Detection of urea in milk using two-dimensional correlation spectroscopy and partial least square method

For the detection and quantification of urea in milk, pure milk samples and 40 adulterated milk samples added different contents of urea were prepared. Then 2D correlation (NIR-NIR, IR-IR, NIR-IR) spectroscopy under the perturbation of adulteration concentration was calculated and the spectra in the range of 4 200-4 800 cm-1 and 1 400-1 704 cm-1 were selected to construct the partial least square (PLS) calibration model, respectively. The PLS calibration model showed 4 200-4 800 cm-1 was the better range for calibration performance and the root mean square errors of cross validation (RMSECV) of the model was 0.266 g/L. When using this model for predicting the urea contents in prediction set, the root mean square errors of prediction (RMSEP) was 0.219 g/L and the coefficient correlation of actual values and predicted values was 0.999, which means the model has good prediction ability. The method can be used for a correct discrimination on whether the milk is adulterated and provides a new and cost-effective alternative to test the adulteration of milk.