Multi-Element Analysis and Origin Discrimination of Panax notoginseng Based on Inductively Coupled Plasma Tandem Mass Spectrometry (ICP-MS/MS)

• Published in: Molecules (Basel, Switzerland) Vol. 27; no. 9; p. 2982
• Main Authors: Ji, Chao, Liu, Jinyu, Zhang, Qin, Li, Juan, Wu, Zhiqiang, Wang, Xingyu, Xie, Yuxin, Zhao, Jiangchao, Shi, Rui, Ma, Xing, Khan, Mohammad Rizwan, Busquets, Rosa, He, Xiahong, Zhu, Youyong, Zhu, Shusheng, Zheng, Wenjie
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 06.05.2022; MDPI
• Subjects: Accuracy; Algorithms; cultivation model discrimination; Detection limits; Discriminant analysis; Fraud; ICP-MS/MS; Inductively coupled plasma mass spectrometry; Mass spectrometry; Mass spectroscopy; Methods; multi-element; Neural networks; origin discrimination; Panax notoginseng; Panax notoginseng - chemistry; Scientific imaging; Spectrum Analysis; Supply chains; Support vector machines; Tandem Mass Spectrometry; Panax notoginseng; ICP-MS/MS; cultivation model discrimination; origin discrimination; multi-element
• ISSN: 1420-3049; 1420-3049
• DOI: 10.3390/molecules27092982

is an important functional health product, and has been used worldwide because of a wide range of pharmacological activities, of which the taproot is the main edible or medicinal part. However, the technologies for origin discrimination still need to be further studied. In this study, an ICP-MS/MS method for the accurate determination of 49 elements was established, whereby the instrumental detection limits (LODs) were between 0.0003 and 7.716 mg/kg, whereas the quantification limits (LOQs) were between 0.0011 and 25.7202 mg/kg, recovery of the method was in the range of 85.82% to 104.98%, and the relative standard deviations (RSDs) were lower than 10%. Based on the content of multi-element in (total of 89 mixed samples), the discriminant models of origins and cultivation models were accurately determined by the neural networks (prediction accuracy was 0.9259 and area under ROC curve was 0.9750) and the support vector machine algorithm (both 1.0000), respectively. The discriminant models established in this study could be used to support transparency and traceability of supply chains of and thus avoid the fraud of geographic identification.