茶叶中茶多酚和生物碱的测定及聚类和线性判别分析

目的：建立一种反相高效液相色谱方法，测定绿茶、乌龙茶、红茶、白茶和普洱茶中儿茶素[(+)-catechin，C]、表儿茶素[(-)-epicatechin，EC]、表儿茶素没食子酸脂[(-)-epicatechin gallate，ECG]、表没食子儿茶素[(-)-epigallocatechin，EGC]、表没食子儿茶素没食子酸脂[(-)-epigallocatechin gallate，EGCG]、没食子酸(gallic acid，GA)、咖啡因(caffeine，CAF)、可可碱(theobromine，THEO)的水平。以这8 种组分为指标对茶叶进行聚类分析和线性判别分析，建立区分绿茶、红茶和乌龙茶的方法。方法：茶叶提取后采用HPLC 法测定儿茶素和生物碱含量，色谱柱为C18 柱，流动相由甲醇(A)、2% 的乙酸(B)等度洗脱，A、B 相的体积比为25:75，流速为1mL/min，柱温30℃。采用PDA 检测器在278nm 检测，参考波长为210nm。采用SPSS 14.0 对实验数据进行了聚类分析和线性判别分析。结果：在选择的分析条件下，样品中的8 种组分获得了理想分离， 加标回收率在8 7%～ 112.8%之间，并采用外标法对8 种组分进行定量。以这8 种组分的含量为指标，聚类分析和线性判别分析能对39 种茶叶样品进较好的区分。

Determination of Polyphenols and Alkaloids in Tea and Cluster-Linear Discrimination Analysis

Objective: To establish a HPLC method for the determination of (+)-catechin, (-)-epicatechin (EC), (-)-epicatechin gallate (ECG), (-)-epigallocatechin (EGC), (-)-epigallocatechin gallate (EGCG), gallic acid (GA), caffeine (CAF) and theobromine (THEO) in green, oolong and black tea samples, and to develop a discrimination method for green, oolong and black tea by cluster analysis and linear discrimination analysis on the basis of determined chemical components. Methods: Tea samples were extracted by 70% aqueous methanol. Totally 200 mg of grinded tea samples was extracted with 5 mL of 70% aqueous methanol for 10 min in 70 ℃water bath. The extract was centrifuged at 3500 r/min for 10 min, and the supernatant was collected. Then the precipitate was extracted with 5 mL of 70% methanol under the same conditions. The supernatants were combined in a volumetric flask and diluted to 10 mL. A total of 2 mL of such solution was diluted by 5 times with stabilizing solution, filtrated with 0.45 μm membrane, and then used for HPLC analysis. Eight compounds were separated by a C18 column using a mobile phase containing methanol-2% aqueous acetic acid at a ratio of 25:75 (V/V) in an isocratic elution at 30 ℃, and detected using a photodiode array detector at 278 nm with the reference wavelength at 210 nm. The cluster and linear discrimination analyses were performed using SPSS 14.0 software. Results: Eight compounds in all tea samples were well separated under the proposed conditions. The recovery rates of spiked samples were in the range of 87%－112.8%. The contents of 8 compounds determined by an external standard method were used to conduct cluster analysis and linear discrimination analysis. The good differentiation of green, oolong and black tea samples were achieved. Conclusion: This established method is feasible to discriminate green, oolong and black tea.