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通过在西北林学院苗圃的北京杨上进行孢子捕捉和病情调查，利用气象因子中的温度（Ｘ１）、湿度（Ｘ２）、降雨量（Ｘ３）、温湿比（Ｘ６）、雨温比（Ｘ７）、雨湿比（Ｘ８）以及树皮相对膨胀度ＲＴ％（Ｘ４）和孢子数（Ｘ５）来分别预测４０ｄ后的病情指数（ｙ）以及第四个１０天内新出现病斑数量（ｙ′）和病情指数增长值（ｙ″）。利用ＳＹＳＴＡＴ软件分别做多元线性回归、逐步回归和非线性回归，得到三个模型，经过实际病情验证，均有较高的准确性
Through the investigation of spore trapping and disease in Beijing poplar in nursery of Northwest Forestry College, the effects of temperature, water temperature (X1), humidity (X2), rainfall (X3), temperature and humidity ratio (Y) and the number of new lesions in the fourth 10 days (y ’), the rain wet ratio (X8) and the bark relative expansion RT% (X4) and the number of spores (X5) ) And the index of disease growth (y ") using SYSTAT software to do multiple linear regression, stepwise regression and nonlinear regression, respectively, to obtain three models, after the actual condition verification, have higher accuracy