Differentiation of eight tea (Camellia sinensis) cultivars in China by elemental fingerprint of their leaves

Abstract

BACKGROUND: Tea is an infusion made from dried leaves of tea (Camellia sinensis)and can be a good dietary source of essential trace metals for humans. Therefore, it is necessary to consider variations in element content of tea leaves among tea cultivars. Thus, elemental fingerprint techniques, based on elemental contents (Al, B, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Na, P, Pb, and Zn) determined by inductively coupled plasma atomic emission spectrometry (ICP-AES) and multivariate statistical analysis, have been used to differentiate eight tea cultivars. RESULTS: The ranges of element concentrations in leaves of the eight cultivars were in good agreement with those obtained in previous studies and the level of most elements in tea leaves was significantly different among cultivars. The classifications of eight tea cultivars were 100% accurate in total by principal component analysis (PCA), hierarchical cluster analysis (HCA), linear discriminant analysis (LDA), and back-propagation neural network (BPNN) analysis. CONCLUSION: Each cultivar presented a distinctive element fingerprint and the elements in tea leaves can be significant predictors in differentiating tea cultivars. © 2009 Society of Chemical Industry.