Bee pollen samples were discriminated using vibrational spectroscopic methods by connecting with botanical sources, composition, and color. SEM and light microscope images of bee pollen loads were obtained and used to assess the botanical origin. Fourier transform (FT) mid- and near-infrared (FT-MIR, FT-NIR), and FT-Raman spectra of bee pollen samples (a set of randomly chosen loads can be defined as an independent sample) were measured and processed by principal component analysis (PCA). The CIE L*a*b* color space parameters were calculated from the image analysis. FT-MIR, FT-NIR, and FT-Raman spectra showed marked sensitivity to bee pollen composition. In addition, FT-Raman spectra indicated plant pigments as chemical markers of botanical origin. Furthermore, the fractionation of bee pollen was also performed, and composition of the fractions was characterized as well. The combination of imaging, spectroscopic, and statistical methods is a potent tool for bee pollen discrimination and thus may evaluate the quality and composition of this bee-keeping product.
Keywords: bee pollen; color; discrimination; image analysis; spectroscopic methods.