Identification and Detection of Adulterated Butter by Colorimetry and Near-IR-Spectroscopy

Abstract

A rapid and simple method for identification of oil and fatty products of plant origin by their own fluorescence and diffuse reflection of IR radiation using colorimetry and near-IR spectroscopy is proposed. Analytical signals were recorded using 3D-printed devices with built-in UV and IR LED matrices (390 and 850 nm) and a smartphone with the PhotoMetrix PRO® application installed and FTIR spectroscopy in the near-IR region (10,000–4000 cm^–1) with the NIRA attachment used for the analysis of solids. Diffuse reflectance spectra were processed using the TQ Analyst and The Unscrambler X applications. The studied objects were identified and differentiated using chemometric algorithms, i.e., principal component analysis (PCA) and hierarchical cluster analysis (HCA). The mass fraction of fat in the declared products was determined using univariate and multivariate (PLS algorithm) analyses. Adulterated butter was located separately from natural products on the PCA and HCA graphs. They did not intersect with each other on the dendrogram. Samples of butter with different milk fat mass fractions (61.5, 72.5, 82.5, and 99.0%) were used to construct a calibration relationship and determine the milk fat concentration using the PLS method and univariate analysis. The calibration error (RMSEC) were ≤1.31%; the predictive properties (RMSEP), ≤4.45%. The methods under consideration were tested with samples of butter and vegetable oil products from various manufacturers. The RMSEP values for dairy products was ≤4.97%; for margarine, >10% using multivariate analysis. The relative deviation of the results from the mass fractions of fat indicated on the packaging was ≤4.8% when using univariate analysis. This parameter for margarine was in the range 96.3–96.5%. The results correlated with those of FTIR spectroscopy.