Urea is added as an adulterant to give milk whiteness and increase its consistency by improving the non-fat solids content, but excessive amounts of urea in milk causes overload and kidney damage. A sensitive method for detecting and quantifying urea adulteration of milk has been developed using FT-NIRS (Fourier Transformed Near Infra Red Spectroscopy) coupled with multivariate analysis. The model was developed using 162 fresh milk samples, consisting of 20 non-adulterated samples (without urea), and 142 samples with the urea adulterant at 8 different concentrations (0.10%, 0.30%, 0.50%, 0.70%, 0.90%, 1.10%, 1.30%, and 1.70%), each prepared in triplicate. The NIR data coupled with the PLS‐DA (Partial Least Squares -Discriminant Analysis) model can be used to discriminate between the unadulterated fresh milk samples and those adulterated with urea. Furthermore, the NIR data coupled with PLSR (Partial Least Squares Regression) models may be used to quantify the level of the urea in milk samples.
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