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基于病菌孢子捕捉和real-time PCR技术的田间空气中小麦白粉病菌孢子动态监测及病情估计模型研究
引用本文:王奥霖,商昭月,张美惠,王贵,胡小平,徐飞,孙振宇,曹世勤,刘伟,范洁茹,周益林.基于病菌孢子捕捉和real-time PCR技术的田间空气中小麦白粉病菌孢子动态监测及病情估计模型研究[J].植物保护,2024,50(2):49-56.
作者姓名:王奥霖  商昭月  张美惠  王贵  胡小平  徐飞  孙振宇  曹世勤  刘伟  范洁茹  周益林
作者单位:1. 中国农业科学院植物保护研究所,植物病虫害综合治理全国重点实验室, 北京100193; 2. 西北农林科技大学植物保护学院, 作物抗逆与高效生产全国重点实验室, 杨凌712100; 3. 河南省农业科学院植物保护研究所, 农业农村部华北南部作物有害生物综合治理重点实验室, 郑州450002; 4. 甘肃省农业科学院植物保护研究所, 兰州730070; 5. 新疆农业大学农学院, 农林有害生物监测与安全防控重点实验室, 乌鲁木齐, 830052
基金项目:国家自然科学基金(32072359)
摘    要:利用Burkard定容式孢子捕捉器结合real-time PCR定量技术,分别对种植高抗、中感和高感白粉病小麦品种的田间空气中白粉病菌分生孢子浓度进行监测,结果表明,real-time PCR定量与传统的显微观察计数两种方法测得的孢子浓度呈显著正相关(P≤0.01),且两种病菌孢子计数方法在同一抗性品种上监测到的孢子浓度动态相近。此外,两种方法测得的孢子浓度与各气象因子的相关性分析结果一致,空气中的白粉病菌孢子浓度主要与空气相对湿度显著正相关。在此基础上,利用两种方法测定的田间空气中白粉病菌孢子浓度分别建立了基于累积孢子浓度的田间病情估计模型。分析发现,基于两种孢子浓度测定方法建立的病情估计模型间无显著性差异,表明real-time PCR定量技术测定的孢子浓度在构建白粉病病情估计模型上具有一定可行性。该结果为real-time PCR定量技术与病菌孢子捕捉技术相结合用于小麦白粉病的监测和预测提供理论依据。

关 键 词:小麦白粉病    病菌孢子捕捉    实时荧光定量PCR    病原菌监测    病情估计模型
收稿时间:2023/10/10 0:00:00
修稿时间:2023/11/3 0:00:00

Dynamic monitoring of aerial conidia and disease estimation models for wheat powdery mildew in fields using pathogen spore traps coupled with real-time PCR technique
WANG Aolin,SHANG Zhaoyue,ZHANG Meihui,WANG Gui,HU Xiaoping,XU Fei,SUN Zhenyu,CAO Shiqin,LIU Wei,FAN Jieru,ZHOU Yilin.Dynamic monitoring of aerial conidia and disease estimation models for wheat powdery mildew in fields using pathogen spore traps coupled with real-time PCR technique[J].Plant Protection,2024,50(2):49-56.
Authors:WANG Aolin  SHANG Zhaoyue  ZHANG Meihui  WANG Gui  HU Xiaoping  XU Fei  SUN Zhenyu  CAO Shiqin  LIU Wei  FAN Jieru  ZHOU Yilin
Institution:1. State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China; 2. State Key Laboratory for Crop Stress Resistance and High-Efficiency Production, College of Plant Protection, Northwest A & F University, Yangling 712100, China; 3. Key Laboratory of Integrated Pest Management on Crops in Southern Part of North China, Ministry of Agriculture and Rural Affairs, Institute of Plant Protection, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China; 4. Institute of Plant Protection, Gansu Academy of Agricultural Sciences, Lanzhou 730070, China; 5. Key Laboratory of the Pest Monitoring and Safety Control of Crops and Forests of Xinjiang Uygur Autonomous Region, College of Agronomy, Xinjiang Agricultural University, Urumqi 830052, China
Abstract:
Keywords:wheat powdery mildew  pathogen spore trap  real-time quantitative PCR  monitoring of pathogen  disease estimation model
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