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Simultaneous determination of total polyphenols and caffeine contents of green tea by near-infrared reflectance spectroscopy

机译:近红外反射光谱法同时测定绿茶中的总酚和咖啡因含量

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This paper indicates the possibility to use near infrared (NIR) spectroscopy as a rapid method to predict quantitatively the content of caffeine and total polyphenols in green tea. A partial least squares (PLS) algorithm is used to perform the calibration. To decide upon the number of PLS factors included in the PLS model, the model is chosen according to the lowest root mean square error of cross-validation (RMSECV) in training. The correlation coefficient R between the NIR predicted and the reference results for the test set is used as an evaluation parameter for the models. The result showed that the correlation coefficients of the prediction models were R=0.9688 for the caffeine and R=0.9299 for total polyphenols. The study demonstrates that NIR spectroscopy technology with multivariate calibration analysis can be successfully applied as a rapid method to determine the valid ingredients of tea to control industrial processes. (c) 2006 Elsevier B.V. All rights reserved.
机译:本文指出了使用近红外(NIR)光谱作为定量预测绿茶中咖啡因和总多酚含量的快速方法的可能性。偏最小二乘(PLS)算法用于执行校准。为了确定PLS模型中包含的PLS因子的数量,根据训练中交叉验证的最低均方根误差(RMSECV)选择模型。测试集的预测NIR与参考结果之间的相关系数R用作模型的评估参数。结果表明,咖啡因的预测模型的相关系数为R = 0.9688,总多酚的预测系数为R = 0.9299。研究表明,具有多变量校准分析的近红外光谱技术可以成功地用作确定茶的有效成分以控制工业过程的快速方法。 (c)2006 Elsevier B.V.保留所有权利。

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