中药材三七提取液近红外光谱的支持向量机回归校正方法

提出近红外光谱的支持向量机回归校正建模方法.以中药材三七渗漉提取液为实际分析对象,对其近红外光谱数据进行预处理和主成分分析后,用支持向量机回归算法建立人参皂苷Rg1,Rb1和Rd以及三七总皂苷的近红外光谱校正模型.以Rg1,Rb1和Rd的HPLC测定值及三七总皂苷的比色法测定值为参照,将本文方法与偏最小二乘回归和径向基神经网络建模方法相比较,结果表明,本文所建模型的预测准确性优于后两者,可推广应用于中药提取过程的近红外光谱分析.

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

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.