黄凯毅;魏丹妮;方金阳;李晞瑗;严斌俊;
HUANG Kai-yi;WEI Dan-ni;FANG Jin-yang;LI Xi-yuan;YAN Bin-jun;College of Pharmaceutical Science,Zhejiang Chinese Medical University;

• 1:浙江中医药大学药学院

摘要(Abstract)：

该研究建立了一种基于紫外光谱的醒脑静注射液一次提取过程分析方法,用于快速测定蒸馏提取液中异佛尔酮、4-亚甲基-异佛尔酮、莪术双环烯酮、莪术烯醇、莪术二酮、莪术酮、莪术呋喃二烯酮、莪术醇、吉马酮9种成分含量。在醒脑静注射液一次提取过程中收集郁金-栀子水蒸气蒸馏液样品166份,扫描紫外光谱,并用高效液相色谱测定9种成分含量,使用最小二乘支持向量机和径向基人工神经网络等方法建立紫外光谱与各成分含量之间的多元校正模型。实验结果表明,该研究建立的紫外光谱分析方法能较准确地测定蒸馏提取液中9种成分含量,预测误差均方根分别为0.068,0.147,0.215,0.319,1.01,1.27,0.764,0.147,0.610 mg·L~(-1)。该方法具有快速、简便、低成本的优点,有助于醒脑静注射液提取过程监测和提取终点判断,减少产品质量缺陷和质量差异。
In this study,an analytical method based on ultraviolet spectroscopy was established for the rapid determination of nine components including isophorone,4-methylene-isophorone,curcumenone,curcumenol,curdione,curzerenone,furanodienone,curcumol and germacrone in the first extraction process of Xingnaojing injection. 166 distillate samples of Gardeniae Fructus and Radix Curcumae were collected in the first extraction process of Xingnaojing injection. The ultraviolet spectra of these samples were collected,and the contents of the nine components in these samples were determined by high performance liquid chromatography. Least squares support vector machine and radial basis function artificial neural network were used to establish the multivariate calibration models between the ultraviolet spectra and the contents of the nine components. The results showed that the established ultraviolet spectrum analysis method can determine the contents of the nine components in the distillates accurately,with root mean square error of prediction of0. 068,0. 147,0. 215,0. 319,1. 01,1. 27,0. 764,0. 147,0. 610 mg·L-1,respectively. This proposed method is a rapid,simple and low-cost tool for the monitoring and endpoint determination of the extraction process of Xingnaojing injection to reduce quality defects and variations.

关键词(KeyWords)： 醒脑静注射液;紫外光谱;过程分析;郁金;栀子;水蒸气蒸馏;支持向量机;人工神经网络
Xingnaojing injection;ultraviolet spectroscopy;process analysis;Curcumae Radix;Gardeniae Fructus;hydrodistillation;least squares support vector machine;radial basis function artificial neural network

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(81703462);; 浙江省重中之重一级学科——中药学学科科研开放基金项目(Yao2016008);; 浙江中医药大学校级科研基金项目(2015ZR04)

作者(Author): 黄凯毅;魏丹妮;方金阳;李晞瑗;严斌俊;
HUANG Kai-yi;WEI Dan-ni;FANG Jin-yang;LI Xi-yuan;YAN Bin-jun;College of Pharmaceutical Science,Zhejiang Chinese Medical University;

Email:

DOI: 10.19540/j.cnki.cjcmm.20170907.015

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