USO DA REGRESSÃO LINEAR MÚLTIPLA COMBINADA COM ADIÇÃO DE PADRÃO (MLR-SA) E ANÁLISE EXPLORATÓRIA DE IMAGENS DIGITAIS NA AVALIAÇÃO DO PERFIL FÉRRICO EM INFUSÕES DE PLANTAS MEDICINAIS

USE OF MULTIPLE LINEAR REGRESSION COMBINED WITH STANDARD ADDITION (MLR-SA) AND EXPLORATORY ANALYSIS OF DIGITAL IMAGES IN THE EVALUATION OF FERRIC PROFILE IN MEDICINAL PLANT INFUSIONS. Iron plays an essential role in the metabolic balance of living beings. Iron also acts as an indicator of redox conditions in the aquatic environment, and a nutrient available in the soil for plant cultivation, which can be released during consumption. The iron content in samples of medicinal plant infusions was monitored by colorimetry, through the acquisition of digital images by smartphone, through the formation of the [Fe(H2O)5(SCN)]2+ complex in small sample volumes (500 µL). This work proposes a promising combination of standard addition calibration with multiple linear regression (MLR-SA) combined with exploratory analysis tools (principal component analysis, PCA, and hierarchical cluster analysis, HCA) to characterize an iron bioavailability profile in infusion samples. Calibration models were obtained with up to 97% of variance explained even in conditions of external light interference and matrix effects. The exploratory analysis revealed a ferric profile of commercial infusions distinguishable from infusions of natural origin. The multivariate approach to digital imaging data has proven to be an alternative methodology for affordable and sustainable monitoring of iron in infusion samples.