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...
| Authors: | , , |
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| 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 |
| 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. |
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