Caracterização físico-química e capacidade antioxidante de méis comercializados no Espírito Santo

Abstract

The chemical composition, as well as the presence of antioxidants in honey, is mainly related to its botanical origin, region, and climate. Thus, based on the study of the total antioxidant capacity (TAC), together with the analysis of the total phenolic compounds (TPC) and the total flavonoid compounds (TFC), it is possible to classify the honey according to their composition. TAC was determined using spectrophotometric (ferric reducing antioxidant power, FRAP) and electrochemical (ceric reducing antioxidant capacity, CRAC) assays. All honey analyzed from Apis mellifera had representative TAC, TPC, and TFC values, with camará flowers outstanding. To evaluate the quality of the honey, the methods of humidity, diastase activity, hydroxymethylfurfural (HMF), total acidity (TA), and water activity (Aw) were used. Among the samples studied, the camará honey (5) and the wild honey (2) had high contents of humidity (20.10 – 20.87%), TA (65.12 – 65.49 mEq kg−1 ), and HMF (> 60 mg kg−1 ), above the limits required by the Brazilian legislation, indicating that this honey was out of date or with possible adulteration. All samples tested in the study had values above the norm. In addition, we found that the color of honey can interfere with the analysis of FRAP assay, with a Pearson correlation of 0.77 between the two variables. In this sense, the CRAC assay represents a new alternative for the evaluation of TAC in the honey bee. Moreover, the classification of honey requires the use of a method that can determine its chemical composition. In this sense, the techniques of infrared (Fourier transform infrared, FTIR) and voltammetry (cyclic voltammetry, CV) were applied to get these data. The classification and analysis of the results must then be done using a chemometric treatment. At the end of this study, it was found that the characterization by CV and FTIR allows the classification of the honey according to the flowering period, revealing the closeness between the groups of samples with predominant coffee flowering. However, further studies need to be conducted to build a more robust statistical model with an analysis of more honey samples for each flowering.