2026-04-13T01:01:07Zhttps://recercat.cat/oai/requestoai:recercat.cat:2445/1740392025-12-04T19:37:18Zcom_2072_1057col_2072_478813col_2072_478917
RECERCAT
author
Núñez, Nerea
author
Saurina, Javier
author
Núñez Burcio, Oscar
2021-02-18T09:35:52Z2022-01-22T06:10:20Z2021-01-222021-02-18T09:35:52Z
Coffee is today one of the most popular beverages in the world and the determination of its authenticity is an important issue considering the increase of adulteration cases in the last years. In this work, a simple and efficient non-targeted HPLC-FLD fingerprinting method was employed to detect and quantify adulteration levels in coffee samples by partial least squares (PLS) regression to guarantee food integrity and authenticity. For that purpose, different adulteration cases, involving both coffee production region and variety, were evaluated by pairs (Colombia-Ethiopia, Colombia-Nicaragua, India-Indonesia, Vietnam Arabica-Vietnam Robusta, Vietnam Arabica-Cambodia, and Vietnam Robusta-Cambodia adulteration cases). Overall, the proposed non-targeted HPLC-FLD fingerprinting strategy showed very good results with PLS cross-validation and prediction errors below 3.4% and 7.5%, respectively, for adulteration levels below 15%. Therefore, non-targeted HPLC-FLD fingerprints demonstrated to be suitable to assess coffee integrity and authenticity in the control and prevention of frauds.
cc-by-nc-nd (c) Elsevier B.V., 2021 http://creativecommons.org/licenses/by-nc-nd/3.0/es info:eu-repo/semantics/openAccess
Quimiometria
Qualitat dels aliments
Cafè (Beguda)
Seguretat alimentària
Chemometrics
Food quality
Coffee drink
Food security
Non-targeted HPLC-FLD fingerprinting for the detection and quantitation of adulterated coffee samples by chemometrics
info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion