The applicability of conventional digital imaging to quantitative determination of fat and total protein in cow's milk, based on the phenomenon of light scatter, has been proved. A new algorithm for extracting features from digital images of milk samples has been developed. The algorithm takes into account spatial distribution of light, diffusely transmitted through a sample. The proposed method has been tested on two sample sets prepared from industrial raw milk standards, with variable fat and protein content. Partial Least-Squares (PLS) regression on the features calculated from images of monochromatically illuminated milk samples resulted in models with high prediction performance when analysed the sets separately (best models with cross-validated R 2=0.974 for protein and R2=0.973 for fat content). However when analysed the sets jointly with the obtained results were significantly worse (best models with cross-validated R2=0.890 for fat content and R2=0.720 for protein content). The results have been compared with previously published Vis/SW-NIR spectroscopic study of similar samples.
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