Prediction of shelf life for quick-frozen dumpling based on BP neural network and effective accumulated temperature theory

In order to well predict the shelf life of quick frozen food during the temperature-fluctuation storage, and accurately monitor its quality changes, frozen-dumplings stored with fluctuant temperature from -28 to -12℃ were studies. Physicochemical indices including acid value, peroxide value, moisture content of dumpling skin, brightness of dumpling skin and sensory evaluation were determined. BP neural network was applied to predict the shelf life of quick-frozen dumplings combined with effective accumulated temperature theory. And kinetic model was used to take comparative analysis. The results showed that the predictive value for BP neural network fitted well with the experimental value, and the maximum error was 3.29%. The maximum error of the test experiment for BP neural network was 2.74%, which was less than that of the kinetic model (5.62%). BP neural network provides a new way to predict the shelf life of quick frozen food.