一种测定天然药物活性成分的HPLC-DAD计算分析方法

A Computational Analysis Method of HPLC-DAD for Determining the Active Components of Natural Medicine

将窗口因子分析所得结果作为初值,采用交替迭代进行窗口的自适应优化调整,以迭代逼近方法有效地解决了窗口选择难题.将其用于丹参中丹参酮、隐丹参酮和丹参酮A含量的HPLC-DAD分析测定,加样回收率分别达94.16%,91.57%和104.48%.计算机仿真和模拟中药物质体系的实验结果均表明,本方法分析结果受窗口偏差的影响较小,显著优于经典窗口因子分析法,可推广用于计算解析复杂样品色谱分析中出现的重叠峰.

Window factor analysis（WFA） is an important method used to resolve the overlapping chromatographic peaks by processing HPLC-DAD data. The selection of window is one of the key factors to affect the accuracy of WFA. In this paper, the results obtained by WFA are used as the initial estimation, and then the estimated value is adaptively optimized by an alternative iteration procedure. In this way, a method named iterative fitting windows factor analysis（IFWFA） is proposed. It can correctly select the window for using WFA. Coupled with HPLC-DAD, the proposed method was used to determine tanshinone Ⅰ , cryptotanshinone and tanshinone Ⅱ A of Salvia rniltiorrhiza, and the results show that their recoveries are 94.16%, 91.57% and 104.48%, respectively. Computer simulation and sample analysis experiments both demonstrate that the method is effective for improvement of analytical accuracy.