Abstract
This study assessed the feasibility of developing a machine vision system equipped with ultraviolet (UV) light, using changes in fish-surface color to predict aerobic plate count (APC, a standard freshness indicator) during storage. The APC values were tested and images of the fish surface were taken when fish were stored at room temperature. Then, images’ color-space conversion among RGB, HSV, and L*a*b* color spaces was carried out and analyzed. The results revealed that a* and b* values from the UV-light image decreased linearly during storage. A further regression analysis of these two parameters with APC value demonstrated a good exponential relationship between the a* value and the APC value (R2 = 0.97), followed by the b* (R2 = 0.85). Therefore, our results suggest that the change in color of the fish surface under UV light can be used to assess fish freshness during storage.
Highlights
Fish is a leading source of high-quality protein and plays an important role in human nutrition
This study assessed the feasibility of developing a machine vision system equipped with ultraviolet (UV) light, using changes in fish-surface color to predict aerobic plate count (APC, a standard freshness indicator) during storage
The rapid increase in the APC value began at 18 h storage
Summary
Fish is a leading source of high-quality protein and plays an important role in human nutrition. The harvesting and consumption of fish has continued to increase [1]. In addition to its contribution to human health, the freshness of fish is crucial to consumer acceptance of fish as a food source as well as to the credibility of the international fishery trade [2]. After the fish dies, quality degrades quickly owing to pre-harvest and post-mortem factors, with a loss of acceptable appearance, taste, and nutritional quality. The ability to determine freshness is critical to the research and development of the fishing industry
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