Assigning the Geographical Origin of Meat and Animal Rearing System Using Isotopic and Elemental Fingerprints

Abstract

In this study, the stable isotope, and elemental fingerprints of 120 meat samples were determined. The Partial Last Squares-Discriminant Analysis (PLS-DA) method was applied to build classification models for chicken and pork meat samples according to the geographical origin (different Romanian regions) and the animal growing system (animals coming from yard rearing systems versus animals coming from industrial farms). The accuracy of the geographical origin differentiation model was 93.8% for chicken and 71.8% for pork meat. The principal discrimination markers for this classification were: B, Na, K, V, As, Se, Rb, Nb, Cd, Sn, δ13C, δ2H, and δ18O (for chicken meat) and B, Na, Mg, K, Ca, V, Cr, Fe, Ni, Cu, Zn, As, Rb, Sr, Nb, Mo, Sn, Sb, Ba, Pb, δ13C, δ2H, and δ18O (for pork meat). The PLS-DA models were able to differentiate the meat samples according to the animal rearing system with 100% accuracy (for pork meat) and 98% accuracy (for chicken meat), based on the main predictors: B, K, V, Cr, Mn, Fe, Cu, Zn, Se, Rb, Nb, Sn, δ13C, and δ2H (for chicken meat) and Se, Rb, Nb, Sb, Ba, Pb, and δ13C (for pork meat).