基于近红外光谱的驴胶补血颗粒浓缩过程研究

目的采用近红外光谱(NIRS)技术检测驴胶补血颗粒(LBG)浓缩过程中的固含量、总多糖质量浓度和阿魏酸质量浓度3个质控指标,建立LBG浓缩过程中多质控指标的快速定量分析方法。方法分别采用称量法测定固含量,苯酚-硫酸法测定总多糖,HPLC法测定阿魏酸;以LBG浓缩过程中固含量、总多糖质量浓度和阿魏酸质量浓度为质控指标,利用偏最小二乘(PLSR)法进行参数优化,并建立定量校正模型。结果各个指标的校正模型相关系数(r)均大于0.945 0。RMSEP和RMSEV非常接近,并且RSEP值均小于10%。建立的PLSR模型具有模型性能好、预测精度高的优点。结论 NIRS技术结合化学计量学在LBG浓缩过程的质量控制中具有潜在的应用价值。

Study on concentrating process of Lvjiao Buxue Granule by near infrared spectroscopy

Objective To establish rapid quantitative analysis models of multiple indicators for quality control in the concentrating process of Lvjiao Buxue Granule (LBG) by means of near infrared spectroscopy (NIRS). Methods The solid content (SC), total polysaccharides concentration (TPC), and ferulic acid concentration (FAC) were determined by weighing method, phenol-sulfuric acid method, and HPLC method, respectively. Calibration models of them were established with partial least squares regression (PLSR) method. The established models were applied to predicting the unknown samples for testing the performance of the models. Results The correlation coefficients (r) of SC, TPC, and FAC were all above 0.945 0. The root mean square error in calibration (RMSEC) and root mean square error in prediction (RMSEP) were very close, and the relative standard errors of predictions (RSEP) were all less than 10%, indicating that the models predicted and performed well. Conclusion NIRS technique combined with chemo metrics can provide a novel efficient and environmental approach for the fast simultaneous determination of key quality indicators friendly, and have the potential application value in the concentration process of LBG.