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Optimal control and multitrophic physiologically-based models: The binomial for successful decision support systems
Luca Rossini1, Ouassim Benhamouche2, Emanuele Garone2
1School of Agriculture, Policy and Development, University of Reading, Reading, UK.
Pest Management Science
|June 1, 2026
Summary
Integrated pest management (IPM) uses optimal control to balance farm profit and pest levels. Strategic timing of interventions, not just reducing pests, maximizes economic returns, aligning with sustainable agroecosystem management.
Area of Science:
- Agricultural Science
- Ecology
- Mathematical Modeling
Background:
- Agroecosystems are dynamic systems balancing inputs, outputs, and profitability.
- Pests and pathogens decrease crop yield and increase production costs.
- Integrated Pest Management (IPM) aims to maintain pest populations below economic thresholds.
Purpose of the Study:
- To formulate IPM as an optimal control problem using mathematical models.
- To develop decision support systems (DSSs) for optimal pest control timing.
- To integrate economic returns and production costs within pest management strategies.
Main Methods:
- Formulating IPM as an optimal control problem.
- Utilizing multitrophic models to represent plant-pest interactions.
- Simulating pest population dynamics and control actions.
Main Results:
- Optimal control accurately reflects IPM guidelines.
- Lower pest populations do not always equate to maximum farm profit.
- Strategic timing of control applications can be as effective as repeated treatments.
Conclusions:
- Decision support systems (DSSs) for pest management should incorporate optimal control.
- Multitrophic models are essential for aligning IPM with economic and environmental sustainability.
- This approach optimizes farm profitability while managing pest populations effectively.
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