摘要
目的建立艾叶中9种挥发性成分的含量测定方法,比较不同产地艾叶挥发性成分的差异。方法采用水蒸气蒸馏法提取艾叶挥发性成分,色谱柱为HP-5(30 m×0.32 mm,0.25μm),程序升温:初始温度为60℃,先以3℃·min^(-1)的速率升温至120℃,再以15℃·min^(-1)的速率升温至250℃,载气流速为1 mL·min^(-1)。结果α-蒎烯、桉油精、侧柏酮、樟脑、龙脑、4-萜品醇、α-萜品醇、反式石竹烯、氧化石竹烯在各自的质量浓度范围内与测定值线性关系良好,平均加样回收率均在90.8%~98.2%。聚类分析中20批艾叶样品分为2类,不同类别艾叶主要差异成分为樟脑、龙脑、反式石竹烯、侧柏酮。结论该方法操作便捷、重复性好,可用于艾叶挥发性成分的质量评价。
Objective To establish a gas chromatography(GC)method to determine the content of 9 volatile components in artemisia argyi,to compare the volatile components of artemisia argyi from different origins.Methods The volatile oil of artemisia argyi was extracted by steam distillation.GC was performed on HP-5(30 m×0.32 mm,0.25μm)chromatographic column.The column temperature was set as follows:initial temperature strated at 60℃,increased to 120℃at the rate of 3℃·min^(-1),and then to 250℃at 15℃·min^(-1).The flow rate of carrier gas was 1 mL·min^(-1).Results Eucalyptus essence,α-pinene,platycladone,camphor,borneol,4-terpineol,α-terpineol,trans caryophyllene and oxidized caryophyllene had good linearity in the range of mass concentration,and the average recoveries ranged 90.8%~98.2%.Cluster analysis showed that 20 batches of artemisia argyi were belonged to 2 categories.The partial least squares discriminant analysis showed that the differences in the compositions of artemisia argyi were mainly caused by platycladone,camphor,trans caryophyllene and platycladone.Conclusion The method is convenient and accurate,and can be used for the quality evaluation of volatile components in artemisia argyi.
作者
张文静
李海燕
王晓伟
王海波
李桂本
李向阳
耿怡玮
ZHANG Wen-jing;LI Hai-yan;WANG Xiao-wei;WANG Hai-bo;LI Gui-ben;LI Xiang-yang;GENG Yi-wei(Henan Institute for Drug and Medical Device Inspection(Henan Vaccine Issuance Center),NMPA Key Laboratory for Quality Control of Traditional Chinese Medicine,Zhengzhou 450008)
出处
《中南药学》
CAS
2023年第12期3305-3309,共5页
Central South Pharmacy
基金
中国药品监管科学行动计划第二批重点项目(No.NMPAJGKX-2023-030)
河南省科技厅科技攻关项目(No.222102310110)。
关键词
艾叶
气相色谱法
挥发性成分
含量测定
聚类分析
正交偏最小二乘判别分析
artemisia argyi
gas chromatography
volatile component
content determination
cluster analysis
orthogonal partial least squares discriminant analysis
