Metabolic Profiling of Chinese Tobacco Leaf of Different Geographical Origins by GC-MS

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