[关键词]
[摘要]
目的 建立金银花提取过程多变量统计过程控制(MSPC)模型,对金银花提取过程进行在线监控。方法 采用近红外光谱(NIRS)仪在线采集多批次金银花提取过程光谱数据,结合MSPC技术建立统计模型,采用主成分得分、Hotelling T2和DModX控制图来监测投料及过程操作参数等异常波动。此外,利用过程光谱进行主成分分析(PCA),建立了金银花提取过程轨迹,反映了提取过程随时间变化的趋势。结果 应用建立的MSPC模型可观测到金银花提取过程的质量变化,对正常批次的监控未出现误报,稳定性和重复性良好。3种控制图联合使用可及时准确地识别异常情况的发生。与传统的监控方法相比,该方法快速无损,且可实现在线实时监控。结论 NIRS结合MSPC技术可成功应用于金银花提取过程,对提升中药生产质量控制水平有重要的意义。
[Key word]
[Abstract]
Objective To develop a multivariate statistical process control (MSPC) model for in-line monitoring of the extraction process of Lonicerae Japonicae Flos (LJF).Methods The spectral data collected by near infrared spectrascopy coupled with MSPC technique were applied to establish the statistical model. Three kinds of multivariate control charts (PC scores, Hottelling T2 and DModX) were used to monitor the abnormal variations caused by the change of starting material quality attributes and abnormal operation conditions. Moreover, the extraction process trajectory was developed by applying principal component analysis on the process spectra, reflecting the changing trend with extraction time. Results The MSPC model with good repeatability and robustness could show the quality variation of extraction process of LJF and accurately predict the normal batches. The joint use of three control charts could effectively identify the abnormal conditions. Compared with the traditional monitoring methods, this approach was fast and nondestructive, and can implemente the in-line and real-time monitoring. Conclusion The near infrared spectroscopy combined with MSPC can be successfully applied to the extraction processes of LJF, which is of great significance for the improvement of the quality control of Chinese material medica (CMM).
[中图分类号]
[基金项目]
国家科技部"国家重大新药创制"项目:现代中药创新集群与数字制药技术平台(2013ZX09402203)