作物病虫害多模态智能管控技术研究进展OA

Crop pests and diseases are characterized by complex occurrence mechanisms,multiple influencing factors,and strong spatiotemporal heterogeneity.Existing studies have mostly focused on single modalities or individual tasks,making it difficult to support the coordinated implementation of diagnosis,monitoring,early warning,and prevention-control services.Based on a review of domestic and international research progress,it systematically analyzed the key technologies for multimodal intelligent management and control of crop pests and diseases.Firstly,the occurrence mechanisms and multi-factor coupling characteristics of crop pests and diseases were summarized,and the multimodal data types and preprocessing methods were reviewed,including microscopic images,visible images,multispectral/hyperspectral images,thermal infrared images,environmental and meteorological data,remote sensing observations,farming records,and plant electronic medical records.Secondly,a"point-area-spatiotemporal"multi-scale intelligent management framework was constructed,and an overall technical framework for multimodal intelligent management and control of crop pests and diseases was further proposed.Finally,research progress was summarized in terms of point-scale intelligent identification and precise prevention-control,area-scale regional monitoring and precision operation,spatiotemporal dynamic early warning and decision-support services,and the integration and application demonstration of full-process intelligent management systems.It showed that intelligent management and control of crop pests and diseases was developing from single-task identification toward multimodal and multi-scale collaborative analysis,from traditional intelligent models toward knowledge-enhanced agricultural foundation models and agents,and from methodological research toward edge-cloud-end collaboration and robotic closed-loop services.However,significant challenges remained in data standardization,model generalization,platform collaboration,real-time control,and practical deployment.In the future,promoting multi-source heterogeneous data interconnection,knowledge-enhanced modeling,intelligent equipment collaboration,and trustworthy closed-loop service systems would provide technical support for precise,efficient,and green prevention and control of crop pests and diseases.