Elemental Profiling for Discrimination of Geographical Origin of Tea (Camellia sinensis) in north-east region of India by ICP-MS coupled with Chemometric techniques

Abstract

The study aimed to discriminate the teas originated from eight north-east region of India using 67 elemental profiling through the use of ICP-MS and process the large data with chemometric software. Among the 67 elements, concentrations of 18 elements were significantly different in the eight regions (Darjeeling, Tripura, Upper Assam, South Bank, Terai, North Bank, Dooars and Cachar). Selected 18 elements belongs to alkali metal (Rb, Cs), alkaline earth metal (Mg, Sr, Ba), transition metal (V, Cr, Mn, Co, Ni, Zn, Mo), basic metal (Al), metalloid (B), non-metal (Se) and lanthanide (La, Ce, Nd). Multivariate chemometric analysis with PCA, LDA, SVM & OPLS DA were performed on the concentration of 18 elements on 307 authentic sample set. The correct classification rate for the training set (307) and test set (24) tea samples were 100% for SVM, LDA and OPLS DA model and confidence measure for SVM and LDA model were 99.4% and 88.97%, respectively. Variable importance in projection (VIP) values ranged between 1.04-1.51 for five elements (Cr, Mo, Rb, Mn and Ni), which can be considered as significant parameter for discrimination. The results demonstrated that ICP-MS with chemometric software could be used to discriminate the geographical origin of tea.