Abstract: Crop diseases are one of the major agricultural disasters in China, which seriously endangers crop growth and development and threaten food security. In order to macroscopically grasp the development trends of crop diseases and understand the research frontiers and application hotspots of crop disease monitoring and early warning,based on the bibliometric method, VOSviewer visualization software is used to visualize and analyze the papers related to crop disease monitoring and early warning research included in the Web of Science core collection database during 2003—2022,which can provide theoretical reference for researchers to track the research frontier and grasp the research direction. The results show that the number of papers published in the field of crop disease monitoring and early warning is gradually increasing and has a promising future. China is the country with the largest number of papers in the field of crop disease monitoring and early warning, but the quality of research results needs to be further improved. The core authors have formed a fixed core research team, and the authors with the largest number of papers are Huang Wenjiang, Zhang Jingcheng, Kang Zhensheng and Varshney. The research results are mainly published in Frontiers in Plant Science, Plant Disease, and Computers and Electronics in Agriculture.The main institutions that publish articles are USDA Agricultural Research Service, Chinese Academy of Sciences, and Chinese Academy of Agricultural Sciences. The main institutions publishing papers include USDAARS, Chinese Academy of Sciences and Chinese Academy of Agricultural Sciences, disease resistance gene breeding, PCR diagnosis of crop diseases, convolutional neural network and deep learning classification of crop diseases and remote sensing monitoring of crop vegetation indices are the focus and hot spots of research in this field in the past 20 years. In a comprehensive view, crop disease monitoring and early warning research has strong application prospects. However, the challenges are still great, which require breakthroughs in existing technical means and integration of multiple technologies to promote crop disease monitoring and early warning in the direction of more intelligent and precise.

Key words: crop diseases, monitoring, early warning, visualization analysis, cluster analysis, Web of Science

摘要： 作物病害是我国主要农业灾害之一，严重危害作物生长发育，威胁粮食安全。为宏观掌握作物病害的发展动态，了解作物病害监测和预警的研究前沿和应用热点，基于文献计量学方法，利用VOSviewer可视化软件，对2003—2022年间Web of Science核心合集数据库收录的作物病害监测和预警研究的相关论文进行可视化分析，为作物病害研究者跟踪研究前沿、把握研究方向提供理论参考。结果表明：作物病害监测和预警领域发文量整体呈现逐步上升趋势，具有广阔的发展前景；中国是作物病害监测和预警研究领域发文数量最多的国家，但研究成果质量需进一步提升；核心作者之间已形成固定的核心研究团队，发文量最多的作者来自以黄文江、张竞成、康振生和Varshney为代表的研究团队；研究成果主要刊载在Frontiers in Plant Science、Plant Disease和Computers and Electronics in Agriculture期刊上；发文的主要机构有美国农业部农业研究局、中国科学院和中国农业科学院；抗病基因育种、PCR诊断作物病害、卷积神经网络和深度学习分类作物病害和遥感监测作物植被指数是近20年来该领域研究的重点和热点。综合来看，作物病害监测和预警研究具有较强的应用前景，但面临的挑战仍很大，需要突破现有技术手段，多种技术相融合，推动作物病害监测和预警向着更加智能化、精准化的方向发展。

关键词: 作物病害, 监测, 预警, 可视化分析, 聚类分析, Web of Science