Sorption of flavor compounds to inner layer of polymer packages and subsequent diffusion results in loss of food flavor and consequently decreases shelf life and consumer acceptance of food stuffs which in turn causes major economic losses, so it is of utmost importance to research on diffusivity of these compounds in polymers to minimize negative effects of this phenomenon. In current research work, artificial neural networks have been applied to model polymer diffusivity to aroma molecules. The model considers all the factors that play a major role in diffusion including environmental factors, aroma molecule structure and polymer structure and is able to provide diffusion coefficient.This model could be used to predict diffusion coefficient of aroma compounds in high density polyethylene packages. Soft drinks extracts, essential oils, fruit concentrates and many other concentrated products are distributed in high density polyethylene packages. The model is able to calculate shelf life and optimum storage conditions of these products. Meanwhile it eliminates high costs involved in measuring diffusion coefficients of aroma compounds. This model at the range of aroma compounds used in this study functions excellent which is the characteristic of modeling using artificial neural networks.

Keywords: Aroma compounds, Artificial Neural Networks, Diffusion Coefficient, Modeling, Permeability, Plastic Packaging