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.