Characterization and Differentiation of Wild and Cultivated Berries Based on Isotopic and Elemental Profiles

Abstract

The isotopic content (δ13C, δ2H, δ18O) and concentrations of 30 elements (Li, Na, Mg, P, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, As, Rb, Sr, Ag, Cd, Ba, Pb, La, Ce, Pr, Nd, Sm, Eu, Gd, and Tb) were determined in different wild and cultivated berries (raspberry, seaberry, blackberry, cranberry, and blueberry). Partial least squares discriminant analysis (PLS-DA) was applied in order to develop models for differentiating berries according to their botanical origin and growing system. δ13C, δ2H, δ18O, Li, Na, Mg, P, Ca, V, Mn, Co, Ni, Zn, As, Rb, Sr, Ba, and Eu were identified as significant elements for the differentiation of berry species, based on which an 85% PLS-DA model accuracy was obtained. Similarly, the PLS-DA model developed for the growing system differentiation correctly classified 94.4% of the cultivated berries and 77.2% of the wild ones, based on the main predictors: δ13C, δ18O, Li, Na, Ca, Cr, Mn, Ni, Rb, and Ba. The developed PLS-DA model for the discrimination of wild blueberries from cultivated ones showed excellent levels of sensitivity (100%), specificity (100%), and accuracy (100%).