Differentiation of meat species of raw and processed meat based on polar metabolites using H NMR spectroscopy combined with multivariate data analysis.

Meat species of raw meat and processed meat products were investigated by H NMR spectroscopy with subsequent multivariate data analysis. Sample preparation was based on aqueous extraction combined with ultrafiltration in order to reduce macromolecular components in the extracts. H NMR data was analyzed by using a non-targeted approach followed by principal component analysis (PCA), linear discrimination analysis (LDA), and cross-validation (CV) embedded in a Monte Carlo (MC) resampling approach. A total of 379 raw meat samples (pork, beef, poultry, and lamb) and 81 processed meat samples (pork, beef, poultry) were collected between the years 2018 and 2021. A 99% correct prediction rate was achieved if the raw meat samples were classified according to meat species. Predicting processed meat products was slightly less successful (93 %) with this approach. Furthermore, identification of spectral regions that are relevant for the classification polar chemical markers was performed. Finally, data on polar metabolites were fused with previously published H NMR data on non-polar metabolites in order to build a broader classification model and to improve prediction accuracy.