Optimization of TLC Identification Method of Angelicae Sinensis Radix
The purpose of this study was to optimize the thin layer chromatography(TLC)identification method of Angelicae Sinensis Ra-dix,and establish a new method to provide a better scheme for the identification of Angelicae Sinensis Radix.In this experiment,silica gel G thin layer plate was used,and ligustilide,ferulic acid and angelica were used as controls.The effects of different developing agents,chro-mogenic agents and temperature and humidity were investigated to determine the preparation method and optimal thin layer chromatography conditions of angelica test solution.The results showed that the volatile oil components in Angelicae Sinensis Radix,with petroleum ether(60 ℃～90 ℃)-ethyl acetate(volume ratio of 8.5∶1.5)as the developing agent,were examined under 365 nm ultraviolet lamp.In the sol-ution chromatography of the test sample,the same fluorescent spots were shown on the corresponding positions of the ligustilide reference substance and the Angelicae Sinensis Radix reference material.The ethyl ether extract of Angelica Sinensis was examined under 365 nm ultraviolet lamp with cyclohexane-ethyl acetate-glacial acetic acid(volume ratio of 7∶2∶1)as the developing agent,and sprayed with 2％ferric chloride-2％potassium ferricyanide(volume ratio of 1∶1)solution.In the chromatogram of the test solution,the same color spots were shown at the corresponding positions of ferulic acid reference substance and Angelica Sinensis reference medicinal material.The n-butanol extract of Angelica Sinensis was examined under 254 nm UV lamp with ethyl acetate-trichloromethane-formic acid-glacial acetic acid-water(volume ratio of 15∶1∶1∶1∶1∶2)as the developing agent.The fluorescence spots of the same color were shown in the corresponding position of the sample solution and the reference medicinal material of Angelica Sinensis.This method is simple and easy to operate,the qualitative characteristics are obvious,the repeatability is good,and the effect is better than that of the existing pharmacopoeia method.
万方数据
维普
