Researchers at University of Chemistry and Technology in Prague have developed a rapid, non-destructive method using attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) to identify the botanical origin of honey. This method, which efficiently categorizes honey based on origin, has implications for honey pricing and marketability, aiding in more precise and cost-effective product differentiation.
Fig. 2. Indicative FTIR spectra for each of the analysed honey matrices. Each colour represents a different matrix as it is displayed in the legend.
In an innovative development that will significantly streamline the categorization of honey and its subsequent pricing in the market, a new study has developed a rapid and non-destructive method to identify the botanical origin of honey.
The study, utilizing a spectroscopic method, namely, attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), successfully demonstrated a workflow to swiftly identify the botanical origin of honey, a task that traditionally necessitated extensive high-end analysis.
Honey's botanical origin influences not only its market price but also its organoleptic properties and potential health benefits, making it a critical factor in consumer choice. This breakthrough comes as a boon to industry stakeholders who can now categorize honey in a more precise and cost-effective manner.
The researchers tested twenty-two different pre-processing methods and combinations, including scatter correction methods and spectral derivation methods, using both supervised and non-supervised tools. Their efforts revolved around optimally projecting a diverse array of fifty-one honey samples from five different botanical origins, namely blossom, honeydew, cotton, thyme, and citrus.
The study's pivotal finding suggests the most efficient data pre-processing method is the combination of multiplicative scatter correction followed by Savitzky-Golay first derivation. This procedure resulted in excellent recognition (87–100%) and prediction (81–100%) ability when applied in binary models.
The findings highlight the significant, yet often overlooked, effect of spectral data pre-processing before the application of advanced chemometrics. This novel approach will pave the way for rapid and efficient identification of honey's botanical origin, thereby providing a much-needed enhancement in the world of honey production and marketing.
Text is based on the research article:
Tsagkaris, A. S., Bechynska, K., Ntakoulas, D. D., Pasias, I. N., Weller, P., Proestos, C., & Hajslova, J. (2023). Investigating the impact of spectral data pre-processing to assess honey botanical origin through Fourier Transform Infrared Spectroscopy (FTIR). Journal of Food Composition and Analysis, 119, 105276. https://doi.org/10.1016/j.jfca.2023.105276