崂山春茶气候品质评价方法研究
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青岛市气象局科研项目(2022qdqxm03)资助


Research on Evaluation Method of Climate Quality of Laoshan Spring Tea
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    摘要:

    基于农业气象田间试验方法,选取崂山大田春茶群体种和龙井43两个主栽品种,于2022年、2023年两年连续观测,各采集17个检测样本、68个重复,检测其主要生化成分:咖啡碱、氨基酸、茶多酚和酚氨比。将各生化成分与采茶日前1~20 d的气温、日照、相对湿度等逐日平均气象资料分别做相关分析、回归分析等,结果表明:①春茶两个品种的咖啡碱、氨基酸、茶多酚和酚氨比与采茶日前1~20 d的气象因子存在显著的相关关系,相关系数分别通过了0.05、0.01的显著性检验,不同茶树品种的生化成分与相关气象因子基本一致,但影响时段存在差异。②建立了茶多酚、氨基酸、酚氨比与气象因子的最优回归方程,群体种茶多酚、氨基酸、酚氨比的平均预报准确率分别为88.5%、94.6%、96.4%;龙井43茶多酚、氨基酸、酚氨比的平均预报准确率分别为88.6%、92.9%、97.5%.③构建了崂山春茶气候品质评价指标。对酚氨比和氨基酸样本做K-平均值聚类分析,划分了崂山春茶气候品质的4个等级,根据不同等级一一对应的酚氨比气象指标,构建了两组崂山春茶气候品质评价指标;根据建立的酚氨比预报方程的不同阈值可以预报崂山春茶气候品质的等级。本研究为崂山春茶气候品质评价提供技术支撑,具有较高的实用性和可操作性,同时面向崂山茶产业,提高春茶的竞争力与附加值,助力乡村振兴。

    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.

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刘春涛,薛晓萍,朱俊翰,项英朔.崂山春茶气候品质评价方法研究[J].气象科技,2024,52(6):890~897

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  • 收稿日期:2023-11-28
  • 定稿日期:2024-10-09
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  • 在线发布日期: 2024-12-25
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