TXRF spectral information enhanced by multivariate analysis: A new strategy for food fingerprint
2023
Allegretta, Ignazio | Squeo, Giacomo | Gattullo, Concetta Eliana | Porfido, Carlo | Cicchetti, Antonio | Caponio, Francesco | Cesco, Stefano | Nicoletto, Carlo | Terzano, Roberto
The increased costumers’ request of safe and high-quality food products makes food traceability a priority for frauds identification and quality certification. Elemental profiling is one of the strategies used for food traceability, and TXRF spectroscopy is widely used in food analysis even if its potentialities have not been fully investigated. In this work, a new method for food traceability using directly TXRF spectra coupled with multivariate analyses, was tested. Twenty-four different beans’ genotypes (Phaseolus vulgaris L.) grown onto two different sites have been studied. After the development of the method for beans’ analysis, TXRF spectra were collected and processed with PCA combined with SNV and GLSW filter obtaining a perfect clustering of the seeds according to their geographical origin. Finally, using PLS-DA, beans were correctly classified demonstrating that TXRF spectra can be successfully used as fingerprint for food/seed traceability and that elemental quantification procedure is not necessary to this aim.
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