本研究基于湖南省耒阳市2004—2024年的气象数据和油菜菌核病发生情况的监测数据，采用相关性分析和逐步回归分析法，探讨气温、降水量、雨日数、日照时数等气象要素对油菜菌核病发生的影响，并建立病害发生风险预测回归方程。结果表明，3月下旬和4 月上旬的降水量与油菜的病株率和病害的发生面积呈正相关；气温和日照时数与菌核病害的发生相关性较小；3月下旬和4月下旬的雨日数对油菜菌核病的发生影响较大。以油菜的病株率和病害的发生面积为因变量Y，降水量和雨日数为自变量X，建立4个气象单因子预测方程和2个复合气象预测方程，6个方程的F检验在0.01水平均具有统计学意义；回测验证表明，复合气象预测方程Y₄=-11.363 8+0.119 6X₁+0.109 7X₂（Y₄为病害发生面积，X₁、X₂分别为3月下旬、4月上旬降水量）和Y₆=17.112 9+0.109 2X₁+0.105 9X₂－0.477 5X₃－0.521 2X₄（Y₆为病害发生面积，X₁、X₂、X₃和X₄分别为3月下旬、4月上旬降水量和2月上旬、2月中旬雨日数）的预测值与实际值之间的拟合误差≤±2的年份占比较高，预测准确度高。综合表明，以降水量和雨日数为气象因子，建立的预测方程（4）和（6）更适宜应用于研究区的油菜菌核病预测。

Based on the meteorological data and monitoring data of sclerotinia stem rot occurrence of rapeseed in Leiyang City, Hunan Province from 2004 to 2024, this study employed correlation analysis and stepwise regression analysis to explore the effects of meteorological factors (e.g., temperature, precipitation, rainy days, and sunshine duration) on the occurrence of sclerotinia stem rot, and established multiple regression equations for disease occurrence risk prediction. The results showed that the precipitation in late March and early April was positively correlated with the disease plant rate and disease occurrence area of rapeseed. Temperature and sunshine duration had weak correlations with the occurrence of sclerotinia stem rot. The number of rainy days in late March and late April had a significant impact on the occurrence of rapeseed sclerotinia stem rot. Taking the disease plant rate and disease occurrence area of rapeseed as the dependent variable Y, and precipitation and rainy days as the independent variables X, 4 single-meteorological-factor prediction equations and 2 composite-meteorological-factor prediction equations were established. All 6 equations were statistically significant at the 0.01 level in the F-test (P<0.01). Back-test verification indicated that the composite-meteorological-factor prediction equations, Y₄=-11.363 8+0.119 6X₁+0.109 7X₂ (where Y₄ was the disease occurrence area; X₁, X₂ were the precipitation in late March, precipitation in early April, respectively) and Y₆=17.112 9 + 0.1092X₁ + 0.105 9X₂ - 0.477 5X₃ - 0.521 2X₄ (where Y₆ was the disease occurrence area; X₁, X₂, X₃, and X₄ were the precipitation in late March, precipitation in early April, number of rainy days in early February, and number of rainy days in mid-February, respectively), had a high proportion of years with a fitting error between predicted and actual values≤±2, showing high prediction accuracy.In conclusion, the prediction equations(4) and (6), established with precipitation and rainy days as meteorological factors are more suitable for the prediction of rapeseed sclerotinia stem rot in the study area.