ArticleJournal of agricultural and food chemistry2026
Novel Analytical Workflow for Tracing Synthetic Caffeine Adulteration in Amazonian Guaraná (Paullinia cupana) Using Low-Field 1H NMR Fingerprinting and Chemometrics.
Article in Journal of agricultural and food chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
Maués guaraná (Paullinia cupana), a Brazilian product with Geographical Indication (GI), is highly susceptible to economically motivated fraud, particularly through the undeclared addition of synthetic caffeine. Conventional chromatographic methods for authenticity control are time-consuming, costly, and rely on hazardous chemicals. This study presents a comparatively streamlined, solvent-efficient, and environmentally friendly approach based on low-field 1H NMR spectroscopy coupled with chemometrics, eliminating the need for deuterated solvents. Using authentic (n = 40), commercial (n = 18), and adulterated samples (1-10% synthetic caffeine), the data-driven soft independent modeling of the class analogy (DD-SIMCA) model achieved 100% sensitivity and over 99% accuracy for authentication. Simultaneously, a PLS regression model accurately quantified adulteration levels, showing high predictive performance (Rpred2 = 0.9891; RMSEP = 0.36%) and low detection limits. This orthogonal workflow successfully distinguished natural agro-industrial variability from intentional adulteration, demonstrating the potential of a practical, affordable, and sustainable first-line screening approach for future regulatory application.
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