Núñez Burcio, OscarNúñez, NereaSaurina, Javier2025-09-192025-09-192025-082304-8158https://hdl.handle.net/2445/223312Coffee adulteration is a growing concern in the food industry due to economic and quality implications. This study evaluates a rapid, non-targeted fingerprinting method based on flow injection analysis–mass spectrometry (FIA-MS) for detecting common coffee adulterants. A total of 119 samples were analyzed, including 43 coffee samples and 76 samples of common coffee adulterants (16 chicory, 10 barley, and 50 flour samples). FIA-MS combined with chemometric analysis allowed for the classification of pure and adulterated coffee samples with over 95% accuracy. Compared to LC-MS, the FIA-MS method showed a similar performance while offering significantly faster analysis and lower solvent consumption, making it a practical and sustainable option for high-throughput screening. For PLS regression studies, calibration and prediction errors were consistently below 0.91% and 11.7%, respectively. Furthermore, the methodology was compared with a non-targeted LC-MS approach, showing an excellent performance.17 p.application/pdfengcc-by (c) Núñez et al., 2025http://creativecommons.org/licenses/by/4.0/Anàlisi per injecció en fluxCafè (Beguda)QuimiometriaFlow injection analysisCoffee drinkChemometricsinfo:eu-repo/semantics/article7601242025-09-19info:eu-repo/semantics/openAccess