APPLICATION OF ALGORITHMS OF WAVELET TRANSFORM (WT)-ARTIFICIAL NEURAL NETWORK (ANN) AND WT-ROBUST REGRESSION (RR) TO HPLC DETERMINATION OF INDIGO AND INDIRUBIN
摘 要
提出了小波变换-人工神经网络(WT-ANN)和小波变换-稳健回归(WT-RR)两算法的数学模型,并应用于高效液相色谱法测定板蓝根、大青叶及中成药复方板蓝根颗粒中靛蓝及靛玉红的测定,从而避免了繁琐的分离,实现了被测组分的直接、同时测定.所用色谱柱为Extend C18(4.6 mm×250 mm,5 μm),所用流动相为甲醇与水(95+5)的混合溶液.由测得的相对标准偏差(RSD)可知两算法均可用于试样中多组分的测定,但WT-ANN法(RSD<0.6%)稍优于WT-RR法(RSD<2.5%).三种实样的分析应用中,回收率在98.8%~101.5%之间.此方法可作为工业生产中在线分析法.
Abstract
Two algorithms of WT-ANN and WT-RR were modelled and applied to HPLC determination of indigo and indirubin in root and leaves of isatis and in ready-prepared Chinese Medicine called “Balangen” compound granules,making it possible to avoid the tedious separation and to determine these two components directly and simultaneously.The components to be determined were extracted from the sample with chloroform,and the extract was concentrated to a volume of 10 mL quantitatively and the solution was ready for HPLC determination.The Extend C18 (4.6 mm×250 mm,5 μm) chromatographic column and a mobile phase of mixed solution of CH3OH and H2O (95+5) were used in the determination.As shown by the RSD′s obtained,both of the algorithms were satisfactory for the analysis of multi-components in a sample,but WT-ANN (RSD<0.6%) was better than WT-RR (RSD<2.5%) in the application.In the analysis of 3 substantial samples,recoveries in the range of 98.8%-101.5% were obtained.It was shown that the proposed method was feasible to be used as a method of on line analysis in the production-process.
中图分类号 O657.37
所属栏目 试验与研究
基金项目 辽宁省教委基金(No.2004003)
收稿日期 2005/9/30
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备注王秀云(1978-),女,沈阳人,日本埼玉工业大学在读博士,研究方向为化学计量学.
引用该论文: WANG Xiu-yun,LI Jing-hui,YU Hong-mei,CHEN Guo-shun,ZHAO Hong-xia. APPLICATION OF ALGORITHMS OF WAVELET TRANSFORM (WT)-ARTIFICIAL NEURAL NETWORK (ANN) AND WT-ROBUST REGRESSION (RR) TO HPLC DETERMINATION OF INDIGO AND INDIRUBIN[J]. Physical Testing and Chemical Analysis part B:Chemical Analysis, 2006, 42(9): 699~701
王秀云,李井会,于洪梅,陈国顺,赵红霞,高丽娟,吴秀红. 小波变换-人工神经网络用于反相高效液相色谱法同时测定靛蓝和靛玉红[J]. 理化检验-化学分册, 2006, 42(9): 699~701
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