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.

Les publikasjonen her:

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