Abstract
Honey is usually adulterated by cheaper, commercially available sugar syrups with similar chemical composition. Adulterated honeys are frequently marked as natural and are valued in the same way as pure honeys and as a result, there is a growing need for rapid, simple, and accurate analytical methods to evaluate their characteristics and authenticity. In this work potential of UV-VIS and NIR spectroscopy coupled with PLS modelling and ANN modelling was analysed for the detection of adulteration and quantification of the physical and chemical proprieties of pure and adulterated honey samples. Acacia honey samples from Krapina-Zagorje County (Croatia) were adulterated by corn syrup (10–90%). The results indicate that PLS models developed in this work, except that for moisture content, can be used efficiently for screening (7<RER<20). ANN modelling provided accurate and simultaneous prediction of the properties of honey with correlation coefficients for validation above 0.8 so that these results show significant performance of ANNs modelling in the prediction of the physical and chemical properties of pure honey samples and adulterations based on combined UV-VIS NIR spectra.
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