Food quality, authenticity and safety constitute an important issue globally. Due
to its short supply and high demand, honey has become a prime target for economically
motivated adulteration. As for other food commodities, NMR-based methods have been
employed in the quality control of honey. However, a challenging step remains the
identification of biomarkers, mainly due to the scarcity of databases, as well as
the samples’ complexity and variability.
Therefore, the aim of the current study was to apply NMR-based metabolite profiling
in the quality control of Greek honey. Moreover, a parallel goal was to evaluate the
impact of Statistical Total Correlation Spectroscopy (STOCSY) in the biomarker identification process [1]. STOCSY correlates signals of the same biomarker based on the variance of its concentration
levels across the samples on their respective spectra.
Thus, using MVA on NMR data, it was possible to discriminate honey samples of different
geographical and botanical origin from Greek Eastern Aegean islands. Furthermore,
5-hydroxymethylfurfural and methyl syringate stood out as indicative biomarkers of
botanical origin identified via STOCSY.
In conclusion, NMR-based metabolite profiling is an effective method in honey quality
and authenticity assessment, while STOCSY is a valuable statistical tool for biomarkers’
identification, with the present being its maiden application in honey. Nevertheless,
its implementation in food is still in early stages.
