Color is one of the most important metrics of foodstuffs quality. It gives an indication of freshness, ingredient composition as well as about the presence or absence of falsification. Most often, the color is estimated visually, and thus, the evaluation is subjective. By automating the color analysis a wide application for this method could be found. The aim of this research is to study the principles of color analysis as applied to the task of evaluating the freshness of meat products using modern machine vision systems. From a scientific point of view, the color of meat depends on the proportion of myoglobin and its derivatives. It's the main pigment that characterizes the freshness of meat. Further color of meat can change due to oxidation of myoglobin during storage. Myoglobin exists in three forms. There are oxygenated form, oxidized form and form without oxygen. The meat color changes not only due to the conversion of one form into another. The content of amino acids and ammonia are another characteristics and constant signs of meat products spoilage. The paper presents the results of meat color computer simulation based on data on the content of various forms of myoglobin in different proportions. The spectral characteristic of the light source used to illuminate the meat sample is taken into account. Also the experimental studies were conducted using samples of beef. As a result the correlations between said biochemical indicators of the quality and color of the meat obtained with the help of machine vision system were found.