A Method for Analysis of Extracting Solution of Panax Notoginseng Using Near-infrared Spectroscopy and Support Vector Regression

Abstract

Abstract: A new method for building near-infrared spectroscopy(NIRS) calibration model using support vector regression(SVR) was proposed. After NIRS data of the extracting solution of Panax notoginseng herb were processed with pretreatment and principal component analysis, NIRS calibration models of ginsenoside R_g1,R_b1, R_d and panax notoginseng saponins(PNS) were built by using SVR. The reference measurements of ginsenoside were performed by HPLC method for ginsenoside R_g1,R_b1, R_d and colourimetric method for PNS. The proposed method was compared with partial least square regression(PLSR) and radial-basis function neural network(RBFNN) modeling methods. The results showed that the predictive accuracy of NIR calibration models built by SVR was much better than that of the models built by PLSR and RBFNN. Therefore, the method could be applied to NIR analysis for extraction process of Chinese medicine.

Key words: Support vector machine, Near infrared spectroscopy, Analysis of Panax notoginseng, Process analytical chemistry, Multivariate calibration

CLC Number:

O652.31

TrendMD:

QU Hai-Bin, LIU Xiao-Xuan, CHENG Yi-Yu . A Method for Analysis of Extracting Solution of Panax Notoginseng Using Near-infrared Spectroscopy and Support Vector Regression[J]. Chem. J. Chinese Universities, 2004, 25(1): 39.

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A Method for Analysis of Extracting Solution of Panax Notoginseng Using Near-infrared Spectroscopy and Support Vector Regression

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