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Total Polyphenols in Green Tea Samples by FT-NIR Spectroscopy

机译:FT-NIR光谱法测定绿茶样品中的总多酚

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The feasibility of measuring total polyphenols content in instant green tea powder and green tea granules was investigated by Fourier Transform Near-Infrared (FT-NIR) Spectroscopy. The spectra were measured in diffused reflectance mode by keeping 8-10g samples in a small sample bottle. A partial least square regression model was developed with vector normalization as the pre-processing method in the NIR region (4000-12000 cm~(-1) or 800-2500 nm). The developed model was validated using a cross validation technique. FT-NIR Spectroscopy with chemometrics, using PLS - vector normalization as the pre-processing method - could predict the total polyphenols content in tea samples in terms of gallic acid accurately up to an R2 value of 0.978 and a standard error of cross validation (RMSECV) value of 1.45 with 4 factors in the prediction model. The developed model was applied to predict total polyphenols in green tea samples within 30-60 min. The developed procedure was further validated with fresh samples which were not used for calibration and compared with spectroscopic method of ployphenol determination. The overall results demonstrate that NIR Spectroscopy with multivariate calibration could be successfully applied as a rapid method not only to identify tea varieties but also to determine total polyphenols content in green tea samples.
机译:通过傅里叶变换近红外光谱(FT-NIR)光谱研究了测量速溶绿茶粉和绿茶颗粒中总多酚含量的可行性。通过将8-10g样品保存在一个小样品瓶中,以漫反射模式测量光谱。以向量归一化为研究对象,在NIR区域(4000-12000 cm〜(-1)或800-2500 nm)中建立了偏最小二乘回归模型。使用交叉验证技术验证了开发的模型。使用PLS-矢量归一化作为预处理方法的FT-NIR光谱化学计量学可以准确预测茶酸中没食子酸中茶多酚的总含量,R2值为0.978,且交叉验证的标准误差为(RMSECV )值1.45,并在预测模型中包含4个因素。将开发的模型用于预测30-60分钟内绿茶样品中的总多酚。所开发的程序用未用于校准的新鲜样品进一步验证,并与多酚测定的光谱法进行了比较。总体结果表明,具有多变量校准的NIR光谱技术可以成功地用作一种快速方法,不仅可以识别茶叶品种,而且可以确定绿茶样品中的总多酚含量。

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