薰衣草化学成分分析及差异标志物的识别

发布时间：2018-12-18 12:51

【摘要】：采用顶空固相微萃取-气相色谱-质谱(HS-SPME-GC/MS)联用技术,结合保留指数(RI),建立了新疆不同品种薰衣草化学成分的快速分析方法,并采用多元统计分析方法对不同品种薰衣草的特征差异性标志物进行识别。选取薰衣草挥发性化合物中顺-β-罗勒烯、芳樟醇、乙酸芳樟酯、萜品烯-4-醇、石竹烯和石竹烯氧化物等6个代表性成分进行方法考察,首先优化HS-SPME萃取条件,然后运用GC/MS法分析3个品种26批薰衣草花中挥发性成分,最后采用主成分分析(PCA)和偏最小二乘-判别分析(PLS-DA)对数据进行处理。结果显示:3个不同品种薰衣草样品间的化学成分得到有效区分;筛选识别出9个不同品种薰衣草间差异显著的化学成分标志物,薰衣草特征变量组分与差异标志物分析结果一致。这说明,SPME-GC/MS结合多元统计技术可以为薰衣草复杂体系的快速鉴定、差异标志物识别提供可行的方法参考。
[Abstract]:Using headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC/MS) and retention index (RI), a rapid analytical method for chemical constituents of different lavender varieties in Xinjiang was established. Multivariate statistical analysis was used to identify the characteristic difference markers of different lavender varieties. Six representative constituents of lavender volatile compounds, such as cis-尾-basil, linalool, camphor acetate, terpene-4-alcohol, caryophyllene and caryophyllene oxide, were investigated. The extraction conditions of HS-SPME were optimized. Then GC/MS method was used to analyze the volatile components in 26 lots of lavender flowers of three varieties. Finally, principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to process the data. The results showed that the chemical constituents of three different species of lavender were effectively distinguished. The chemical component markers of 9 different varieties of lavender were screened and identified, and the results of characteristic variables of lavender were consistent with those of the difference markers. This indicates that SPME-GC/MS combined with multivariate statistical technique can provide a feasible method for the rapid identification of lavender complex system and the identification of differential markers.
【作者单位】：新疆大学理化测试中心;
【基金】：国家自然科学基金(21565024) 新疆高校科研计划科学研究重点项目(XJEDU2012I14) 新疆大学博士科研启动基金(BS120135)资助
【分类号】：O657.63;R284

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