Chemometric model for rapid detection of urea and hydrogen peroxide in milk
DOI:
https://doi.org/10.3329/bjsir.v56i1.52689Keywords:
Fourier-Fransform Infrared spectroscopy (FTIR); Multiplicative Scatter Correction (MSC); Savitzky-Golay derivative; Partial Least-Square Regression (PLSR)Abstract
A simple and cost effective method has been developed for determination of adulteration in milk with urea and hydrogen peroxide by using chemometric modeling with Fourier Transform Infrared (FTIR) spectroscopic data. Milk samples were purchased from a dairy farm (South Banasree, Dhaka, Bangladesh) and spiked at different concentrations of urea and hydrogen peroxide. Spectral data of all samples were collected using ATR-FTIR spectrophotometer. After acquisition of spectral data, they were preprocessed with transformation techniques such as multiplicative scatter correction (MSC) and savitzky-golay derivative. The predictive performance of principal component regression (PCR) and partial least-square regression (PLSR) methods were assessed by relative prediction errors and recoveries (%) were compared . PLSR shows better prediction efficiencies over PCR with R2 value 99% for urea and 95% for hydrogen peroxide.Six brands of commercial milk samples have been evaluated by this method and the samples contain 21.66-44.73 mg urea and 1.62-2.86 mg hydrogen peroxide in 100 ml milk. This method can be easily used in the quality assessment of milk.
Bangladesh J. Sci. Ind. Res.56(1), 1-8, 2021
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