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Visual properties of horticultural produces are important quality characteristics. A machine vision system can provide with quantitative shape and color characterization and can be the basis of the quality assurance either in the classification process or during the post-harvest treatments. Objectives of our work were to analyze and model of the color change trend of different produces and varieties and on the basis of this analysis to develop methods and software for determination of the ripeness stage and for detection of surface defects of produces.

Apricot and tomato samples were tested to describe the color distribution in different ripeness stages. Definite trend of the color change of sound fruits was found during the ripening/post-ripening process for the tested varieties. Different trends were described for each cultivars and the models were added to the expert system data base developed for description of the regular color properties of cultivars in different ripeness stages. Surface defects can be recognized on the basis of color irregularities that is the deviation from the regular trend. A quality assessment software was developed for the tested cultivars to determine the ripeness stage and to detect the surface defects.