Time–temperature integrators as predictive temperature sensors

This work presents the idea of predictive time–temperature integrator sensors (pTTIs) as a means to recover and to predict safety and quality evolution in thermal processing. Predictive TTIs combine a rigorous and computationally efficient model of the process with standard TTIs. The calibration of the pTTIs requires several steps, including the definition of the model, the appropriate means for its simulation and the use of adequate parameter estimation and optimal experimental design techniques to recover food and package thermo-physical properties. s show how a limited number of experiments and standard TTIs are required to calibrate predictive sensors. Possible uses include the prediction of microbial lethality and quality attributes, recovery of processing conditions considering eventual perturbations or optimal process design. ation and uses are illustrated here with examples related to the tunnel pasteurization of highly viscous liquid foods.