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作物病害监测预警研究进展
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引用本文:胡小平,户雪敏,马丽杰,黄冲,周益林,徐向明.作物病害监测预警研究进展.植物保护学报,2022,49(1):298-315
DOI:10.13802/j.cnki.zwbhxb.2021.2021134
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作者单位E-mail
胡小平 西北农林科技大学植物保护学院, 旱区作物逆境生物学国家重点实验室, 陕西 杨凌 712100 xphu@nwsuaf.edu.cn 
户雪敏 西北农林科技大学植物保护学院, 旱区作物逆境生物学国家重点实验室, 陕西 杨凌 712100  
马丽杰 西北农林科技大学植物保护学院, 旱区作物逆境生物学国家重点实验室, 陕西 杨凌 712100
鄂尔多斯生态环境职业学院, 内蒙古 鄂尔多斯 017010 
 
黄冲 全国农业技术推广服务中心, 北京 100125  
周益林 中国农业科学院植物保护研究所, 植物病虫害生物学国家重点实验室, 北京 100193  
徐向明 英国国家农业植物研究所东茂林病虫害生态学研究组, 东茂林 ME19 6BJ  
中文摘要:作物侵染性病害是影响作物安全生产的重要生物灾害,具有突发性、暴发性和强流行性等特点,常常造成巨大的损失。近年来,随着病菌孢子捕捉、遥感、地理信息系统、卫星定位系统、大气环流分析、分子生物学、人工智能、大数据和物联网等技术的快速发展与应用,作物病害监测预警技术取得了重要进展,大幅度提高了对病害监测和预测的准确度。该文综述了小麦、水稻、玉米和马铃薯等粮食作物的6种重大病害监测预警工作的研究进展及应用情况,同时,探讨了我国作物病害监测预警工作中存在的主要问题,并提出了未来作物病害监测预警的前景和发展方向。
中文关键词:孢子捕捉  实时定量PCR  "3S"技术  智能化
 
Research progresses in monitoring and prediction of crop diseases
Author NameAffiliationE-mail
Hu Xiaoping State Key Laboratory of Crop Stress Biology in Arid Areas, College of Plant Protection, Northwest A&F University, Yangling 712100, Shaanxi Province, China xphu@nwsuaf.edu.cn 
Hu Xuemin State Key Laboratory of Crop Stress Biology in Arid Areas, College of Plant Protection, Northwest A&F University, Yangling 712100, Shaanxi Province, China  
Ma Lijie State Key Laboratory of Crop Stress Biology in Arid Areas, College of Plant Protection, Northwest A&F University, Yangling 712100, Shaanxi Province, China
Ordos Vocational College of Eco-Environment, Ordos 017010, Inner Mongolia Autonomous Region, China 
 
Huang Chong National Agro-Tech Extension and Service Center, Beijing 100125, China  
Zhou Yilin State Key Laboratory for Biology of Plant Disease and Insect Pest, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China  
Xu Xiangming Pest & Pathogen Ecology, East Malling Research, The National Institute of Agricultural Botany, East Malling, West Malling, Kent ME19 6BJ, UK  
Abstract:Infectious crop diseases can cause significant food losses due to their explosive nature. In recent years, the rapid development in many areas, such as pathogen inoculum trapping, remote sensing, geographic information system, global positioning system, atmospheric circulation modelling, molecular biology, artificial intelligence, big data analytics and Internet of Things(IoT), has made it possible to predict crop disease development reliably at a fine spatio-temporal resolution. In this review, we reviewed the current status of research and development in monitoring and predicting six major diseases of wheat, rice, maize, and potato. At the same time, we also identified some key research questions on crop disease monitoring and prediction in China that should be tackled in the near future in order to exploit fully these technology advances in disease management.
keywords:spore trap  real-time quantitative PCR  "3S"technology  intelligent information technology
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