Developing a machine vision system for simultaneous prediction of freshness indicators based on tilapia (Oreochromis niloticus) pupil and gill color during storage at 4°C

Ce Shi; Jianping Qian; Shuai Han; Beilei Fan; Xinting Yang; Xiaoming Wu

doi:10.1016/j.foodchem.2017.09.047

Developing a machine vision system for simultaneous prediction of freshness indicators based on tilapia (Oreochromis niloticus) pupil and gill color during storage at 4°C

Food Chem. 2018 Mar 15:243:134-140. doi: 10.1016/j.foodchem.2017.09.047. Epub 2017 Sep 18.

Authors

Ce Shi¹, Jianping Qian¹, Shuai Han¹, Beilei Fan¹, Xinting Yang², Xiaoming Wu¹

Affiliations

¹ Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China; National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; National Engineering Laboratory for Agri-product Quality Traceability, Beijing 100097, China.
² Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China; National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; National Engineering Laboratory for Agri-product Quality Traceability, Beijing 100097, China. Electronic address: yangxt@nercita.org.cn.

PMID: 29146319
DOI: 10.1016/j.foodchem.2017.09.047

Abstract

The study assessed the feasibility of developing a machine vision system based on pupil and gill color changes in tilapia for simultaneous prediction of total volatile basic nitrogen (TVB-N), thiobarbituric acid (TBA) and total viable counts (TVC) during storage at 4°C. The pupils and gills were chosen and color space conversion among RGB, HSI and L^∗a^∗b^∗ color spaces was performed automatically by an image processing algorithm. Multiple regression models were established by correlating pupil and gill color parameters with TVB-N, TVC and TBA (R²=0.989-0.999). However, assessment of freshness based on gill color is destructive and time-consuming because gill cover must be removed before images are captured. Finally, visualization maps of spoilage based on pupil color were achieved using image algorithms. The results show that assessment of tilapia pupil color parameters using machine vision can be used as a low-cost, on-line method for predicting freshness during 4°C storage.

Keywords: Chilled storage; Color parameters; Freshness indicators; Machine vision; Pupil and gill; Tilapia.

MeSH terms

Animals
Cold Temperature*
Color
Eye*
Food Quality*
Food Storage / methods*
Gills*
Nitrogen / analysis
Thiobarbiturates / analysis
Tilapia / anatomy & histology*

Substances

Thiobarbiturates
thiobarbituric acid
Nitrogen