| 宁夏温室瓜菜白粉病菌鉴定及病害流行预测模型构建 |
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| 引用本文：李磊福,孙秋玉,史娟,马占鸿.宁夏温室瓜菜白粉病菌鉴定及病害流行预测模型构建.植物保护学报,2017,44(5):788-795 |
| DOI：10.13802/j.cnki.zwbhxb.2017.2016053 |
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| 中文摘要:为明确宁夏回族自治区温室瓜菜白粉病菌的分类地位，对采自该地区温室的南瓜、黄瓜和甜瓜上的白粉病菌基于ITS序列分析进行分子鉴定；利用孢子捕捉器对温室中甜瓜白粉病菌的孢子量进行监测，分析环境因子、孢子量和病情指数之间的关系，并采用逐步回归分析法构建温室甜瓜白粉病的流行预测模型。结果表明，基于ITS序列的分子鉴定结果，3种瓜菜白粉病的病原菌均为单囊壳白粉菌Podosphaera xanthii。发病期间，每日温室中甜瓜白粉病菌的孢子量在12：00-16：00时段最多，占24 h内总孢子量的34%~81%，20：00-08：00时段最少；白粉病菌孢子的释放与光照强度有关，相关系数为0.602。第t天的病情指数与标准累积温度、标准累积湿度、t-4 d前08：00-12：00时段的累积孢子量、第t-4天16：00-20：00时段的孢子量均具有显著的相关性，相关系数分别为0.935、0.938、0.956和0.921。以标准累积湿度和第t-4天16：00-20：00时段的孢子量为预测变量构建了温室甜瓜白粉病流行预测模型，决定系数为0.962，表明该模型具有较好的实际应用价值。 |
| 中文关键词:瓜菜白粉病 ITS序列 孢子量 环境因子 预测模型 |
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| Pathogen identification and forecasting model construction of cucurbit powdery mildew in greenhouse in Ningxia |
| Author Name | Affiliation | E-mail | | Li Leifu | Department of Plant Pathology, College of Plant Protection, China Agricultural University, Beijing 100193, China | | | Sun Qiuyu | Department of Plant Pathology, College of Plant Protection, China Agricultural University, Beijing 100193, China | | | Shi Juan | College of Agriculture, Ningxia University, Yinchuan 750001, Ningxia Hui Autonomous Region, China | shijuan0@163.com | | Ma Zhanhong | Department of Plant Pathology, College of Plant Protection, China Agricultural University, Beijing 100193, China | |
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| Abstract:In order to determine the pathogen of cucurbit powdery mildew in Ningxia, the sample of cucurbit powdery mildew were collected from pumpkin, cucumber and melon leaves to amplify their ITS sequences and construct phylogenetic trees using a neighbor-joining method. Meanwhile, spore traps were used to monitor the number of airborne conidia of melon powdery mildew in greenhouse. The relationship among environmental factors, the number of airborne conidia and the disease index was analyzed to develop a prediction model of this disease. The identification results showed that the pathogen of cucurbit powdery mildew was primarily determined to be Podosphaera xanthii. The number of airborne conidia of melon powdery mildew were released largest from 12:00-16:00, accounting for 34%-81% of total amount of conidia within 24 h, and least between 20:00-08:00. Conidial release was related to the light as the correlation coefficient was 0.602. The disease index was most related to the standard accumulated temperature, the standard accumulated moisture, the accumulated number of airborne conidia between 08:00-12:00 four days ago and the number of airborne conidia between 12:00-16:00 four days ago and their correlation coefficients were 0.935, 0.938, 0.956 and 0.921, respectively. A prediction model of melon powdery mildew in greenhouse was constructed and the standard accumulated moisture and the number of airborne conidia between 16:00-20:00 four days ago were chosen as predictive variables and the determination coefficient of the regression equation was 0.962, which shows this model occupies preferable practicability. |
| keywords:cucurbit powdery mildew ITS sequences number of airborne conidia environmental factors prediction model |
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