近红外光谱法快速检测绿茶中儿茶素的含量

提出了一种应用傅里叶近红外漫反射光谱分析技术快速检测茶叶中主要儿茶素含量的新方法.首先获取茶叶在10000～4000 cm<'-1>范围的近红外漫反射光谱,然后以高效液相色谱分析值作参考值.采用偏最小二乘法建立茶叶中表没食子儿茶素没食子酸酯(EGCG)、表儿茶素没食子酸酯(ECG)和表没食子儿茶素(EGC)含量的定量分析模型.通过交互验证方法来优化模型的主成分数和所采用的光谱预处理方法.EGCG、ECG和EGC三个模型预测值和参考值问的相关系数分别为0.9800、0.9763和0.9853,预测均方根误差分别为0.3509、0.1147和0.1365.研究结果表明,近红外光谱技术可成功地检测茶叶中EGCG,ECG和EGC的含量.

Feasibility Study on Use of Near-Infrared Spectroscopy in Quantitative Analysis of Catechins in Green Tea

Near-infrared spectroscopy (NIR) combined with partial least squares (PLS) for the prediction of catechins compounds in the green tea was developed. The original spectra of tea in wavelength range of 10000～4000 cm-1 was acquired. Reference measurement of epigallocatechin gallate (EGCG), epicatechin gallate (ECG) and epigallocatechin (EGC) were performed by reversed-phase high-performance liquid chromatography (HPLC). PLS is used to perform the calibration models to predict the contents of EGCG, ECG and EGC. To decide upon the number of PLS factors included in the PLS model and the method of spectra preprocessing, the model with the lowest root mean square error of cross-validation (RMSECV) for the training set is chosen. The correlation coefficient between the predicted and the reference results for the test set is used as an evaluation parameter for the models. The results show that the correlation coefficients of the prediction models are 0.9800 for the EGCG, 0.9763 for the ECG and 0.9853 for the EGC, with root mean squared error of prediction (RMSEP) 0.3509, 0.1147 and 0.1365 respectively. The study demonstrates that NIR spectroscopy with PLS can be used sucessfully to determine the content of RGCG, RCG and EGC in green tea.