Development and assessment of a shelf life prediction system for cultured fish

Based on the growth kinetics data of Pseudomonas spp. on naturally contaminated cultured Tilapia stored at 0℃, 5℃, 10℃ and 15℃, a growth kinetics model of Specific Spoilage Organisms(SSO) Pseudomonas spp. at 0～15℃ was set up. With the help of Visual Basic, quality monitoring and remaining shelf life prediction expert system was developed for circulating fresh product of Tilapia in chill chain. It was shown from the reliability assessment between predictive remaining shelf life(RSL) and observed RSL that basic error was within ±10% and the system could rapidly and reliably predict the freshness and RSL of cultured Tilapia. The approach of SSO growth kinetics model by using experimental data on naturally contaminated fish, effectively solved the difficulty in predicting the microbial growth at the kinetic temperatures and enhanced the accuracy and practicability of the system. The system was a rapid and valuable tool to design and assess technological parameters, predict and monitor freshness of fresh fish in the chill chain.