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Exactly six-hundred (600) scientific articles that report milk and milk products’ color results in scientific journals in the last couple of decades were reviewed. Thereof, the greatest part of the articles derived from Europe (36.3%) and Asia (29.5%). The greatest share of researchers used Minolta colorimeters (58.8%), while 26.3% of them used Hunter devices. Most reports were on cheese (31.0%) followed by fermented products (21.2%). Moreover, the highest number of papers reported color data of milk and milk products made from cow’s milk (44.81%). As expected, goat’s cheese was the brightest (L* = 87.1), while cow’s cheese was the yellowest (b* = 17.4). Most importantly, it appeared that color research results reported were often impossible to replicate or to interpret properly because of incomplete description of the methodology. In some of the manuscripts reviewed, illuminant source (61.0%), aperture size (93.8%), observer angle, and number of readings (over 70% of all cases) were not reported. It is therefore critical to set rules regarding the description of the methodology for (milk) color research articles in order to ensure replicability and/or comparison of studies.

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The ability of a computer vision system to evaluate the color of meat and meat products was investigated by a comparison study with color measurements from a traditional colorimeter. Pros and cons of using a computer vision system for color evaluation of meat and meat products were evaluated. Statistical analysis revealed significant differences between the instrumental values in all three dimensions (L*, a*, b*) between the computer vision system and the colorimeter. The computer vision system-generated colors were perceived as being more similar to the sample of the meat products visualized on the monitor, compared to colorimeter-generated colors in all (100%) individual trials performed. The use of the computer vision system is, therefore, considered a superior and less expensive alternative to the traditional method for measuring color of meat and meat products. The disadvantages of the computer vision system are its size, which makes it stationary, and the lack of official manufacturers that can provide ready-to-use systems. This type of computerized system still demands experts for its assembly and utilization.

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