We propose two convenient methods to quickly detect the presence of non-milk fat (palm oil) in butter, as well as to determine its amount in the product. For the first time, we have experimentally obtained the dependence of the size of drops of an alcoholic emulsion of oil or spread on the content of palm oil in it by the dynamic light scattering (DLS) method. We have also obtained the dependence of intensity ratio of the components of spread luminescence spectrum on palm oil content when excited at a wavelength λ = 266 nm. These results allowed us to propose two methods for determining the adulteration of butter with palm oil using DLS and measuring luminescence spectra. The two methods are physically independent but successfully supplement each other. DLS and luminescent methods for determining the proportion of palm oil give errors of no more than 10% and 6%, respectively.

The light field at the output of the Mach–Zehnder interferometer, where one of its arms contains a birefringent sample and a rotating polarizer is pl

We propose a simple noncontact spectral method for determining the presence or absence of milk pasteurization. The method is based on the pasteurization te

An increase in the intensity of photoluminescence spectra of organic phosphor with terbium Tb3+ ions intruded into a 3D photonic crystal, i.e., SiO2 opal m

Determination of the history of food processing, specifically the detection of undeclared use of reconstituted ingredients instead of fresh ones, remains a serious challenge. In dairy systems, such detection is difficult because conventional chemical markers reflect the cumulative history of time and temperature changes rather than specific processing steps. Although Raman spectroscopy is widely recognized as a non-destructive, high-throughput tool for screening molecular alterations, physicochemically interpretable ratiometric indices are still required, particularly for use in explainable AI models. To identify diagnostic spectral variances, a single batch of raw whole milk was evaluated across distinct states: raw, pasteurized (76, 88, and 98 °C), and spray-dried at outlet air temperatures of ≤70 °C and ~95 °C. The resulting whole milk powders were reconstituted to a 12.1% total solids mass fraction. Raman spectra were acquired using an M532 microscope (λ = 532 nm), and the analytical band areas at 1005, 1063, 1083, and 1121 cm⁻¹ were identified as key diagnostic markers. The structural indices I_lac and I_prot, which are mathematically orthogonal within the principal component space, were subsequently established. As a preliminary proof-of-concept, a binary logistic regression model achieved complete geometric separation between non-dried milk (including high-temperature pasteurized samples) and reconstituted milk. Within the training dataset, the false-positive rate for non-dried milk did not exceed 3.2%, whereas reconstituted milk classification model-predicted probability of belonging to the reconstituted class ranged from 96.8% to 99.9%. Furthermore, the proposed indices show great promise for classifying milk powders based on their heat treatment level. Nevertheless, further validation on independent commercial batches is strictly necessary to evaluate the proposed method’s robustness against matrix and instrumental variability.