关键词: 西湖龙井茶, 开采期, 物候期, 气象因子, 预报, 集成模型

Abstract: Based on the picking date of the main species of Xihulongjing Tea (Longjing43 and Longjingqunti) and its meteorological data, the accumulated temperature prediction model and the stepwise regression prediction model of Xihulongjing tea were constructed by using accumulated temperature and stepwise regression method, also the prediction of multiple regression ensemble method was integrated by these two prediction results, using the multiple linear regression method. The results showed that the accumulated temperature prediction model, stepwise regression prediction model and integrated prediction model all passed the significance test of P<0.01. The simulated mean absolute error（MAE） of accumulated temperature prediction model were 3.6d and 2.8d, while the prediction MAE of 2-year test prediction were 2.5d and 1.0d for Longjing43 and Longjingqunti respectively. In addition, the simulated MAE of stepwise regression analysis were 0.9d and 1.4d, the prediction MAE of 2-year test prediction were 1.6d and 0.8d for Longjing43 and Longjingqunti separately. The prediction of multiple regression ensemble method was more accurate than single method with the simulated MAE value were 0.7d and 1.1d ,while the prediction MAE of 2-year test prediction were 1.3d and 0.8d, the prediction of multiple regression ensemble method would provide more scientific support for guiding tea production. These three forecasting models are of practical value for the prediction of the picking up period of Xihulongjing tea. The prediction of multiple regression ensemble method is more ideal and with more practical application value than accumulated temperature forecasting model and stepwise regression analysis model.

Key words: Xihulongjing tea, Picking date, Phenophase, Meteorological factors, Prediction, Ensemble method