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

Decker, Christina 1; Krapf, Reiner; Kuballa, Thomas; Bunzel, Mirko 2
1 Karlsruher Institut für Technologie (KIT)
2 Institut für Angewandte Biowissenschaften (IAB), Karlsruher Institut für Technologie (KIT)

Abstract:

1H 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.


Verlagsausgabe §
DOI: 10.5445/IR/1000160994
Veröffentlicht am 27.07.2023
Originalveröffentlichung
DOI: 10.1007/s00217-023-04312-y
Scopus
Zitationen: 1
Dimensions
Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte Biowissenschaften (IAB)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2023
Sprache Englisch
Identifikator ISSN: 1438-2377, 1438-2385
KITopen-ID: 1000160994
Erschienen in European Food Research and Technology
Verlag Springer-Verlag
Band 249
Heft 10
Seiten 2559–2567
Vorab online veröffentlicht am 28.06.2023
Nachgewiesen in Web of Science
Scopus
Dimensions
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