Dynamic prediction model of ripening degree of Chinese spicy cabbage under fluctuation temperatures

Abstract The objective of this study was to investigate the effect of temperature on the change of titratable acidity in Chinese spicy cabbage (CSC) and develop a dynamic prediction model to determine the ripening degree of CSC under fluctuation temperatures. So, the changes of titratable acidity in CSC were measured under different storage temperatures and a kinetic model of titratable acidity under constant temperatures was established. Then the dependence of the change of titratable acidity on temperature was adequately modeled by the Arrhenius equation. In the end, a dynamic prediction model under fluctuation temperatures was established based on the exponential model and the Arrhenius equation. The results showed the changes of titratable acidity in CSC increased gradually with storage time and temperature within a certain temperature range. The model of titratable acidity under constant temperatures fitted well with the change of titratable acidity. The activation energy value in the Arrhenius equation was 57.9 kJ mol−1. The dynamic prediction model under fluctuation temperatures was established and the validation results showed that changes of the CSC quality could be predicted based on the prediction models. There, the consumers could understand the maturity of fermented vegetables by the prediction model without opening the package.