文献类型：期刊文献

中文题名：丹参多酚酸盐柱层析过程的近红外光谱在线检测及质量控制

英文题名：Near-infrared online monitoring and quality control of Salvianolate column separation

作者：杨辉华[1];王勇[1];吴云鸣[2];史晓浩[2];胡坪[3];梁琼麟[1];王义明[1];罗国安[1]

机构：[1]清华大学分析中心;[2]绿谷(集团)有限公司,上海201203;[3]华东理工大学化学与分子工程学院,上海200237

年份：2008

卷号：30

期号：3

起止页码：409

中文期刊名：中成药

外文期刊名：Chinese Traditional Patent Medicine

收录：CSTPCD;;北大核心:【北大核心2004】；CSCD:【CSCD2011_2012】；

基金：科技部十五攻关项目(No.2004BA721AB);广西科学基金(No.桂科青0542037);中国博士后基金(No.20060390494)资助

语种：中文

中文关键词：丹参多酚酸盐;柱层析;近红外光谱;过程分析技术

外文关键词：Salvianolate; column separation; near infrared spectrum; process analysis technique

摘要：目的:研究利用近红外光谱(NIR)结合HPLC含量测定对丹参多酚酸盐生产的关键工艺——柱层析进行在线质量分析及控制的可行性。方法:对NIR透射光谱和丹酚酸B的含量进行PLS回归分析,并系统考察光程、波数选择、预处理方法对建模效果的影响。结果:2 mm光程优于1 mm光程,在2 mm光程下,最优的波数范围为6 102.1-5 446.3cm-1、预处理方法为矢量归一化,对预测集样本的均方根误差为0.234 mg/mL、R2为0.995 2。结论:该方法快速、简便、准确,可用于生产过程在线检测及质量控制。
AIM ： To study the feasibility of online monitoring and controlling of the key process of column chromatographic separation in the production of Salvianolate by combining near-infrared （NIR） spectrum and HPLC fingerprinting. METHODS ： Partial Least Square （PLS） regression was used to model the correlation of NIR spectra with the concentrations of salvianolic acid B, and the influences of light path, wavelength selection, and preprocessing method on the PLS model were investigated systematically. RESULTS： A 2 mm light path was better than 1 mm one, and with 2 mm light path, the optimal wave-number was in the range of 6 102.1 -5 446.3 cm^-1 and the optimal preprocessing method was the vector normalization. The root mean-square error of PLS model on test samples was 0. 234 mg/mL, and R^2 was 0. 995 2. CONCLUSION： This method is proved to be fast, convenient, and precise. It can be used to online monitoring and quality control of the manufacturing of Salvianolate.