Abstract
Control of moisture transfer inside composite food products or between food and its environment remains today a major challenge in food preservation. A wide rage of film-forming compounds is now available and facilitates tailoring moisture barriers with optimized functional properties. Despite these huge potentials, a realistic assessment of the film or coating efficacy is still critical. Due to nonlinear water sorption isotherms, water-dependent diffusivities, and variations of physical state, modelling transport phenomena through edible barriers is complex. Water vapor permeability can hardly be considered as an inherent property of films and only gives a relative indication of the barrier efficacy. The formal or mechanistic models reported in literature that describe the influence of testing conditions on the barrier properties of edible films are reviewed and discussed. Most of these models have been validated on a narrow range of conditions. Conversely, few original predictive models based on Fick's Second Law have been developed to assess shelf-life extension of food products including barriers. These models, assuming complex and realistic hypothesis, have been validated in various model foods. The development of nondestructive methods of moisture content measurement should speed up model validation and allow a better comprehension of moisture transfer through edible films.
Notes
* GMP: Good Manufacturing Practices
#: Possible use for food contact of such waxes, lacs and coatings after specific authorization as disclosed in the Framework Regulation (EC) 1935-2004 (L338/4)
*Mannuronic/Guluronic residue ratio: 0.8;
** Acetylation Degree : 1.6%;
# SS: equilibrium over Saturated Salt solutions;
† Setaram B92 dynamic microbalane submitting sample at given temperature and increasing partial pressure of water by means of an evaporator;
‡ DVS: Dynamic Vapor sorption balance submitting sample at given temperature and increasing RH levels;
§ G = 100/n· ∑|Xe − Xp|/Xe;
§§ RSS = ∑(Xe − Xp)2;
¶ R2 = linear correlation coefficient;
¶¶ RMSE = √(Xp − Xe)2/(N − p) where Xe, Xp, N, and p are respectively, the experimental and predicted moisture content [g/100 g d.b.], the number of experimental moisture content measurements and the number of estimated model parameters.
# DS: Degree of Substitution
* CMC: Critical Moisture Content considered in the cereal-based component which corresponds to the end of shelf life.