A mechanistic model to predict headspace concentration profile of carvacrol for controlled release packaging

Abstract

The efficacy of an antimicrobial agent in food packaging depends largely on its concentration profile in the package headspace. In this study, a mechanistic mathematical model was developed to predict the headspace concentration profile of carvacrol, a prominent antimicrobial agent, using the physical principles that govern the movement of carvacrol molecules in a controlled release packaging system. The model and its estimated parameter values were validated using three different sets of gas chromatography measurements—this rigorous process confirms the accuracy and reliability of the model. Advancing beyond existing models, our model enhances the understanding of the dynamics between the concentration profile and its interacting processes including evaporation, adsorption, and gas transmission. It provides packaging developers with a superior alternative to the trial-and-error approach to tailor concentration profiles for optimizing antimicrobial efficacy. It leads to more efficient and better design of controlled release packaging.