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RATIONALE: Caffeinated drinks and supplements are popular products, many of which claim to use naturally derived caffeine. The availability of less expensive synthetic caffeine can motivate adulteration. Additionally, the caffeine content of these products can be inaccurately labeled, raising health concerns. As a result, effective testing methods are required to distinguish synthetic and natural caffeine and to test caffeine content in complex matrixes. In this study, a stable isotope method for natural caffeine authentication is described and applied to commercial samples. The accuracy of labeled caffeine content of products is evaluated. METHODS: Samples containing exclusively natural caffeine (i.e., coffee, tea, guarana, yerba mate) and synthetic caffeine were selected. Commercial products claiming to contain natural caffeine including supplements, energy drinks, and guarana products were also tested. Caffeine was extracted by incubation with a water-ammonium hydroxide mixture and phase separation with dichloromethane. Its carbon and nitrogen stable isotope composition was determined using GC-C-IRMS. Caffeine content was determined by HPLC-DAD. RESULTS: N) isotopes. Based on this distinction, 15 of the 75 commercial samples labeled as containing natural caffeine were adulterated. The rate of apparent adulteration was high in guarana products (~78%) and supplements (~22%). Caffeine content deviating from label claim by more than ±20% was observed in 46% of the 86 samples tested, ranging from 57% to 217% of the labeled content. CONCLUSIONS: Carbon and nitrogen isotope ratio analysis by gas chromatography-combustion-isotope ratio mass spectrometry is an efficient method for distinguishing natural and synthetic caffeine in commercially available products. Such testing is important given the significant number of apparently mislabeled products on the USA market. The prevalence of inaccurate caffeine content labeling may raise health concerns, highlighting the need for better production quality control and increased testing.
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Yanay et al. (2026) studied this question.
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