title: Classification of Maojian teas from different geographical origins by micellar electrokinetic chromatography and pattern recognition techniques.
abstract: A micellar electrokinetic chromatography (MEKC) method was applied for the identification of geographical origins of Chinese green teas. Under the optimized conditions, chromatographic profiling of collected Maojian tea samples was obtained. Based on MEKC-UV profiling, twenty-four tea samples were successfully differentiated according to the relative peak areas of selected peaks in the chromatograms. Tea samples from Hubei and Henan provinces were classified correctly by hierarchical cluster analysis model (HCA) and principal component analysis (PCA). The application of linear discriminant analysis (LDA) gave correct assignation percentages of 100% for the training set and the prediction set. The overall results demonstrated that MEKC with pattern recognition could be successfully applied to discriminate Maojian teas according to their geographical origins.
authors: Department of Chemistry, Capital Normal University, Beijing, PR China. yensh@mail.cnu.edu.cn
authors: Nengsheng
authors: N
authors: Ye
authors: Liqin
authors: L
authors: Zhang
authors: Xuexin
authors: X
authors: Gu
mesh_terms: D002845:Chromatography; D020374:Chromatography, Micellar Electrokinetic Capillary / Q000379:methods*; D016000:Cluster Analysis; D016002:Discriminant Analysis; D005843:Geography; D010363:Pattern Recognition, Automated / Q000379:methods*; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D013662:Tea / Q000737:chemistry / Q000145:classification*
chemical_list: D013662:Tea