400 MHz nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis techniques were used in the context of food surveillance to measure 328 honey samples with1H and13C NMR. Using principal component analysis (PCA), clusters of honeys from the same botanical origin were observed. The chemical shifts of the principal monosaccharides (glucose and fructose) were found to be mostly responsible for this differentiation. Furthermore, soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA) could be used to automatically classify spectra according to their botanical origin with 95–100% accuracy. Direct quantification of 13 compounds (carbohydrates, aldehydes, aliphatic and aromatic acids) was additionally possible using external calibration curves and applying TSP as internal standard. Hence, NMR spectroscopy combined with chemometrics is an efficient tool for simultaneous identification of botanical origin and quantification of selected constituents of honeys.

The globalization of trade of foods with its overwhelming variety has led to an increased demand for authentic products by all parts of the food value chain. In particular high-priced products are commonly adulterated, mislabeled or completely substituted. Honey is a typical example for such foods, which show an increasing number of adulterations, mostly related to the declaration of the botanical origin. A non-targeted 1 H-NMR-based screening, combined with multivariate statistical analysis was applied as a fast and simple comprehensive approach to verify the botanical origin of honey samples. The NMR fingerprints of honey sample were processed by taylor-made chemometric tools, based on principal component analysis (PCA) and linear discriminant analysis (LDA) in custom MATLAB routines. The results obtained by PCA-LDA showed very good discrimination between the different honey types with 98.9 % correct overall classification rate of the samples. Hence, this NMR based screening approach could be an effective alternative to traditional, laborious methods.

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