Multielemental + isotopic fingerprint enables linking soil, water, forage and milk composition, assessing the geographical origin of Argentinean milk.

The aim of this work was to verify the usefulness of multielemental and isotopic fingerprint to differentiate the origin of milk samples from different areas, linking milk fingerprint with those corresponding to soil, water, and forage. Samples from four production areas in Argentina were analysed: 26 elements, δH, δC, δN and δO. Milk provenance was assessed using 16 variables (Na, Mg, Al, V, Co, Ni, As, Se, Rb, Sr, Mo, Hg, δH, δO, δC and K/Rb). Generalized Procrustes Analysis (GPA) demonstrated the consensus between soil, water, forage and milk, in addition to differences between studied areas. Canonical Correlation Analysis (CCA) demonstrated significant correlations between the milk-drinking water, milk-forage, and milk-soil. So far, we report a feasible method to establish the milk provenance, assessing the follow up from environmental matrixes (soil + water) to dairy products through the food web (forage) by a combined chemical-isotopic fingerprint.