Zhongning wolfberry is a famous geographical indication (GI) in China. The concentrations of twenty elements (K, Mg, Fe, Ca, Zn, Cu, Mn, Al, Sr, Rb, Mo, Tb, Cd, Co, V, As, Cs, Pr, Dy and Gd) in samples were determined using inductively coupled plasma mass spectrometry. The data were subjected to analysis of variance, principal component analysis and linear discriminant analysis. The results indicated that nineteen minerals (except K) represented significant differences among regions. The correct classification rates of original group and cross-validation of Zhongning wolfberry were 95.7% and 85.7%, for these nineteen variables. Furthermore, there was no significant difference for all variables in samples from three picking periods. It was feasible to distinguish Zhongning wolfberry based on mineral profiles with chemometric approaches, and the study could serve as a reference for the authentication of wolfberries and the prevention of deceptive labelling of other GI products.

Summary Totally 270 wheat samples with ten genotypes of 2010/2011, 2011/2012 and 2012/2013 from three regions were collected, and the multi‐elemental compositions (Mg, Al, Ca, Mn, Fe, Cu, Zn, As, Sr, Mo, Cd, Ba, Pb) were analysed with high‐resolution inductively coupled plasma mass spectrometry (HR‐ICP‐MS). Multiway analysis of variance was employed to investigate the influences of region, genotype, harvest year and their interactions on all elements. The contribution rates of variances were computed, and the results showed that the elements of Mn, Sr, Mo and Cd were closely related to region explaining 34.2%, 39.6%, 35.0% and 78.8% of the total variation, respectively. The genotype contributed most for the variation of Ba, accounting for 27.3%, and the other elements were affected by the harvest year. Mn, Sr, Mo and Cd can be used for establishing the robust discriminant model with the correct classification rate of 98.5% to identify the geographical origin of wheat.