing world population, its impact on ensuring a stable food supply, and the growing international investments in ethanol as a renewable fuel source. Nevertheless, the invasion and extensive spread of the Spodoptera frugiperda pest cause substantial losses in maize yields, resulting in a diminished standard of living and an economic downturn for those involved in maize production. This study formulates the systems of differential equations to simulate the dynamics of a model encompassing both Spodoptera frugiperda and maize biomass. The model considers the presence of predators and the application of best farming practices. The model demonstrates six equilibrium points, and they are locally asymptotically stable provided that the essential conditions are satisfied. Global stability for models’ equi libria are established by Lyapunov functions. Latin Hypercube Sampling (LHS) and Partial Rank Correlation Coefficient (PRCC) multivariate analysis were utilized to pinpoint the sen sitive parameters that influence the pest. The predators attack rate and best farming practices was the most sensitive parameter, when increases maize biomass increases while pest popu lation significantly dencreases. Numerical simulations indicate that, during the initial phases, combining natural enemies with best farming practices emerges as a successful intervention by directly decreasing the pest population and fostering sustainable pest control. The optimal control strategy which combines farming education campaign and predator selection awere ness on eggs and larval reduced pest infestation in early stages. Thus, to control the pest, we recommend that more efforts be directed to reduce eggs and larval populations and improving farming methods through education campaign.