面向农户需求的作物病害智能管控技术研究现状与推广策略

Research Status and Promotion Strategies of Crop Disease Intelligent Control Technology Targeting Farmers' Needs

摘要:

作物病害智能管控技术为破解传统病害诊断与防治效率低的困境提供了新路径，但推广面临农户需求多样、技术体系复杂、应用场景分散等现实挑战。以病三角原理为理论基础，阐明作物病害智能管控工作原理，构建了涵盖感知层、认知层、预测层、决策层和执行层的作物病害智能管控技术体系。在此基础上，系统分析了多模态数据采集与融合技术、作物病害表征机理解析技术、作物病害关联挖掘与预测技术、多目标决策与处方推荐技术、作物病害智能管控终端装备的研究现状。基于创新扩散理论和技术接受模型，深入分析农户对作物病害智能管控技术的需求特征以及典型应用场景。最后，设计了面向农户需求的4阶段作物病害智能管控模式，构建了以农户需求为核心的多主体协同推广策略方案，提出跨区协同、技术优化、示范推广、能力提升、终端适配、制度保障等推广措施。研究结果可为作物病害智能管控技术从研发到推广应用提供科学依据与实践指导。

Abstract:

Crop disease intelligent control technology offers an approach to overcome the inefficiencies of traditional disease diagnosis and management.However, its promotion still faces practical challenges, including diverse farmer need, complex technological systems, and fragmented application scenarios.Grounded in the disease triangle principle, the working mechanism of crop disease intelligent control was elucidated and a five-layer technological framework encompassing perception, cognition, prediction, decision-making, and execution was constructed.Based on this framework, the research status of core technologies was systematically analyzed, including multi-modal data acquisition and fusion, disease characterization mechanism analysis, association mining and prediction, multi-objective decision-making and prescription recommendation, and intelligent control terminal equipment.Drawing on innovation diffusion theory and the technology acceptance model, farmers' demand characteristics for intelligent control technology and their typical application scenarios were further explored.Subsequently, a four-stage intelligent control model oriented to farmer needs was designed, a multi-stakeholder collaborative promotion strategy system centered on farmer demands was constructed, and specific promotion measures were proposed, including cross-regional collaboration, technology optimization, demonstration and extension, capacity building, terminal adaptation, and institutional support.This research can provide scientific basis and practical guidance for the transition of crop disease intelligent control technology from research to application.