Assessment of food compositional parameters by means of a Waveguide Vector Spectrometer

By processing spectral data with Partial Least Square Regression (PLS) algorithm, high levels of prediction accuracy were observed for all the tested products (R2 values from 0.940 to 0.999, in validation). Generally, both gain and phase waveforms appeared to be effective, for the selected foods, in terms of prediction accuracy. On the whole, the proposed system seems able to assess the content of varied substances both on simple and complex matrices. Simple prospective changes of the sample holder make the equipment potentially suitable for on-line monitoring of the quality of food products.