Cao Xueren, Yao Dongming, Xu Xiangming, Zhou Yilin, Ding Kejian, Duan Xiayu, Fan Jieru, Luo Yong
State Key Laboratory for Biology of Plant Disease and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, and Key Laboratory of Integrated Pest Management on Tropical Crops, Ministry of Agriculture, Environment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571001, China.
State Key Laboratory for Biology of Plant Disease and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, and College of Plant Protection, Anhui Agricultural University, Hefei 230036, China.
Plant Dis. 2015 Mar;99(3):395-400. doi: 10.1094/PDIS-02-14-0201-RE.
Disease severity of wheat powdery mildew, caused by Blumeria graminis f. sp. tritici, was recorded weekly in fungicide-free field plots for three successive seasons from 2009 to 2012 in Langfang City, Hebei Province, China. Airborne conidia of B. graminis f. sp. tritici were trapped using a volumetric spore sampler, and meteorological data were collected using an automatic weather station. Cumulative logit models were used to relate the development of wheat powdery mildew to weather variables and airborne conidia density. Density of airborne conidia was the most important variate; further addition of weather variables, although statistically significant, increased model performance only slightly. A model based on variables derived from temperature and humidity had a generalized R of 72.4%. Although there were significant differences in model parameters among seasons, fine adjustment did not increase model performance significantly.
2009年至2012年连续三个季节,在中国河北省廊坊市无杀菌剂的田间小区每周记录由小麦白粉菌引起的小麦白粉病的病情严重程度。使用体积孢子采样器捕获小麦白粉菌的气传分生孢子,并使用自动气象站收集气象数据。使用累积logit模型将小麦白粉病的发展与气象变量和气传分生孢子密度联系起来。气传分生孢子密度是最重要的变量;进一步添加气象变量,虽然在统计学上有显著意义,但仅略微提高了模型性能。基于温度和湿度导出变量的模型广义R为72.4%。尽管各季节模型参数存在显著差异,但精细调整并未显著提高模型性能。