DISCRIMINATION OF GEOGRAPHICAL ORIGIN OF TEA BASED ON MULTI-ELEMENT FINGERPRINTING BY INDUCTIVELY COUPLED PLASMA OPTICAL EMISSION SPECTROMETRY AND ATOMIC ABSORPTION SPECTROMETRY

Abstract

The metal content of 49 tea leaf samples from three different provinces inVietnamwere determined using inductively coupled plasma optical emission spectrometry (ICP-OES) and atomic absorption spectrometry (AAS). Total 18 elements in tea leaves were determined including macro element such as Al, Ca, K, Mg, Mn; trace element such as Na, Ba, Fe, Cu, Zn, B and heavy metals (Pb, Cd, Hg, Ni, Se, Sn) and metalloid (As). There was a wide variation of metal contents among the tea leaves coming from different province in which K content was the highest in all the tea leaf samples from the three provinces, followed by Ca, Mn and Al content. Principal component analysis (PCA) was applied in order to determine the different amount of metals as main sources of variability in the data sets and to establish the relation between samples and metal contents (variables). Linear discriminant analysis (LDA) was used to explore the different tea samples grouping according to the metal contents. Among the 18 elements found in the composition of tea leave samples, the LDA shows that Fe, Mg, Cd, and As are components with major discriminating power for the samples. This confirms that tea from different province shows unique elemental fingerprint characteristics that can be differentiated one from another and both techniques (PCA and LDA) are able to create for clear separation of tea leaf from identical province. However, LDA method could provide better discrimination of tea geographical origin over the PCA method.