Authenticity assessment and fraud quantitation of coffee adulterated with chicory, barley and blours by untargeted HPLC-UV-FLD fingerprinting and chemometrics

Coffee, one of the most popular drinks around the world, is also one of the beverages most sus-ceptible of being adulterated. Untargeted high-performance liquid chromatography with ultra-violet and fluorescence detection (HPLC-UV-FLD) fingerprinting strategies in combination with chemometrics were e...

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Bibliographic Details
Authors: Núñez, Nerea, Saurina, Javier, Núñez Burcio, Oscar
Format: article
Status:Published version
Publication Date:2021
Country:España
Institution:Universidad de Barcelona
Repository:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/176689
Online Access:https://hdl.handle.net/2445/176689
Access Level:Open access
Keyword:Qualitat dels aliments
Cafè (Beguda)
Alteració d'aliments
Quimiometria
Food quality
Coffee drink
Food spoilage
Chemometrics
Description
Summary:Coffee, one of the most popular drinks around the world, is also one of the beverages most sus-ceptible of being adulterated. Untargeted high-performance liquid chromatography with ultra-violet and fluorescence detection (HPLC-UV-FLD) fingerprinting strategies in combination with chemometrics were employed for the authenticity assessment and fraud quantitation of adulter-ated coffees involving three different and common adulterants: chicory, barley and flours. The methodologies were applied after a solid-liquid extraction procedure with a methanol:water 50:50 (v/v) solution as extracting solvent. Chromatographic fingerprints were obtained using a Kinetex® C18 reversed-phase column under gradient elution conditions using 0.1% formic acid aqueous solution and methanol as mobile phase components. The obtained coffee and adulter-ants extract HPLC-UV-FLD fingerprints were evaluated by partial least squares regres-sion-discriminants analysis (PLS-DA) resulting to be excellent chemical descriptors for sample discrimination. 100% classification rates for both PLS-DA calibration and prediction models were obtained. Besides, Arabica and Robusta coffee samples were adulterated with chicory, bar-ley and flours, and the obtained HPLC-UV-FLD fingerprints subjected to partial least squares (PLS) regression, demonstrating the feasibility of the proposed methodologies to assess coffee authenticity and to quantify adulteration levels (down to 15%), showing both calibration and prediction errors below 1.3% and 2.4%, respectively.