Predicting Tea Harvest Time by Using Climate Data before Budding Time

<p>Early prediction of the best harvest time and making a precise harvest plan is vital in tea cultivation, because harvest time has a substantial impact on tea quality. However, existing models are difficult to predict the best harvest time, even 2 weeks in advance. In addition, budding time needs to be known. Here we developed a linear multiple regression model to predict tea harvest time by using the integrated values of weather data before budding time (1 month before harvest time). The harvest times of the cultivars ‘Yabukita’, ‘Sayamakaori’, and ‘Okumidori’ planted in Uji City, Kyoto Prefecture over a period of 10 to 19 years were used. Climate components—daily mean relative humidity, daily precipitation, daily daylight hours, and one of the daily mean, maximum, and minimum air temperature—were selected via the stepwise method. All weather data combinations within 30 days from 1 March to the average budding time were used as the integration period. The best prediction model for each cultivar was selected, with the smallest mean absolute error (MAE) between the predicted and recorded harvest times of the validation data based on the leave-one-out cross-validation test (MAE_test). As a result, the MAE between the predicted and recorded harvest times ranged from 0.8 to 2.0 days, which was accurate enough for practical use. In addition, the MAE_test ranged from 1.2 to 2.3 days—less than that of our previous model trained with the integrated value of weather data after budding time. The best time to harvest tea could, therefore, be predicted approximately 1 month before harvest.</p>