关键词: 油菜, 花期预报模型, 相关分析法, 灰色关联分析法, 物候期

Abstract: In order to explore a simple and easy method to predict the initial flowering stage of rape, the correlation analysis method was used in this paper to determine the winter climate factors significantly related to the first flowering period, and the gray correlation analysis method was also used to determine the pre flowering phenology factors most related to the first flowering period. Then the multiple regression linear equations were established and back substitution test was carried out, and finally the root mean square error (RMSE) and relative error (RE) models were used to evaluate the simulated and measured values. The results showed that: (1) the winter meteorological factors significantly related to the first flowering period were the average minimum temperature in January, the average minimum temperature in February and the sunshine hours in February, and their correlation coefficients were −0.404, −0.556, −0.478, respectively. There was no collinearity between the three independent variables. The regression model was statistically significant and passed the significance test. (2) Among the pre-anthesis phenological stages, there is a high correlation between the sprouting stage, budding stage and the initial flowering stage; and their correlation coefficients were 0.656 and 0.634, respectively. The regression model also showed statistical significance and passed the significance test. (3) The models established by the two methods are tested and evaluated. The back substitution test shows that the fitting accuracy of the models established by the two methods is relatively close on the whole. The RMSE climate factor based on climate factor is 7.16, and the RE climate factor is 11.2%; The phenological factors based on RMSE and RE were 6.50% and 3.87%, respectively. Pearson correlation analysis showed that the correlation coefficients of R phenological factor and R climatic factor were 0.738 and 0.658 respectively, which passed the significance test of 0.01 level. Among them, R phenological factor is higher than R climatic factor. Based on comprehensive analysis of various indicators, the model established by grey correlation analysis is more reliable than the model established by climate factors can be drawn.

Key words: Rape, Flowering prediction model, Correlation analysis method, Grey correlation analysis method, Phenology