A untargeted metabolomics approach was proposed in this study based on ultra-high performance liquid chromatography quadrupole time-of-flight (UHPLC-QTOF) and rapid evaporative ionization mass spectrometry (REIMS) to discriminate lamb and mutton meat and investigate their subtle metabolic differences, considering the higher popularity of lamb meat than mutton in the market. Multivariate statistical analysis was performed for data processing in order to distinguish between the two sample types. A total of 42 potential metabolites (20 in positive and 22 in negative ion mode) were defined for UHPLC-QTOF analysis, which provided references for discriminating the two kinds of meat. Furthermore, three potential markers were tentatively identified using LC/MS data against chemical databases. In addition, 14 potential metabolites were putatively identified in negative ion mode using the LipidMaps database. Meanwhile, the data-driven soft independent modeling of class analogy (DD-SIMCA) model was established, which could rapidly differentiate non-pretreated lamb meat and mutton with 92% specificity, rendering REIMS a promising technique for meat identification.

For the protection of Protected Geographical Indication (PGI) Sunite lamb, PGI Sunite lamb samples and lamb samples from two other banners in the Inner Mongolia autonomous region were distinguished by stable isotopes (δ¹³C, δ¹⁵N, δ²H, and δ¹⁸O) and two local modeling approaches. In terms of the main characteristics and predictive performance, local modeling was better than global modeling. The accuracies of five local models (LDA, RF, SVM, BPNN, and KNN) obtained by the Adaptive Kennard–Stone algorithm were 91.30%, 95.65%, 91.30%, 100%, and 91.30%, respectively. The accuracies of the five local models obtained by an approach of PCA–Full distance based on DD–SIMCA were 91.30%, 91.30%, 91.30%, 100%, and 95.65%, respectively. The accuracies of the five global models were 91.30%, 91.30%, 91.30%, 100%, and 91.30%, respectively. Stable isotope ratio analysis combined with local modeling can be used as an effective indicator for protecting PGI Sunite lamb.