The use of NIR hyperspectral imaging have gained importance in the analysis of food, helping in the combat of the adulteration. Faced with the routine analysis of food quality control, NIR hyperspectral imaging provides results of the distribution of components in the surface of the sample in a short time, with little or no sample preparation, avoiding external contamination risks. In this work, the NIR hyperspectral imaging in combination with multivariate curve resolution method (MCR) allowed the detection of a quaternary mixture of milk adulterants, such as starch, sucrose, whey powder and urea.
The analysis of milk powder surfaces were conducted using the Spotlight 400N FT-NIR Imaging System from Perkin-Elmer. Tablets were made with powdered milk samples containing different concentrations of contaminants starch, sucrose, whey powder and urea, which were placed on supports for microscopy and subsequently accommodated on the positioner. By using a joystick, the focus and the area to be analyzed were adjusted. The conditions for the analysis were 32 scans analyzing individual pixels of 25 μm2 and 4 mm2 area in the range of 4000-10000 cm-1. The data obtained from the pure samples and mixtures were converted to log1/R and it was applied as a pre-treatment the SNV (Standard Normal Variate) with the aim of reducing the light scattering.
The data set generated were converted in matrices and processed by MCR algorithm, in routines developed for Matlab 2009b.
Ten samples containing mixtures of milk powder and different concentrations of starch, sucrose, whey powder and urea were analyzed. Through the images generated by the MCR was possible to distinguish each of the four contaminants and confirmation was accomplished comparing the pure spectra of each constituent with the spectra recovered. The MCR method was suitable for the detection of contaminants in the range of 1 to 7%.