Optimal control and multitrophic physiologically-based models: The binomial for successful decision support systems in insect pest management.

backgroundAgroecosystems can be viewed as dynamic systems that receive inputs through agronomic practices, generate yield as an output, and whose economic profitability depends on balancing production costs and revenues. Pests and pathogens reduce crop yield and often require growers to apply additional inputs, thereby increasing production costs. According to integrated pest management (IPM), however, maximising yield while minimising costs does not mean eradicating bio-aggressors from the field but corresponds to maintain pest populations below economic thresholds. This objective can be achieved by identifying the optimal timing for control actions through decision support systems (DSSs) as, from a mathematical perspective, IPM can be formulated as an optimal control problem: the objective function accounts for economic returns and production costs, including treatments, and is driven by plant-pest dynamics.

resultsWe introduced the essential concepts of an optimal control problem that faithfully fits the IPM guidelines. Multitrophic models account the interaction between plant and pest, while the effect of control actions relates to the objective function of the problem: the total economic income of the farm depends on the number of treatments and the timing of their application. Simulations showed both that lower pest population does not correspond to the maximum profit and that a good timing in the application can have almost the same effect of repeated treatments.

conclusionThis study revises the concept of DSS through optimal control applied to pest populations, pointing out that multitrophic models are fundamental to fit the IPM guidelines of economic and environmental sustainability. © 2026 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.