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Simultaneous Analysis Of Main Catechins Contents In Green Tea (camellia Sinensis (l.)) By Fourier Transform Near Infrared Reflectance (ft-nir) Spectroscopy

机译:傅立叶变换近红外反射光谱法同时分析绿茶中主要儿茶素的含量

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This paper reported the results of simultaneous analysis of main catechins (i.e., EGC, EC, EGCG and ECG) contents in green tea by the Fourier transform near infrared reflectance (FT-NIR) spectroscopy and the multivariate calibration. Partial least squares (PLS) algorithm was conducted on the calibration of regression model. The number of PLS factors and the spectral preprocessing methods were optimised simultaneously by cross-validation in the model calibration. The performance of the final model was evaluated according to root mean square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP) and correlation coefficient (R). The correlations coefficients (R) in the prediction set were achieved as follows: R = 0.9852 for EGC model, R = 0.9596 for EC model, R= 0.9760 for EGCG model and R = 0.9763 for ECG model. This work demonstrated that NIR spectroscopy with PLS algorithm could be used to analyse main catechins contents in green tea.
机译:本文报道了通过傅立叶变换近红外反射(FT-NIR)光谱法和多元校正对绿茶中主要儿茶素(即EGC,EC,EGCG和ECG)进行同时分析的结果。对回归模型进行了校正的偏最小二乘(PLS)算法。在模型校准中通过交叉验证同时优化了PLS因子的数量和光谱预处理方法。根据交叉验证的均方根误差(RMSECV),预测的均方根误差(RMSEP)和相关系数(R)评估最终模型的性能。预测集中的相关系数(R)如下获得:EGC模型的R = 0.9852,EC模型的R = 0.9596,EGCG模型的R = 0.9760,ECG模型的R = 0.9763。这项工作表明,采用PLS算法的NIR光谱可用于分析绿茶中的主要儿茶素含量。

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