嶗山春茶氣候品質評價方法研究
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青島市氣象局科研項目(2022qdqxm03)資助


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

    基于農業氣象田間試驗方法,選取嶗山大田春茶群體種和龍井43兩個主栽品種,于2022年、2023年兩年連續觀測,各采集17個檢測樣本、68個重復,檢測其主要生化成分:咖啡堿、氨基酸、茶多酚和酚氨比。將各生化成分與采茶日前1~20 d的氣溫、日照、相對濕度等逐日平均氣象資料分別做相關分析、回歸分析等,結果表明:①春茶兩個品種的咖啡堿、氨基酸、茶多酚和酚氨比與采茶日前1~20 d的氣象因子存在顯著的相關關系,相關系數分別通過了0.05、0.01的顯著性檢驗,不同茶樹品種的生化成分與相關氣象因子基本一致,但影響時段存在差異。②建立了茶多酚、氨基酸、酚氨比與氣象因子的最優回歸方程,群體種茶多酚、氨基酸、酚氨比的平均預報準確率分別為88.5%、94.6%、96.4%;龍井43茶多酚、氨基酸、酚氨比的平均預報準確率分別為88.6%、92.9%、97.5%.③構建了嶗山春茶氣候品質評價指標。對酚氨比和氨基酸樣本做K-平均值聚類分析,劃分了嶗山春茶氣候品質的4個等級,根據不同等級一一對應的酚氨比氣象指標,構建了兩組嶗山春茶氣候品質評價指標;根據建立的酚氨比預報方程的不同閾值可以預報嶗山春茶氣候品質的等級。本研究為嶗山春茶氣候品質評價提供技術支撐,具有較高的實用性和可操作性,同時面向嶗山茶產業,提高春茶的競爭力與附加值,助力鄉村振興。

    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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劉春濤,薛曉萍,朱俊翰,項英朔.嶗山春茶氣候品質評價方法研究[J].氣象科技,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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  • 在線發布日期: 2024-12-25
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