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Title: | Non-targeted high-performance liquid chromatography with ultraviolet and fluorescence detection fingerprinting for the classification, authentication, and fraud quantitation of instant coffee and chicory by multivariate chemometric methods |
Author: | Núñez, Nerea Pons Marquès, Josep Saurina, Javier Núñez Burcio, Oscar |
Keywords: | Cafè (Beguda) Qualitat dels aliments Quimiometria Cromatografia de líquids d'alta resolució Coffee drink Food quality Chemometrics High performance liquid chromatography |
Issue Date: | 1-May-2021 |
Publisher: | Elsevier B.V. |
Abstract: | Non-targeted strategies based on high-performance liquid chromatography with ultraviolet detection (HPLC-UV) and fluorescence detection (HPLC-FLD) fingerprints were evaluated to accomplish the classification and authentication of instant coffee (40 samples), instant decaf coffee (26 samples), and chicory (22 samples, including both ground and instant), as well as to detect and quantify frauds based on chicory adulteration by multivariate chemometric methods. HPLC-UV and HPLC-FLD fingerprints were simultaneously obtained with a HPLC-UV-FLD instrument, and they proved to be excellent chemical descriptors for the classification of coffee and decaf coffee against chicory samples by partial least squares regression-discriminant analysis (PLS-DA). In contrast, HPLC-UV fingerprints improved the classification results when addressing coffee against decaf coffee samples (94.4% classification rate in comparison to 83.3% for HPLC-FLD fingerprints). Besides, the proposed methodologies resulted to be excellent to detect and quantify fraud levels in coffee and decaf coffee samples adulterated with chicory by using partial least squares (PLS) regression, exhibiting good calibration linearities, calibration errors, and prediction errors. In this case, improved capabilities were observed with HPLC-FLD fingerprints, providing better PLS calibration linearities (R2>0.999), lower calibration errors (≤0.8%), and similar to better prediction errors (2.9-3.2%) in comparison to HPLC-UV fingerprints. |
Note: | Versió postprint del document publicat a: https://doi.org/10.1016/j.lwt.2021.111646 |
It is part of: | LWT Food Science and Technology, 2021, vol. 147, p. 111646 |
URI: | http://hdl.handle.net/2445/177134 |
Related resource: | https://doi.org/10.1016/j.lwt.2021.111646 |
ISSN: | 0023-6438 |
Appears in Collections: | Articles publicats en revistes (Enginyeria Química i Química Analítica) |
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