Classification of raw Ethiopian honeys using front face fluorescence spectra with multivariate analysis

Abstract

Front face fluorescence measurements were carried out to classify raw honeys as such based on their floral origins. The excitation-emission matrix patterns of mixed flower, pseudoacacia, arabica, fials-indica, and amygdalina raw honeys along with fake honey sample from the market were examined by recording emission wavelength from 250 to 600 nm with excitation wavelength in the range of 200–550 nm. The spectra of fake honey samples demonstrated low intensity and did not fit within any one of the classified raw honeys. The multivariate analyses of the spectra were performed using principal component analysis and soft independent modeling of class analogy (SIMCA). The SIMCA model showed that the adulterate honey samples were detected with 100% sensitivity and specificity.