Comparative Evaluation of Colorimetric and Computer Vision Systems for Red Meat Color Analysis During Refrigerated Storage
Abstract
This study compared a traditional colorimeter device and a computer vision system (CVS) for monitoring color changes in beef tenderloin during refrigerated storage. Beef samples were obtained from 2-3-year-old male Simmental cattle, portioned into uniform slices, and stored at 4±2 °C for four days. Color was measured at 24-hour intervals by both methods, while aerobic plate counts (APC) and pH were also recorded. Over the 4-day storage period, both methods detected significant changes in Lab*, Chroma, Hue, and the redness index (RI), with microbiological and pH analyses confirming spoilage progression. CVS consistently yielded higher L*, b*, Chroma, and Hue values, whereas the colorimeter produced higher RI values due to lower b* measurements. A significant method and day interaction indicated that these differences persisted under dynamic storage conditions. The results suggest that due to its surface-focused measurement principle, CVS offers a reliable, practical, and non-destructive approach for both pointin- time assessments and continuous monitoring of red meat color.
Keywords
Ethical Statement
References
- Altun, S. K., Aydemir, M. E., Takım, K., Yilmaz, M. A., Yalcin, H. (2024). Inhibition of Nε-(carboxymethyl) lysine and Nε-(carboxyethyl) lysine formation in air-fried beef tenderloins marinated with concentrated cranberry juice. Food Bioscience, 60, 104336. https://doi.org/10.1016/j.fbio.2024.104336
- Aydemir, M. E., Altun, S. K., Takım, K., Yilmaz, M. A., Yalcin, H. (2024). nhibitory effect of homemade hawthorn vinegar-based marinade on Nε-(carboxymethyl)lysine and Nε-(carboxyethyl) lysine formation in beef tenderloins. Meat Science, 214, 109535. https://doi.org/10.1016/j.meatsci.2024.109535
- Barbut, S. (2001). Effect of illumination source on the appearance of fresh meat cuts. Meat Science, 59(2), 187–191. https://doi.org/10.1016/S0309-1740(01)00069-9
- Chmiel, M., Słowiński, M., Dasiewicz, K., Florowski, T. (2012). Application of a computer vision system to classify beef as normal or dark, firm, and dry. Journal of Animal Science, 90(11), 4126–4130. https://doi.org/10.2527/jas.2011-5022
- Girolami, A., Napolitano, F., Faraone, D., Braghieri, A. (2013). Measurement of meat color using a computer vision system. Meat Science, 93(1), 111–118. https://doi.org/10.1016/j. meatsci.2012.08.010
- Gonzalez, S. V., Zhai, C., Hernandez-Sintharakao, M. J., Geornaras, I., Nair, M. N. (2024). Evaluation of beef retail shelf-life following extended storage at low temperature. Meat and Muscle Biology, 8(1), 17649. https://doi.org/10.22175/mmb.17649
- Güngören, A., Akkemik, Y., Tufekci, E. F., Zengin, G., Emre, G., Gungoren, G., & Baloğlu, M. C. (2025). Applying chitosan-based films enriched with Borago officinalis extract for active and green packaging of fresh rainbow trout fillets. Foods, 14(4), 639. https://doi.org/10.3390/foods14040639
- Güngören, A., Güngören, G. (2025). Impact of correlated color temperature on red meat color assessment via image processing systems. Journal of Food Science, 90(11), e70660. https://doi.org/10.1111/1750-3841.70660
Details
Primary Language
English
Subjects
Veterinary Food Hygiene and Technology, Animal Science, Genetics and Biostatistics
Journal Section
Research Article
Publication Date
March 27, 2026
Submission Date
September 23, 2025
Acceptance Date
January 6, 2026
Published in Issue
Year 2026 Volume: 15 Number: 1
