小麦条锈病是影响我国小麦安全生产的重要生物灾害，是典型的气传流行性病害。目前，有效监测预警小麦条锈病的方法仍然是采用田间大面积病情普查，并结合气象数据和专家经验进行的，存在耗时费工、效率低下等问题。本研究将在前期小麦条锈菌传播规律研究结果的基础上，通过孢子捕捉和实时定量PCR技术，研究我国小麦条锈病主要流行区系内空气中条锈菌夏孢子数量的动态变化规律及其远程传播路线，准确估计初始菌源数量，并结合田间小气候因素及条锈病病情监测结果，建立基于孢子捕捉数量和田间小气候关键因子的小麦条锈病预测模型，提高预测预报的准确率，以期为小麦条锈病的科学防控提供服务。

Wheat stripe rust caused by Puccinia striiformis f. sp. tritici is an important disaster in wheat production in China. It is a typical airborne and epidemic disease of wheat. At present, efficient monitoring and prediction of the disease are still through large-scale field investigation combined with meteorological data and experts' experiences. The method has shortcomings of time-consuming and low efficiency. In this study, the dynamic change of urediniospore quantity and its dispersal route in air of the main epidemic region, and the primary inoculum source will be studied and estimated through spore trapping and real-time quantitative PCR based on RNA level. Meanwhile, the weather factors in micro-climate will be recorded through an automatic weather station installed in the field. The prediction model of wheat stripe rust will be established based on urediniospore quantity and the key meteorological factors in order to improve the prediction accuracy of the disease and serve for the prediction and scientific control of wheat stripe rust.