Intra-regional classification of Codonopsis Radix produced in Gansu province (China) by multi-elemental analysis and chemometric tools

Abstract

Multi-elemental analysis is widely used to identify the geographical origins of plants. The purpose of this study was to explore the feasibility of combining chemometrics with multi-element analysis for classification of Codonopsis Radix from different producing regions of Gansu province (China). A total of 117 Codonopsis Radix samples from 7 counties of Gansu province were collected. Inductively coupled plasma mass spectrometry (ICP-MS) was used for the determination of 28 elements (39 K, 24 Mg, 44Ca, 27Al, 137Ba, 57Fe, 23Na, 88Sr, 55Mn, 66Zn, 65Cu, 85Rb, 61Ni, 53Cr, 51 V, 7Li, 208Pb, 59Co, 75As, 133Cs, 71 Ga, 77Se, 205Tl, 114Cd, 238U, 107Ag, 4Be and 202Hg). Among macro elements, 39 K showed the highest level, whereas 23Na was found to have the lowest content value. Micro elements showed the concentrations order of: 88Sr > 55Mn > 66Zn > 85Rb > 65Cu. Among trace elements, 53Cr and 61Ni showed higher content and 4Be was not detected in all samples. Intra-regions differentiation was performed by principal component analysis (PCA), cluster analysis (CA) and supervised learning algorithms such as linear discriminant analysis (LDA), k-nearest neighbors (k-NN), support vector machines (SVM), and random forests (RF). Among them, the RF model performed the best with an accuracy rate of 78.79%. Multi-elemental analysis combined with RF was a reliable method to identify the origins of Codonopsis Radix in Gansu province.