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https://doi.org/10.1016/j.compag.2017.05.006

has been cited by the following article:

• 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.