Research and Analysis of Shelf Life Model Prediction Based on Arrhenius Equation

Abstract

The shelf life of food will undergo a series of quality changes with changes in storage temperature and time, which is an important factor that needs to be considered in the process of cold chain logistics. In this thesis, a shelf prediction model kinetic model based on the Arrhenius equation was established, and a linear regression model was used to fit a variety of biological experimental data to discuss the changing law of the quality of pretreated food under different storage temperatures. The results show that the calculation results of the model can predict the shelf life more accurately, and at the same time, because the complex integral calculation is avoided, the calculation consumption can be significantly reduced, which provides a way to think about related research.