Numerical modeling of CO2 gas diffusion in food as a porous medium with application to Soluble Gas Stabilization technology

Sammendrag

Soluble gas stabilization (SGS) is an emerging preservation technology in which food products are pre-saturated with carbon dioxide (CO2) prior to packaging to exploit its bacteriostatic effects. The effectiveness of SGS is governed by CO2 diffusion within the food matrix; however, this diffusivity cannot be directly measured and is typically estimated through time-consuming experiments combined with empirical modeling. In this study, a predictive numerical model was developed to estimate the effective diffusion of CO2 in food tissues, treated as a porous medium. The porous geometry was derived from histological sections of pre-rigor salmon loin, where CO2 transport occurs through the liquid phase within both extracellular pores and muscle fibers. The model accounts for variations in food structure and composition and predicts effective diffusivity based on the more controllable diffusivity of CO2 in water, thereby reducing experimental uncertainty. Model predictions showed strong agreement with experimental data. No statistically significant temperature effect on CO2 diffusivity was observed between 1◦C and 4◦C at an average initial pressure of 160 kPa (𝑝 = 0.451). Comparative analysis with literature data acquired under comparable operating conditions further confirmed that effective diffusivity is influenced by the gas-to-product volume ratio and diffusion distance. At equal diffusion distances, higher gas-to-product volume ratios resulted in increased diffusivity due to sustained higher headspace pressures and enhanced mass transfer. Greater diffusion depths were also associated with higher effective diffusivity, potentially linked to interfacial convection effects. Overall, the proposed framework provides a robust and standardized approach for optimizing the SGS process while reducing experimental effort and facilitating its industrial implementation.

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DOI : doi.org/10.1016/j.jfoodeng.202...
NVA : hdl.handle.net/11250/5509937