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Quantitative Analysis of Panax ginseng by FT-NIR Spectroscopy

机译:FT-NIR光谱定量分析人参

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Near-infrared spectroscopy (NIRS), a rapid and efficient tool, was used to determine the total amount of nine ginsenosides in Panax ginseng. In the study, the regression models were established using multivariate regression methods with the results from conventional chemical analytical methods as reference values. The multivariate regression methods, partial least squares regression (PLSR) and principal component regression (PCR), were discussed and the PLSR was more suitable. Multiplicative scatter correction (MSC), second derivative, and Savitzky-Golay smoothing were utilized together for the spectral preprocessing. When evaluating the final model, factors such as correlation coefficient (R-2) and the root mean square error of prediction (RMSEP) were considered. The final optimal results of PLSR model showed that root mean square error of prediction (RMSEP) and correlation coefficients (R-2) in the calibration set were 0.159 and 0.963, respectively. The results demonstrated that the NIRS as a new method can be applied to the quality control of Ginseng Radix et Rhizoma.
机译:近红外光谱(NIRS)是一种快速有效的工具,用于确定人参中九种人参皂甙的总量。在研究中,使用多元回归方法建立回归模型,并将常规化学分析方法的结果作为参考值。讨论了多元回归方法,偏最小二乘回归(PLSR)和主成分回归(PCR),PLSR更合适。乘法散射校正(MSC),二阶导数和Savitzky-Golay平滑一起用于光谱预处理。在评估最终模型时,考虑了相关系数(R-2)和预测均方根误差(RMSEP)等因素。 PLSR模型的最终最佳结果表明,校准集中的预测均方根误差(RMSEP)和相关系数(R-2)分别为0.159和0.963。结果表明,NIRS作为一种新方法可以应用于人参的质量控制。

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