Caracterização de fórmulas infantis para lactentes usando espectroscopia no infravermelho médio

Abstract

This work focuses on the use of Fourier Transformed Mid Infrared Spectroscopy (FT-MIR) coupled to Attenuated Total Reflectance (ATR), combined with multivariate calibration as Principal Component Analysis (PCA) and Partial Least Squares (PLS) to characterize and quantify the majority composition of infant formulas. Twenty trademarks marketed in Juiz de Fora (MG) were evaluated from four different industries. The majority composition of the samples (lipid content, true protein, carbohydrates, moisture, total solids and ashes) was determined by physicochemical methods, in duplicate, according to official analysis methodologies. The results, in general, comply with current legislation. On the other hand, the spectroscopic evaluation of the formulations was performed in the MIR region from 4000 cm-1 to 400 cm-1. Using statistical tools, it was possible to interpret the generated spectra and characterize the composition of the infant formulas tested, in comparison to the main claims described in the labels and in the literature. The suggested propositions were confirmed by the behavior of these samples when compared to PCA. It can be said that FT-MIR-ATR spectroscopy was able to characterize the different formulations tested, when allied to multivariate statistics. In relation to the Regression by PLS, only a correlation was found between physicochemical data and MIR spectra in the interval between 1400 cm-1 and 1000 cm-1, and therefore, it was used for the predictions of the analytical values. Because it is the characteristic region of carbohydrate absorption, the model presented the best results in the prediction of the content of this component, with a calibration curve profile and at the same time presented bad predictions for the rest of the attributes tested. It is suggested that the model has potential for physicochemical predictions, especially for carbohydrates, if calibration curves are made for this type of food matrix.