UTILIZAÇÃO DE ESPECTROSCOPIA FOTOACÚSTICA E FLUORESCÊNCIA DE RAIOS X COM ABORDAGEM QUIMIOMÉTRICA PARA CLASSIFICAÇÃO E ESTIMAÇÃO DE MINERAIS EM GEOPRÓPOLIS

Abstract

Geopropolis is an apicultural product composed mainly of soil, about 90%, in addition to plant resins and enzymatic secretions of bees, which are used as raw material for the construction of internal and external structures of the hive. It has several biological properties, which are associated with the geographic characteristics where the colony is located, according to the flora, climate and bee species. Studies have shown that geopropolis has several pharmacological activities such as antimicrobial, anti-inflammatory, antioxidant, immunomodulatory, antitumor and among others. In addition to its importance for the health area, it has the potential to be a good indicator of contaminants in soils. Considering the wide application of geopropolis in several areas and sectors and the lack of studies of this bee product, in this work the chemical composition was estimated and the minerals present in the geopropolis samples were determined by the techniques, photoacoustic spectroscopy (PAS) and x-ray fluorescence by dispersive energy (EDXRF). In the photoacoustic spectra results, bands between 250 and 350 nm and others between 350 and 400 nm were observed, characteristic of some phytochemical compounds present in geopropolis such as quercitin, chrysin, p-coumaric acid, gallic acid and kaempferol. However, in general, the photoacoustic spectra are very similar, making it difficult to distinguish between samples. Through the qualitative analysis of the EDXRF technique, the following minerals were identified: Al, Si, P, S, K, Ca, Ti, Cr, Mn, Fe, Cu, Zn, Sr and Zr. In the quantitative analysis, an empirical calibration method was developed from the reference material SQC001, which was validated for an error of less than 20%. In this way, the concentrations of Si, K, Ca, Cr, Mn, Fe and Zn minerals present in the samples were estimated. Also, through the data of the PAS and EDXRF techniques, the samples of the species M. marginata, M. quadrifasciata and T. angustula were classified by logistic regression (LR) and principal component analysis (PCA), where the results showed that both the chemical composition and mineral from the samples can be used to classify the species of bees that produce geopropolis.