A hyperspectral scatter imaging system was developed for contactless acquisition of spatially resolved diffuse reflectance profiles for optical characterization of turbid food products in the wavelength range 500 - 960 nm. To investigate the potential of this concept sugar foams with different microstructure, but similar chemical composition have been prepared by applying different mixing times to the same mixtures of sugar and albumin. Hyperspectral scatter images have been acquired from these samples and the absorption and reduced scattering coefficients have been derived from spatial reflectance profiles based on the diffusion approximation of the radiative transfer equation describing the light propagation in turbid media. The model-based optical properties estimation approach has been successfully validated on a set of liquid phantoms with known optical properties. The effect of the different mixing times on the foam microstructure could be clearly observed from the estimated reduced scattering coefficients ?s' spectra. On the other hand, similar absorption coefficient spectra were observed, confirming the identical chemical composition of the designed sugar foams. These results confirm that the hyperspectral scatter imaging technique has potential as a non-contact and rapid method for online quality control and process monitoring in the food industry.