A data-driven stage-structured host-parasitoid model for optimizing Trichogramma interventions against soybean pod borer (Leguminivora glycinivorella) outbreaks

The soybean pod borer (Leguminivora glycinivorella) poses a severe threat to global soybean production.In this study, we developed a stage-structured host-parasitoid dynamic model that explicitly couples the holometabolous life cycle of the pest with the obligate egg-parasitism mechanism of Trichogramma wasps. Utilizing field monitoring data from Changchun, Jilin Province, key biological parameters were rigorously estimated via the Markov Chain Monte Carlo (MCMC) method.This calibration facilitated the establishment of a precise Economic Injury Level ($Q_{EIL}$) of 0.0389 individuals/$m^2$, based solely on the destructive larval stage. Through theoretical and numerical analyses of different intervention scenarios, we identified an optimal continuous release rate ($C^* = 2.645$) that efficiently suppresses the outbreak without causing wasteful parasitoid accumulation. Furthermore, simulations demonstrate that a 5-day impulsive release interval provides the optimal balance between strict pest suppression and field operational costs. This study bridges the gap between theoretical population dynamics and applied agricultural management, providing a directly applicable mathematical decision-making tool for the precise biological control of crop pests.