Abstract Catechin polyphenols and caffeine play an important role in tea quality. This study analyzed the visible and near-infrared (Vis-NIR) spectral variation and concentration differences of catechin and caffeine of fresh tea leaves (Camellia sinensis L.) in three varieties and six leaf positions, and a universal spectral model for quickly and accurately measurement of the catechin and caffeine content in the various varieties and leaf positions was established. It was found that all the catechins and caffeine were significantly influenced by variety and leaf position. While, the Vis/NIR spectrum as an indication of internal biochemical substances was successfully used to distinguish different varieties and leaf positions with the discrimination accuracy rates of 98.15% and 100%, respectively. The quantitative relationship between the chemical components and the data obtained by Vis-NIR spectroscopy was established based on multivariate regression analysis such as partial least squares (PLS) and multiple linear regression (MLR). Furthermore, competitive adaptive reweighted sampling (CARS) and successive projections algorithm (SPA) were used to select the characteristic wavelengths for the development of simple models. Results showed that the quantitative determination models obtained good performance with the determination coefficients (R2) of 0.949, 0.893, 0.968, 0.931 and 0.917 for epigallocatechin gallate (EGCG), epicatechin gallate (ECG), epigallocatechin (EGC), epicatechin (EC) and caffeine (CAF), respectively. Such high detection accuracy shows that the spectral detection model has a strong applicability for both varieties and leaf positions. The overall results of the study revealed the potential use of Vis-NIR spectroscopy as a rapid, simple and non-destructive method for the determination of four main catechins and caffeine in fresh tea leaves, and it will play a great role in the real-time detection of tea physiological information in tea garden.

中文翻译：

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基于可见光和近红外光谱的鲜绿茶叶中四种主要儿茶素和咖啡因简易鉴别模型的建立

摘要 儿茶素多酚和咖啡因对茶叶品质起着重要作用。本研究分析了新鲜茶叶 (Camellia sinensis L.) 三个品种、六个叶位的儿茶素和咖啡因的可见光和近红外 (Vis-NIR) 光谱变化和浓度差异，并建立了一个通用光谱模型，可快速准确地建立了对不同品种和叶位置的儿茶素和咖啡因含量的测量。发现所有的儿茶素和咖啡因都受品种和叶位的显着影响。同时，Vis/NIR光谱作为内部生化物质的指示被成功用于区分不同品种和叶片位置，区分准确率分别为98.15%和100%。基于偏最小二乘法(PLS)和多元线性回归(MLR)等多元回归分析，建立了化学成分与Vis-NIR光谱数据之间的定量关系。此外，竞争性自适应重加权采样 (CARS) 和连续投影算法 (SPA) 用于选择用于开发简单模型的特征波长。结果表明，该定量测定模型对表没食子儿茶素没食子酸酯（EGCG）、表儿茶素没食子酸酯（ECG）、表没食子儿茶素（EGC）、表儿茶素（EC）和咖啡因（CAF），分别。如此高的检测精度表明光谱检测模型对品种和叶位都有很强的适用性。该研究的总体结果表明，可见-近红外光谱作为一种快速、简单和无损测定新鲜茶叶中四种主要儿茶素和咖啡因的方法具有潜在的应用价值，并将在实际应用中发挥重要作用。茶园茶叶生理信息的时间检测[J].