Abstract:

In order to realize the best effects of spring tea picking in Gaochun, to optimize the tea picking time, and help tea farmers and tea enterprises to reduce costs and increase efficiency, based on the actual situation in Gaochun, the most suitable and effective forecast model of picking period was established to carry out the relevant analysis of spring tea picking period in Gaochun, so as to apply it into the actual production. Based on the first picking date of 'Wuniuzao' in Gaochun Chunqing Tea Garden from 2012 to 2023 and the meteorological data of the same period, the accumulated temperature and gradual regression methods were applied to construct the accumulated temperature forecast model and the stepwise regression forecast model. Research showed that the product temperature forecast model had great uncertainty, results of stepwise regression forecast model was more comparable with the actual result. The average temperature in the early January, the average relative humidity and sunshine duration in the middle of January, the days that average temperature less than 4℃ in the early February were the key meteorological factors affecting the picking period of 'Wuniuzao'. The absolute error value of forecast result and the actual error were mostly within 1d. Stepwise regression forecast model has actual production guidance, and can provide the local tea farmers and local tea enterprise picking advice.

Key words: Gaochun, spring tea, Wuniuzao, picking period, meteorological factor, forecast model