1H NMR spectroscopy combined with multivariate data analysis for authentication of “Swabian–Hall Quality Pork” with protected geographical indication

Abstract

Abstract1H NMR spectroscopy was applied to analyse samples of “Swabian–Hall Quality Pork” with protected geographical indication (PGI). To obtain maximum chemical information sample preparation was based on both polar extraction and non-polar extraction. A non-targeted approach was used to analyse the 1H NMR data followed by principal component analysis (PCA), linear discriminant analysis (LDA), and cross-validation (CV) embedded in a Monte Carlo (MC) resampling approach. A total of 275 raw pork samples were collected in the years 2018 to 2021. The correct prediction rate of “Swabian–Hall Quality Pork” was about 92% on average for both models based on either the polar or non-polar metabolites. In addition, 1H NMR data describing the polar and non-polar metabolites were combined in a classification model to improve the prediction accuracy. By performing a mid-level data fusion, a correct prediction rate of 98% was achieved. Furthermore, spectral regions in the NMR spectra of the polar and non-polar metabolites that are relevant for the classification of the pork samples were identified to describe potential chemical marker compounds.