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近红外反射光谱法在同时预测绿茶叶片中生物碱和酚类物质的应用。

Application of near-infrared reflectance spectroscopy to the simultaneous prediction of alkaloids and phenolic substances in green tea leaves.

作者信息

Schulz H, Engelhardt U H, Wegent A, Drews H, Lapczynski S

机构信息

Institute for Quality Analysis, Federal Research Center for Breeding Research on Cultivated Plants, Neuer Weg 22-23, D-06484 Quedlinburg, Germany.

出版信息

J Agric Food Chem. 1999 Dec;47(12):5064-7. doi: 10.1021/jf9813743.

DOI:10.1021/jf9813743
PMID:10606573
Abstract

A near-infrared reflectance spectroscopic (NIRS) method for the prediction of polyphenol and alkaloid compounds in the leaves of green tea [Camellia sinensis (L.) O. Kuntze] was developed. Reference measurements of the individual catechins, gallic acid, caffeine, and theobromine were performed by reversed-phase HPLC. The total polyphenols were determined according to the colorimetric Folin-Ciocalteu assay. Using the partial least-squares algorithm, very good calibration statistics were obtained for the prediction of gallic acid, (-)-epicatechin, (-)-epigallocatechin, (-)-epicatechin gallate, (-)-epigallocatechin gallate, caffeine, and theobromine (R(2) > 0.85) with standard deviation/standard error of cross-validation (SD/SECV) ratio ranging from 2.00 to 6.27. Simultaneously, the dry matter content of the tea leaves can be analyzed very precisely (R(2) = 0.94; SD/SECV = 4.12). Furthermore, it is possible to discriminate tea leaves of different age by principal component analysis on the basis of the received NIR spectra. Prediction of the total polyphenol content is performed with a lower accuracy, which might be due to the lack of specificity in the colorimetric reference method. The study demonstrates that NIRS technology can be successfully applied as a rapid method not only for breeding and cultivation purposes but also to estimate the quality and taste of green tea and to control industrial processes, for example, decaffeination.

摘要

开发了一种近红外反射光谱法(NIRS),用于预测绿茶[茶树(L.)O. Kuntze]叶片中的多酚和生物碱化合物。通过反相高效液相色谱法对各儿茶素、没食子酸、咖啡因和可可碱进行参考测量。根据比色法福林-西奥尔特法测定总多酚含量。使用偏最小二乘算法,在预测没食子酸、(-)-表儿茶素、(-)-表没食子儿茶素、(-)-表儿茶素没食子酸酯、(-)-表没食子儿茶素没食子酸酯、咖啡因和可可碱时获得了非常好的校准统计数据(R²>0.85),交叉验证的标准偏差/标准误差(SD/SECV)比值在2.00至6.27之间。同时,可以非常精确地分析茶叶的干物质含量(R² = 0.94;SD/SECV = 4.12)。此外,基于获得的近红外光谱,通过主成分分析可以区分不同年龄的茶叶。总多酚含量的预测精度较低,这可能是由于比色参考方法缺乏特异性所致。该研究表明,近红外光谱技术不仅可以作为一种快速方法成功应用于育种和栽培目的,还可以用于评估绿茶的品质和口感以及控制工业过程,例如脱咖啡因。

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