农业装备与车辆工程2025，Vol.63Issue(10)：1-8,8.DOI:10.3969/j.issn.1673-3142.2025.10.001
水稻病虫害AI识别研究现状与展望
Research status and prospect of AI recognition for rice diseases and pests
摘要
Abstract
The accurate identification and efficient prevention and control of rice diseases and pests are recognized as crucial links in ensuring food security and promoting the high-quality development of agriculture.Traditional methods for identifying diseases and pests mainly rely on manual judgment and specialized detection instruments;however,they are still unable to meet the practical needs of modern agricultural production in terms of identification efficiency,accuracy,and adaptability to complex field environments.With the rapid development of artificial intelligence and information technology,deep learning has become the mainstream technical means for the intelligent identification of agricultural diseases and pests.This technology can independently learn the characteristics of diseases and pests from massive image data,significantly improve the identification accuracy,and drive the enhancement of agricultural intelligence.For this reason,a systematic review was conducted on the key technologies in the identification of rice diseases and pests.The review focused on aspects such as the acquisition and preprocessing of disease and pest image data,the optimization of deep learning network structures,model interpretability,and prediction.Through this,the research progress and core issues both at home and abroad were sorted out.Studies showed that the current research on disease and pest identification still faced challenges such as over-reliance on sample quality,weak interpretability of model decisions,and great difficulty in practical deployment.On this basis,further exploration could be carried out in the future in directions such as the standardization of data collection,model lightweighting and structural innovation,multi-modal information fusion,and big data-driven prediction,so as to improve the practicality and intelligence level of the rice disease and pest identification system.关键词
水稻病虫害/深度学习/目标识别/农业智能化Key words
rice pests/deep learning/object identification/agricultural intelligent分类
农业科技引用本文复制引用
杨圣杰,刘双喜,王刘西航,刘忠贤,张玮平,卢淼,展颖超,王圣楠,国磊,魏立兴..水稻病虫害AI识别研究现状与展望[J].农业装备与车辆工程,2025,63(10):1-8,8.基金项目
山东省现代农业产业技术体系水稻农业机械岗位专家项目(SDAIT-17-08) （SDAIT-17-08）
山东省现代农业产业技术体系东营综合试验站(SDAIT-17-10) （SDAIT-17-10）
