山鸡椒挥发油GC-MS指纹图谱及模式识别研究  

GC-MS Fingerprint and Chemical Pattern Recognition Analysis of Litsea cubeba(Lour.)Pers. Essential Oil

作　　者：斯林林[1,2] 汪阳东[2] 陈益存[2] 张静[1] 田胜尼[1] 

机构地区：[1]安徽农业大学生命科学学院,安徽合肥230036 [2]中国林业科学院亚热带林业研究所,浙江富阳311400

出　　处：《激光生物学报》2012年第5期453-457,共5页Acta Laser Biology Sinica

基　　金：国家林业局重点科研项目(2011-01)

摘　　要：为控制山鸡椒挥发油的质量,通过水蒸气蒸馏法分离出山鸡椒挥发油,利用GC-MS建立了山鸡椒挥发油的指纹图谱,并运用主成分分析和聚类分析对指纹图谱进行模式识别研究。结果显示16批样本图谱共匹配出27个共有峰,以此27个峰为评价指标,样本的相似度均大于0.98。对27个共有峰中的18个峰进行了定性,以此18个峰为评价指标,方法学考察结果较好,主成分分析和聚类分析结果基本一致。表明该方法建立的GC-MS指纹图谱具有良好的稳定性和可靠性。同时,模式识别显示不同产地间和同一产地内的山鸡椒挥发油都存在差异。To control the quality of L. cubeba essential oil, standard fingerprint of L. cubeba essential oil obtained by hydrodistillation was developed by using GC-MS. Principle component analysis and cluster analysis methods were em- ployed to recognize the fingerprint established. Twenty-seven peaks were found in the 16 batches of samples, among which 18 peaks were determined. The similarity analysis was conducted based on the 27 peaks. Validation of the meth- od, principle component analysis and cluster analysis were preformed according to the 18 peaks. It showed that the simi- larity degrees of all samples were more than 0.98, and the method was proved to be applicable for analyzing the finger- print. The principle component analysis was relatively consistent with that of cluster. The result indicated that the GC- MS fingerprint for L. cubeba essential oil here was stable and reliable. And the diversities of L. cubeba essential oil were observed not only in different production areas but also in the same production area in the light of the chemical pattern recognition.

关 键 词：山鸡椒挥发油 质量控制 指纹图谱 主成分分析 聚类分析 

分 类 号：Q946.85[生物学—植物学] R284.1[医药卫生—中药学]