Abstract: The study proposed the tea yield prediction mechanism using the adaboost BP network model with the tea yield level factor and China meteorological forcing dataset in 59 counties of Zhejiang in 1999-2018. We extracted 11 factors including the planting area, the yearly average temperature, the average relative humidity from March to July in the sensitivity analysis. The tea yield prediction model was established then. The result shows that the adaboost BP method with the yield level factor could reach the correlation coefficient as 0.893 and the average of the relative error as 0.187 and the variance of the relative error as 0.316. When selecting history data, the prediction error was lower when the data was closer to the prediction years. Based on the proposed method, the distribution of the prediction error was made. The average relative errors were 18.32%, 16.73% and 22.69% in level 1 high production area, level 2 medium area and level 3 general production area, respectively. The proposed model could realize the tea yield prediction in the counties of Zhejiang Province and could be used in the management of tea production process.

Key words: tea, yield prediction, model, adaboost, BP model