Zhang Li, Wang Xiaoyu, Guo Jizhao, Xia Qiaoling, Zhao Ge, Zhou Huina, Xie Fuwei
Zhengzhou Tobacco Research Institute of CNTC , Zhengzhou, People's Republic of China.
J Agric Food Chem. 2013 Mar 20;61(11):2597-605. doi: 10.1021/jf400428t. Epub 2013 Mar 8.
Tobacco leaf obtained from different geographical areas in China was profiled using gas chromatography-mass spectrometry (GC-MS) coupled with multivariate data analyses. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) showed that the tobacco metabolome was clearly dependent on geographical origins; climatic conditions, such as temperature and precipitation, imposed a greater impact on metabolite levels than the cultivars. By orthogonal partial least-squares-discrimination analysis (OPLS-DA), 20 metabolites that contributed to the discrimination were screened, including primary metabolites (sucrose, D-fructose, D-mannose, D-glucose, inositol, maleic acid, citric acid, malic acid, L-threonic acid, L-proline, L-phenylalanine), secondary metabolites (chlorogenic acid, α- and β-4,8,13-duvatriene-1,3-diol, nicotine, quinic acid), and four unknown metabolites. The results suggest that metabolic profiling using GC-MS combined with multivariate analysis can be used to discriminate tobacco leaf of different geographical origins and to provide potential indicators of tobacco origins.
采用气相色谱-质谱联用（GC-MS）结合多变量数据分析方法，对来自中国不同地理区域的烟叶进行了代谢物谱分析。层次聚类分析（HCA）和主成分分析（PCA）表明，烟草代谢组明显依赖于地理来源；温度和降水等气候条件对代谢物水平的影响大于品种。通过正交偏最小二乘判别分析（OPLS-DA），筛选出20种有助于鉴别的代谢物，包括初级代谢物（蔗糖、D-果糖、D-甘露糖、D-葡萄糖、肌醇、马来酸、柠檬酸、苹果酸、L-苏糖酸、L-脯氨酸、L-苯丙氨酸）、次级代谢物（绿原酸、α-和β-4,8,13-杜瓦三烯-1,3-二醇、尼古丁、奎尼酸）以及4种未知代谢物。结果表明，利用GC-MS结合多变量分析的代谢物谱分析方法可用于鉴别不同地理来源的烟叶，并提供烟草产地的潜在指标。
