Abstract
The produce of food, oil-producing, drug, and cosmetic industry are in general the liquid or semi-liquid dispersions. The spectral analysis of them is labored by poorly known multiple scattering of radiation by particles and molecule aggregates of disperse phase. Our purpose was to investigate the influence of the structural parameters of dispersion consisting of weakly absorbing condensed particles and of a strongly absorbing media onto their near-infrared spectra, having in view to discriminate the disperse phases by their sizes. In this paper, we present the application of a laser correlation spectrometry of scattered light and of a multi-component partial least square regression for study of correlation between near-infrared spectra of dispersions and a particle density and size variations. Studied dispersed systems were milk compositions enriched by two different protein fractions – globulin and casein, and solutions of hydrated surfactant micelles, having some parameters similar to globulin fraction. The well-known structure model of surfactant micelles and laser correlation spectrometry of scattered light were used for acquiring the reference sample set of dispersions standardized upon the particle density and size value of nanometer range. Partial least square regression between near-infrared spectra and nano-particles density variations shows robust correlation of high level in spite of negligible particle absorption. For the first time, on our knowledge, calibration was built taking into account the efficiency of interaction between the dispersive nano-particles. Acquired knowledge about the influence of dispersion structure parameters on near-infrared spectrometer calibration allows developing the simple device for discrimination of dispersion on the structure parameters; in particular, for detecting the counterfeit of milk protein with inferior serum concentrates.
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