Mathematical Evaluation of Prediction Accuracy for Food Quality by Time Temperature Integrator of Intelligent Food Packaging through Virtual Experiments

Abstract

Prediction of the quality of packaged foods using a colorimetric time temperature integrator (TTI) is affected by the types of kinetic models for the TTIs and the associated food qualities. Several types of kinetic models were applied for the TTI color change (four types) and food microbial growth (three types). To evaluate the prediction, a virtual experiment data of the food microbial growth were mathematically created by using the relevant kinetic models. In addition to the kinetic models, two types of temperature-dependent models (Arrhenius and square root models) were used in the calculation. Among the four types of TTIs, M2-3510 or S type for Pseudomonas spp. and M type for Listeria monocytogenes and Escherichia coli showed the least erroneous results. Overall, a suitable TTI could be selected for each food microorganism, based on the prediction accuracy.