Anais do Simpósio Latino Americano de Ciências de Alimentos
Actas del 14 SLACA - Simposio Latinoamericano de Ciencia de los Alimentos

Honey is a chemically complex matrix because of the great diversity of forage sources for honey bees in the Brazilian flora. Over the years, efforts have been made to improve the analytical techniques for characterizing honey, further enhancing the value of the product in the market. In this sense, this study aimed to chemically characterize polyfloral honeys originated from the states of Santa Catarina (SC, n = 51) and São Paulo (SP, n = 10) through a typical metabolomic analytical platform, i.e., UV-vis spectrophotometry (200-800 nm), near-infrared (NIR, 800-2500 ɳm), and 1H nuclear magnetic resonance (1H-NMR) spectroscopy. Honey samples from the 2019-2020 harvest were analyzed in triplicate and the metabolomic data set was pre-processed (baseline correction, smoothing, and multiplicative dispersion correction), following principal component analysis (PCA). Besides, the total phenolic content (TPC) of the samples was determined (Folin-Ciocalteau reagent) and the five samples with higher contents for each state were further profiled by 1H-NMR (300 MHz). The PCA of the UV-vis data set covered 97% of the sample’s total variance and discriminated the SP honeys (PC2+, PC1-) from the SC ones. The NIR spectral profiles revealed prominent bands assigned to water (0-H) and carbohydrates (O-H and C-H), but the description models built did not discriminate samples. The TPC of SC honeys varied between 2.33 and 9.53 mg GAE.g-1, as SP ones showed lower contents (0.76 to 5.83 mg GAE.g-1). Besides, the five honey samples with the highest TPC revealed distinct 1H-NMR profiles in respect to their geographic origins, i.e., SC and SP. It was found that the analytical techniques employed, especially UV-vis, can help quickly, cheaply, and cleanly characterize the SC and SP polyfloral honeys, revealing different chemical profiles which may be linked to the diversity of flora and other (a)biotic factors in the production regions.