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dc.contributor.authorBarbosa, Sergio-
dc.contributor.authorPardo-Mates, Naiara-
dc.contributor.authorHidalgo-Serrano, Míriam-
dc.contributor.authorSaurina, Javier-
dc.contributor.authorPuignou i Garcia, Lluís-
dc.contributor.authorNúñez Burcio, Oscar-
dc.description.abstractUHPLC-HRMS (Orbitrap) fingerprinting in negative and positive H-ESI mode was applied to the characterization, classification and authentication of cranberry-based natural and pharmaceutical products. HRMS data in full scan mode (m/z 100-1500) at a resolution of 70,000 full-width at half maximum was recorded and processed with MSConvert software to obtain a profile of peak intensities in function of m/z values and retention times. A threshold peak filter of absolute intensity (105 counts) was applied to reduce data complexity. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) revealed patterns able to discriminate the analyzed samples according to the fruit of origin (cranberry, grape, blueberry and raspberry). Discrimination among cranberry-based natural and cranberry-based pharmaceutical preparations was also achieved. Both, UHPLC-HRMS fingerprints in negative and positive H-ESI modes, as well as the data fusion of both acquisition modes, showed to be good chemical descriptors to address cranberry extracts authentication. Validation of the proposed methodology showed a prediction rate of 100% of the samples. Obtained data was further treated by partial least squares (PLS) regression to identify frauds and quantify the percentage of adulterant fruits in cranberry-fruit extracts, achieving prediction errors in the range 0.17-3.86%.-
dc.format.extent25 p.-
dc.publisherRoyal Society of Chemistry-
dc.relation.isformatofVersió postprint del document publicat a:
dc.relation.ispartofAnalytical Methods, 2019, vol. 11, num. 26, p. 3341-3349-
dc.rights(c) Barbosa, Sergio et al., 2019-
dc.subject.classificationEspectrometria de masses-
dc.subject.classificationQuímica dels aliments-
dc.subject.otherMass spectrometry-
dc.subject.otherFood composition-
dc.titleUHPLC-HRMS (Orbitrap) fingerprinting in the classification and authentication of cranberry-based natural products and pharmaceuticals using multivariate calibration methods-
Appears in Collections:Articles publicats en revistes (Enginyeria Química i Química Analítica)

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