The current study presents an application of Diffuse Reflectance Infrared Fourier Transform Spectroscopy for detection and quantification of fraudulent addition of commonly employed adulterants (spent coffee grounds, coffee husks, roasted corn and roasted barley) to roasted and ground coffee. Roasted coffee samples were intentionally blended with the adulterants (pure and mixed), with total adulteration levels ranging from 1% to 66% w/w. Partial Least Squares Regression (PLS) was used to relate the processed spectra to the mass fraction of adulterants and the model obtained provided reliable predictions of adulterations at levels as low as 1% w/w. A robust methodology was implemented that included the detection of outliers. High correlation coefficients (0.99 for calibration; 0.98 for validation) coupled with low degrees of error (1.23% for calibration; 2.67% for validation) confirmed that DRIFTS can be a valuable analytical tool for detection and quantification of adulteration in ground, roasted coffee.
Keywords: Barley; Coffee adulteration; Coffee husks; Corn; DLATGS; DR; DRIFTS; Deuterated Triglycine Sulfate Doped with l-Alanine; Diffuse Reflectance Infrared Fourier Transform Spectroscopy; FTIR; Fourier Transform Infrared Spectroscopy; LDA; Linear Discriminant Analysis; MSC; NIRS; PLS; Partial Least Squares Regression; RMSEC; RMSECV; RMSEP; RS; Raman spectroscopy; SNV; Spent coffee grounds; diffuse reflectance; multiple scatter correction; near infrared spectroscopy; root mean square error for calibration; root mean square error for cross validation; root mean square error for validation; standard normal variates.
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