Research on Evaluation Method of Climate Quality of Laoshan Spring Tea
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Abstract:
Based on the field experiment method of agricultural meteorology, two main cultivars: Laoshan Datian spring tea population and Longjing 43, are selected for research. Using two consecutive years of observations from 2022-2023, 17 test samples and 68 replicates are collected for Laoshan Datian spring tea population and Longjing 43 to detect their biochemical components such as caffeine, amino acids, tea polyphenols, and phenol ammonia ratio. We establish the climate evaluation indicators for Laoshan spring tea by conducting correlation analysis and regression analysis of each biochemical component with the daily average meteorological data of temperature, sunshine, and relative humidity of 1-20 days before tea picking. The results show that: (1) There is a significant correlation between caffeine, amino acids, tea polyphenols, and phenol ammonia ratio of the two varieties of Laoshan spring tea and meteorological factors of 1-20 days before tea picking. The correlations pass the 0.05 and 0.01 significance tests, respectively. The main meteorological factors affecting the different biochemical components are basically constant; however, different meteorological factors have different primary times of action. (2) We establish an optimal regression model for tea polyphenols, amino acids, phenol ammonia ratio, and meteorological factors. The results of the forecasting equations show that: the average prediction accuracies of polyphenols, amino acids, and phenol ammonia ratio of tea from Laoshan Datian spring tea population are 88.5%, 94.6% and 96.4%, respectively; and those of polyphenols, amino acids, and phenol ammonia ratio of Longjing 43 are 88.6%, 92.9% and 97.5%, respectively. (3) We further establish the climate evaluation indicators for Laoshan spring tea: by conducting the K-means clustering analysis on phenol ammonia ratio and amino acid samples, four grades of Laoshan spring tea have been classified. Climate quality evaluation indicators for Laoshan spring tea are established based on the corresponding phenol ammonia ratio meteorological indicators for each grade. Combined with the forecasting equation of Laoshan Datian spring tea population and Longjing 43, we can determine the different levels of climate quality of Laoshan tea by predicting the threshold of phenol ammonia ratio. The purpose of this study is to provide technical support for the evaluation of spring tea climate quality in Laoshan, which is very important and highly practical. At the same time, it is aimed at the Laoshan tea industry, which is conducive to improving the competitiveness and adding value of spring tea. This helps to contribute to rural revitalisation.