智能化农业装备学报（中英文）

农作物重大病虫害预警与应急防控技术研究现状与趋势

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李董 ¹ , 汤启国 ¹ , 王红波 ¹^,² , 邱威 ¹^,³^,⁴ , 熊炜 ¹^,^*^,^*

智能化农业装备学报（中英文） | 2025,6(1): 25-40

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智能化农业装备学报（中英文） | 2025 , 6 (1) : 25 -40

农作物重大病虫害预警与应急防控技术研究现状与趋势

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李董¹, 汤启国¹, 王红波¹^,², 邱威¹^,³^,⁴, 熊炜¹^,^*^,^*

作者信息

^1.农业农村部科技发展中心，北京市，100176

^2.湖北省农业科学院粮食作物研究所，湖北武汉，430064

^3.南京农业大学工学院，江苏南京，210031

^4.江苏省智能化农业装备重点实验室，江苏南京，210031

通讯作者:

^* 熊炜，男，1969年生，北京人，高级农艺师；研究方向为农业科技管理。E-mail：1537233963@qq.com

作者简介:

李董，女，1992年生，北京人，硕士，农艺师；研究方向为农业科技管理。E-mail：lidongmoa@126.com

Current status and trends of research on early warning and emergency control technology for major crop pests and diseases

Dong LI¹, Qiguo TANG¹, Hongbo WANG¹^,², Wei QIU¹^,³^,⁴, Wei XIONG¹

Affiliations

^1.Development Center of Science and Technology, Ministry of Agriculture and Rural Affairs, Beijing 100176, China

^2.Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China

^3.Nanjing Agricultural University College of Engineering, Nanjing 210031, China

^4.Jiangsu Key Laboratory for Intelligent Agricultural Equipment, Nanjing 210031, China

Corresponding Author:

^* XIONG Wei, E-mail: 1537233963@qq.com

LI Dong, E-mail: lidongmoa@126.com

出版时间: 2025-02-15 doi: 10.12398/j.issn.2096-7217.2025.01.003

文章导航

摘要

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随着农业的发展，重大病虫害对农林业造成的经济损失和食品安全威胁日益严重。2024年中国主要粮食作物面临22种病虫害的挑战，预计影响面积达155 411 khm²次，产量损失超1.5×10¹¹ t。综述了农作物病虫害预警与应急防控技术的现状，其中病虫害预警技术包括物联网、遥感技术和计算机视觉识别技术；应急防控技术涵盖了化学通信机制的理解以开发新药剂和装备、物理消杀和智能防控产品的创新、生物防治资源的利用与产品创新、害虫致害性变异机制的研究以及植物抗性品种的可持续利用技术、害虫抗药性机制的研究与治理技术的开发，以及病虫害生态调控机理的研究与应用技术，旨在通过多学科交叉合作，实现对病虫害的有效控制，同时减少对环境的影响，促进农业的可持续发展。并探讨了病虫害预警与应急防控技术在农业领域的应用，分析了其在农业科技发展中的重要作用，并概括了各领域面临的挑战，例如无人机遥感监测技术精度不够，病虫害图像自动识别技术样本采集困难，化学防治未能实现精准施药，绿色制剂的生产工艺和市场化推广较为滞后以及病虫害预警系统的建设尚不完善等问题。未来，应加快物联网技术应用于病虫害预警，推动智慧农业与病虫害预警系统建设，研究无人机遥感监测技术、病虫害图像自动识别技术与化学防治技术生物防治技术。

关键词

病虫害预警 / 应急防控 / 物理防治 / 抗药性机制 / 生态调控策略 / 植物保护

Abstract

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With the advancement of agriculture, the economic losses and food safety threats caused by major plant diseases and pests to agriculture and forestry are becoming increasingly severe. In 2024, China's main food crops face challenges from 22 types of diseases and pests, with an expected affected area of 155 411 khm² and a yield loss exceeding 1.5×10¹¹ t. This article provides an overview of the current status of crop disease and pest warning and emergency control technologies, where disease and pest warning technologies include the Internet of Things, remote sensing technology, and computer vision recognition technology; emergency control technologies cover the understanding of chemical communication mechanisms for the development of new pesticides and equipment, innovation in physical extermination and intelligent control products, utilization and product innovation of biological control resources, research on pest damage-type variation mechanisms and sustainable use of plant resistance varieties, research and development of pesticide resistance mechanisms and control technologies, as well as research and application technologies for the ecological regulation of diseases and pests. The aim is to achieve effective control of diseases and pests through interdisciplinary cooperation, while reducing environmental impact and promoting sustainable agricultural development. The article also discusses the application of disease and pest warning and emergency control technologies in the agricultural field, analyzes their important role in the development of agricultural science and technology, and summarizes the challenges faced in each field, such as the insufficient accuracy of unmanned aerial vehicle remote sensing monitoring technology, difficulties in sample collection for disease and pest image automatic recognition technology, the failure of chemical control to achieve precise application, the lagging production processes and market promotion of green formulations, and the incomplete construction of disease and pest warning systems. In the future, the application of Internet of Things technology to disease and pest warning should be accelerated, the construction of smart agriculture and disease and pest warning systems should be promoted, and research should be conducted on unmanned aerial vehicle remote sensing monitoring technology, disease and pest image automatic recognition technology, chemical control technology, and biological control technology.

Key words

pest and disease forewarning / emergency control / physical control / mechanisms of resistance / ecological control strategies / plant protection

引用本文

李董, 汤启国, 王红波, 邱威, 熊炜. 农作物重大病虫害预警与应急防控技术研究现状与趋势. 智能化农业装备学报（中英文）, 2025 , 6 (1) : 25 -40 . DOI: 10.12398/j.issn.2096-7217.2025.01.003

Dong LI, Qiguo TANG, Hongbo WANG, Wei QIU, Wei XIONG. Current status and trends of research on early warning and emergency control technology for major crop pests and diseases[J]. Journal of Intelligent Agricultural Mechanization, 2025 , 6 (1) : 25 -40 . DOI: 10.12398/j.issn.2096-7217.2025.01.003

基金

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农业农村部科技发展中心专业机构管理费(2069999)
国家自然科学基金(32171905)

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2025年第6卷第1期

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doi: 10.12398/j.issn.2096-7217.2025.01.003

接收时间：2024-11-11
首发时间：2026-11-05
出版时间：2025-02-15

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收稿日期：2024-11-11
修回日期：2024-12-30

基金

Professional Institutions Management fees of the Technology Development Center of the Ministry of Agriculture and Rural Affairs(2069999)

农业农村部科技发展中心专业机构管理费(2069999)

National Natural Science Foundation of China(32171905)

国家自然科学基金(32171905)

作者信息

^1.农业农村部科技发展中心，北京市，100176

^2.湖北省农业科学院粮食作物研究所，湖北武汉，430064

^3.南京农业大学工学院，江苏南京，210031

^4.江苏省智能化农业装备重点实验室，江苏南京，210031

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^* 熊炜，男，1969年生，北京人，高级农艺师；研究方向为农业科技管理。E-mail：1537233963@qq.com

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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