人参叶总皂苷大孔树脂分离纯化工艺的近红外光谱在线监测模型及其含量测定

利用近红外(NIR)光谱技术研究并建立可在线监测人参叶皂苷类成分的大孔树脂分离纯化工艺的方法。建立人参皂苷Rg₁，Re和Rb₁的高效液相色谱(HPLC)含量测定方法，收集人参叶提取物的40%乙醇大孔树脂洗脱液，采集其近红外光谱信息，并用已建立的HPLC法测定其中人参皂苷Rg₁，Re和Rb₁的含量，结合偏最小二乘法(PLS)建立上述三种成分及人参总皂苷的定量分析模型。建模过程中，以决定系数(R2)，交叉验证均方根误差(RMSECV)为指标，确定用于建模的最优近红外波段和光谱预处理方法，结果表明人参皂苷Rg₁，Re，Rb₁及人参总皂苷模型的最佳建模波段均为12 000.8~7 499.8 cm-1，R2分别为0.988 7，0.960 3，0.990 5和0.970 1，RMSECV分别为0.059 7，0.072 2，0.004 88和0.075 5。将1个批次的人参叶提取物大孔树脂分离纯化工艺样品用于验证人参总皂苷定量分析模型的预测性能，总皂苷的NIR预测值和HPLC测定值的相关系数为0.992 8，平均预测回收率为100.52%，表明所建的模型预测效果良好。该法快速、简便、准确，可用于生产工艺过程中人参总皂苷的含量测定和质量控制。

Establishment of the Model for Online Monitoring of the Column Separation and Purification Process by Near-Infrared Spectroscopy and Determination of Total Ginsenosides in Folium Ginseng

A method was developed for online monitoring of the constituents of ginsenoside of Folium Ginseng in the column separation and purification process using near-infrared (NIR) spectroscopy technology. Determination method of ginsenoside Rg₁, Re and Rb₁ was developed by high performance liquid chromatography (HPLC). After collecting 40%-ethanol eluant, their NIR spectra were detected and the contents of Rg₁, Re and Rb₁ were determined by the above HPLC method. The quantitative analysis models of the above three compounds and the total ginsenosides were established using partial least squares (PLS). During modeling, coefficient of determination (R2) and root mean square errors of cross-validation (RMSECV) were regarded as the indexes to select optimal wave numbers and preprocessing methods. The optimal wave numbers of ginsenoside Rg₁, Re, Rb₁ and total ginsenosides were all in the range of 12 000.8~7 499.8 cm-1; R2 were 0.988 7, 0.960 3, 0.990 5 and 0.970 1, respectively; RMSECV were 0.059 7, 0.072 2, 0.004 88 and 0.075 5, respectively. A lot of samples, collected during the column separation and purification process of Folium Ginseng extract, were used to validate the predicttion effect of quantitative analysis model of total ginsenosides. As a result, the correlation coefficient of NIR predicted value and HPLC value of total ginsenosides was 0.992 8 and the mean prediction recovery was 100.52%, which indicated that the prediction effect of the developed model was satisfactory. This method was proved to be fast, convenient and precise. It can be used for assaying and quality control of total ginsenosides in manufacture.