TITLE:
Developing a Machine Vision System Equipped with UV Light to Predict Fish Freshness Based on Fish-Surface Color
AUTHORS:
Qiuhong Liao, Chao Wei, Ying Li, Lin’an Guo, Huaxue Ouyang
KEYWORDS:
Fish Freshness, Machine Vision, UV Light, Color Parameters
JOURNAL NAME:
Food and Nutrition Sciences,
Vol.12 No.3,
March
16,
2021
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.