Minerals assessment and sodium control in hamburger by fast and green method and chemometric tools

Abstract

The aim of this study was to investigate the feasibility of applying near infrared spectroscopy (NIR), associated with multivariate calibration, which is characterized as a fast and green technique, to evaluate Fe, Ca, K and Na in commercial hamburger samples and for sodium control, according to the law. PLS models obtained by NIR to predict the essential mineral content showed Standard Error of Prediction (SEP) values from 0.34 to 68.01 mg/kg; RE from 0.5 to 2.78% and R2cal from 0.85 to 0.96. PLS-DA were performed in order to classify samples regarding sodium content control and it was concluded that the classification model was efficient with high selectivity and sensitivity. The results showed that the PLS models-discriminant and regression-associated to NIR vibrational spectroscopy technique can be successfully used to control essential minerals Fe, Ca and K besides of quantify and detect hamburger with high content of Na, with shorter analysis time after simple sample preparation by grinding