Acta Vet. Brno 2025, 94: 251-259

https://doi.org/10.2754/avb202594030251

Raman spectroscopy and NIR as a method of comparing monofloral and honeydew honeys

Boris Pleva1, Matej Pospiech1, Alena Saláková2, Martina Pečová1, Jana Čaloudová1, Zdeňka Javůrková1, Pavel Hrabec3, Bohuslava Tremlová1

1University of Veterinary Sciences Brno, Faculty of Veterinary Hygiene and Ecology, Department of Plant Origin Food Sciences, Brno, Czech Republic
2Mendel University in Brno, Faculty of AgriSciences, Department of Food Technology, Brno, Czech Republic
3University of Technology Brno, Faculty of Mechanical Engineering, Department of Computer Graphics and Geometry, Brno, Czech Republic

Received June 26, 2025
Accepted September 10, 2025

Honey is one of the most commonly adulterated foods. This study therefore focused on innovative possibilities of identifying the botanical origin of honey using Raman spectroscopy and Fourier transform near-infrared spectroscopy (FT-NIR), in order to test their potential use as an alternative to physicochemical analysis and melissopalynology methods. Both mentioned non-destructive methods were used for discrimination and characterization of the honey species. Forty-seven samples of flower and honeydew honey obtained from hobby beekeepers from different regions of the Czech Republic were analysed in the period between 2019 and 2021. Among the floral honeys, poly- as well as monofloral honeys were selected (rapeseed, clover, acacia, phacelia, fruit tree honey). The FT-NIR analysis results confirmed significant differences (P < 0.05) between the specific-species honey samples for wavenumbers of 5,624, 5,171, 4,780, 4,391 cm-1 (P < 0.05). Raman spectroscopy confirmed significant differences between multiple wavenumbers, with classification into the most classes confirmed for wavenumbers of 308, 606, 613, 620, 999 and 1,013 cm-1 (P < 0.05). However, neither method allowed classification for all honey species, thus FT-NIR and Raman spectra were compared by linear discriminant analysis (LDA), which confirmed a high correct classification rate (CCR) of 99.38%, and 91.30% in the case of cross-validation. In the case of rapeseed honey, the lowest CCR (96.15%) and cross-validation (76.92%) values were confirmed. It was confirmed that the FT-NIR method in combination with Raman spectroscopy can be used to identify individual honey species with a high degree of reliability.

Funding

The study was supported by the Applied Research Programme of the Ministry of Agriculture for the 2017-2025 period [Project No. QK1920344, ‘ZEMĚ’ (‘The Land’)].

References

29 live references