Detection and quantitation of frauds in the authentication of cranberry-based extracts by UHPLC-HRMS (Orbitrap) polyphenolic profiling and multivariate calibration methods

UHPLC-HRMS (Orbitrap) polyphenolic profiling was applied to the characterization, classification and authentication of cranberry-based natural and pharmaceutical products. 53 polyphenolic standards were characterized to build a user accurate mass database which was then proposed to obtain UHPLC-HRMS...

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Detalles Bibliográficos
Autores: Barbosa, Sergio, Pardo-Mates, Naiara, Hidalgo-Serrano, Míriam, Saurina, Javier, Puignou i Garcia, Lluís, Núñez Burcio, Oscar
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2018
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/124665
Acceso en línea:https://hdl.handle.net/2445/124665
Access Level:acceso abierto
Palabra clave:Oli d'oliva
Polifenols
Quimiometria
Envasament d'aliments
Espectrometria de masses
Olive oil
Polyphenols
Chemometrics
Food packaging
Mass spectrometry
Descripción
Sumario:UHPLC-HRMS (Orbitrap) polyphenolic profiling was applied to the characterization, classification and authentication of cranberry-based natural and pharmaceutical products. 53 polyphenolic standards were characterized to build a user accurate mass database which was then proposed to obtain UHPLC-HRMS polyphenolic profiles by means of ExactFinderTM software. Principal component analysis results showed a good sample discrimination according to the fruit employed. Regarding cranberry-based pharmaceuticals, discrimination according to the presentation format (syrup, sachets, capsules, etc.) was also observed due to the enhancement of some polyphenols by purification and preconcentration procedures. Procyanidin A2 and homogenistic, sinapic, veratric, cryptochlorogenic and caffeic acids showed to be important polyphenols to achieve cranberry-based products discrimination against the other studied fruits. Partial least square regression allowed the determination of adulterant percentages in cranberry-fruit samples. Very satisfactory results, with adulteration quantification errors lower than 6.0% were obtained even at low adulteration levels.