Combined deterministic and stochastic approaches for modeling the evolution of food products along the cold chain. Part I: Methodology

Many deterministic models have been developed to describe heat transfer in the cold chain and to predict the thermal and microbial evolution of food products. However, different product items will have different evolutions because of the variability of logistic supply chain, equipment design and operating conditions, etc. jective of this study is to propose a general methodology to predict the evolution of food products and its variability along a cold chain. This evolution is characterized by state variables such as temperature, water content, microbial load, etc. The methodology, presented in part I, is based on deterministic models for equipment and on stochastic laws for different sources of randomness. A Monte-Carlo algorithm is proposed for solving the model equations. The approach will be applied for the three last links of the cold chain: display cabinet, shopping basket and domestic refrigerator in part II of this study.