Classification of Monofloral and Polyfloral Honey using Near-Infrared Spectroscopy and Chemometric Techniques

Honey is a widely consumed natural product with substantial commercial importance. The ability to rapidly and reliably differentiate honey types would benefit both producers and consumers. This study examines the application of nearinfrared (NIR) spectroscopy, combined with chemometric analysis, to differentiate between monofloral and polyfloral honey. A total of 102 honey samples (44 monofloral and 58 polyfloral) were collected from various apiaries across Bulgaria, with botanical origins confirmed through melissopalynology analysis. Spectral data were acquired using a NIRQuest 512 scanning spectrometer (Ocean Optics, Inc.) in the 900-1700 nm range, employing a reflection fiber-optic probe. Soft Independent Modeling of Class Analogy (SIMCA) models were created using various preprocessing techniques. The SIMCA model based on autoscaling, smoothing, and first derivative transformation demonstrated the most consistent performance, with calibration and test accuracies of 98.04 % and 96.08 %, respectively. These results emphasize the potential of NIR spectroscopy as a fast, non-destructive screening tool for honey type classification. In addition, such techniques may be incorporated into industrial workflows for honey quality assessment, including the use of portable NIR instruments suitable for on-site applications.

• Publication year

  2025

• Venue

  2025 10th International Conference on Energy Efficiency and Agricultural Engineering (EE&AE)

• Publication date

  2025-11-05

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1109/EEAE65901.2025.11273670
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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