苹果蠹蛾对高效氯氟氰菊酯的抗性现状、机制及治理策略
Current status,mechanism,and management strategy of codling moth Cydia pomonella resistance to lambda-cyhalothrin
刘雨茜 1胡超 1马尧 1鞠迪 1杨念婉 2李玉婷 1高萍 1杨雪清1
作者信息
- 1. 沈阳农业大学植物保护学院,辽宁省经济与应用昆虫学教育厅重点实验室,沈阳市重大农业入侵生物监测与防控重点实验室,沈阳 110866
- 2. 中国农业科学院植物保护研究所,北京 100193
- 折叠
摘要
苹果蠹蛾Cydia pomonella属鳞翅目卷蛾科,是全球仁果类水果种植地区最重要的果树害虫之一,也是我国重大农业入侵物种,对全球水果生产造成严重威胁.当前主要采用高效氯氟氯氰菊酯等杀虫剂对苹果蠹蛾进行防治,杀虫剂的频繁使用导致其对高效氯氟氰菊酯产生了抗性.针对苹果蠹蛾对高效氯氟氰菊酯的抗性问题,该文综述了全球苹果蠹蛾种群对高效氯氟氰菊酯的抗性现状,指出由编码细胞色素P450(cytochrome P450,P450)、羧酸酯酶(carboxylesterase,CarE)和谷胱甘肽S-转移酶(glutathione S-transferase,GST)的解毒酶基因过表达导致代谢能力增强是其最普遍的抗性机制,提出合理的抗性治理策略,并对苹果蠹蛾的绿色防控进行展望.
Abstract
The codling moth,Cydia pomonella,is a major invasive pest of pome fruits,found on six continents and causing serious damage to global fruit production.Currently,the management of C.po-monella mainly relies on the application of insecticides,which has led to the development of insecticide resistance.Two major types of insecticide resistance mechanisms-metabolic resistance and target resistance-have been documented in this species.The most common resistance mechanism involves the overexpression of detoxification enzyme genes encoding cytochrome P450 monooxygenases(P450s),carboxylesterases(CarEs),and glutathione S-transferases(GSTs),which enhances the metabolic capac-ity of C.pomonella to break down insecticides.Given the prominent problem of C.pomonella's resis-tance to lambda-cyhalothrin and the need to maximize the effectiveness of this insecticidefor control-ling the pest,it is essential to develop reasonable resistance management strategies based on comprehen-sive understanding the resistance mechanisms.This review summarized the current status of C.po-monella resistance to lambda-cyhalothrin,explores the underlying resistance mechanisms,and dis-cusses strategies for effective insecticide resistance management in C.pomonella.
关键词
苹果蠹蛾/高效氯氟氰菊酯/解毒酶/靶标抗性/抗性监测Key words
Cydia pomonella/lambda-cyhalothrin/detoxification enzyme/target resistance/resistance monitoring引用本文复制引用
基金项目
国家重点研发计划(2021YFD1400200)
国家自然科学基金(32272588)
出版年
2024
NETL
NSTL
万方数据