This invention discloses an AI-driven method for precise control of the oriental fruit moth during its growth stages, belonging to the field of
crop pest and
disease control technology. Addressing the shortcomings of poor targeted control, extensive
pesticide application, and lack of precise decision-making and closed-
loop optimization in peach orchards in the Jiangsu and Zhejiang regions, this invention constructs a four-dimensional feature
library containing
crop, pest, environment, and control methods (each dimension labeled with
plant protection-related weights). Through a multimodal AI model fusing visual, sensor, and phenological data, it achieves precise determination of the oriental fruit moth throughout its entire growth stage (accuracy ≥95%). Using weighted
collaborative filtering and the NSGA-III multi-objective optimization
algorithm, it dynamically matches the
optimal combination of
microemulsion pesticides,
physical control, and auxins, meeting the targets of control
efficacy ≥85%,
pesticide reduction ≥30%, cost ≤15 yuan / mu, and
phytotoxicity rate ≤0.5%. A closed-loop
system is formed through a field
efficacy feedback iterative model and the feature
library. This method improves peach yield and quality, reduces
pesticide residues and costs, is suitable for the climate of Jiangsu and Zhejiang, and has broad application prospects.