Simultaneous detection for adulterations of maltodextrin, sodium carbonate, and whey in raw milk using Raman spectroscopy and chemometrics

To achieve rapid on-site identification of raw milk adulteration and simultaneously quantify the levels of various adulterants, we combined Raman spectroscopy with chemometrics to detect 3 of the most common adulterants. Raw milk was artificially adulterated with maltodextrin (0.5-15.0%; wt/wt), sodium carbonate (10-100 mg/kg), or whey (1.0-20.0%; wt/wt). Partial least square discriminant analysis (PLS-DA) classifica-tion and a partial least square (PLS) regression model were established using Raman spectra of 144 samples, among which 108 samples were used for training and 36 were used for validation. A model with excellent per-formance was obtained by spectral preprocessing with first derivative, and variable selection optimization with variable importance in the projection. The clas-sification accuracy of the PLS-DA model was 95.83% for maltodextrin, 100% for sodium carbonate, 95.84% for whey, and 92.25% for pure raw milk. The PLS model had a detection limit of 1.46% for maltodextrin, 4.38 mg/kg for sodium carbonate, and 2.64% for whey. These results suggested that Raman spectroscopy com-bined with PLS-DA and PLS model can rapidly and efficiently detect adulterants of maltodextrin, sodium carbonate, and whey in raw milk.

Automated summary

In this study, Raman spectroscopy combined with chemometrics was successfully used for rapid on-site identification and quantification of common adulterants in raw milk. The method of Raman spectroscopy combined with PLS-DA and PLS model can accurately detect maltodextrin, sodium carbonate, and whey adulteration, and has high classification and detection accuracy.