Chemometric Discrimination of the Geographical Origin of by Stable Isotope Analysis.

is one of the primary rhubarb species used for food and medicinal purposes, and it has recently been gaining more attention and recognition. This research represents the first attempt to use stable isotopes and elemental analysis via IRMS to identify the geographical origin of . A grand total of 190 rhubarb samples were gathered from 38 locations spread throughout the provinces of Gansu, Sichuan, and Qinghai in China. The carbon content showed a decreasing trend in the order of Qinghai, followed by Sichuan, and then Gansu. Nitrogen content was notably higher, with Qinghai and Sichuan displaying similar levels, while Gansu had the lowest nitrogen levels. Significant differences were noted in the C (-28.9 to -26.5‱), N (2.6 to 5.6‱), H (-120.0 to -89.3‱), and O (16.0‱ to 18.8‱) isotopes among the various rhubarb cultivation areas. A significant negative correlation was found between %C and both longitude and humidity. Additionally, C and N isotopes were negatively correlated with longitude, and N showed a negative correlation with humidity as well. H and O isotopes exhibited a strong positive correlation with latitude, while significant negative correlations were observed between H and O isotopes and temperature, precipitation, and humidity. The LDA, PLS-DA, and k-NN models all exhibited strong classification performance in both the training and validation sets, achieving accuracy rates between 82.1% and 91.7%. The combination of stable isotopes, elemental analysis, and chemometrics provides a reliable and efficient discriminant model for accurately determining the geographical origin of in different regions. In the future, the approach will aid in identifying the geographical origin and efficacy of rhubarb in other studies.