Spectral Separation Degree Method for Vis-NIR Spectral Discriminant Analysis of Milk Powder Adulteration

Abstract

Quick and easy spectral discrimination technology of milk powder adulterated has important application prospects. The separation degree spectrum between the two spectral populations and a wavelength selection method based on the separation degree priority combination (SDPC) were proposed here. The wavelength step by step phase-out (WSP) method was used for secondary wavelength optimization. Using Vis-NIR spectroscopy combined with SDPC-WSP-PLS-DA method, the discriminant analysis models for milk powder adulterated were established. Among them, standard normal transformation (SNV) and Norris derivative filtering (NDF) were used in turn for the spectral preprocessing with the NDF parameters of d = 2, s = 11, g = 5. The selected optimal SDPC-WSP-PLS-DA model used only 8 wavelengths to achieve high-precision discrimination effect in modeling (100%) and independent validation (96.0%). The results shower the feasibility of applying Vis-NIR spectroscopy to high-precision discriminant analysis of milk powder adulteration. The proposed spectral separation degree method can enhance the spectral difference of different spectral populations, extract information wavelengths, and improve the discrimination effect.