“辨状论质”看中药材苦杏仁走油

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“辨状论质”看中药材苦杏仁走油

作者：拱健婷赵丽莹

来源：《中国中药杂志》2016年第23期

[摘要]通过苦杏仁走油前后的质量比较，探讨苦杏仁走油变质现象的感官判别及其物质内涵。该研究对苦杏仁样品走油前后的脂肪油含量、酸值、过氧化值进行了测定，并采用HPLC，GCMS分别检测了苦杏仁苷、苦杏仁脂肪酸等。利用电子感官仪器（色度仪、电子鼻）量化并对比苦杏仁样品走油前后的颜色、气味；同时与上述结果作相关性分析。结果显示苦杏仁走油后颜色由黄白变棕黄，出现酸味；苦杏仁苷含量下降，酸值、过氧化值显著增高，脂肪酸成分发生变化；药材的外表特征与内在质量的变化具有显著相关性。“感官分析质量鉴别系统” 能为预测中药化学成分的含量、初步判断中药优劣及质量实时监测提供一定科学依据；为中药贮藏的“事先预测、事中干预、事后鉴别”提供新的思路与参考。

[关键词] 苦杏仁；走油；辨状论质；电子鼻；色度仪；质量评价； GCMS

Rancidness of Armeniacae Semen Amarum involving Bianzhuang Lunzhi

GONG Jianting1， ZHAO Liying1， Rudolf Bauer2， MI Wenjuan1， LI Yang1，

LI Jiahui1， REN Zhiyu1， XU Dong1， ZHAO Ting1*， YAN Yonghong1*

（1School of Chinese Pharmacy， Beijing University of Chinese Medicine， Beijing 100102，China；

2Institute of Pharmaceutical Science， University of Graz， Graz 8010， Austria）

[Abstract]This article aims to compare the qualities of Armeniacae Semen Amarum before and after rancidness， in order to study the rancidness of Armeniacae Semen Amarum In the experiment， content of fatty oil， acid value and peroxide value were determined before and after rancidness，respectively Meanwhile， HPLC， GCMS were utilized to analyze laetrile and fatty acid components Besides， colorimeter and enose were introduced to quantify and compare "color and odor" A correlation analysis was conducted on the above results The results showed that color of postrancidness Armeniacae Semen Amarum changed from yellow to brown， with sour and lower content of laetrile On the contrary， acid and peroxide values increased significantly， with changes in fatty acid component There was a considerable correlation between appearance characteristics and changes in internal quality The "sensory analysisquality identification system" can provide a certain scientific basis for prediction of the content of chemical components in traditional Chinese medicine， preliminary judgment of quality of traditional Chinese medicine and realtime quality monitoring， which offers us novel ideas and reference for storage principles of traditional Chinese medicines of "preevent prediction， duringevent intervention and postevent identification"