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

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