Predictive modelling of post-harvest quality evolution in perishables, applied to mushrooms

A large number of models on post-harvest quality evolution of perishables is available. Yet the number of applications is limited. The most common application is the comparison of shelf-life predictions for different constant temperature scenarios. Application of post-harvest quality evolution models for perishables in evaluation of cold-chains (non-constant temperatures) and in model predictive control (MPC) poses specific requirements to the models: predictive, causal, stable, irreversible models are required that are valid for non-constant temperatures. In this paper a modelling methodology is presented in which the class of permitted models is limited by the above requirements. The methodology is used to develop a post-harvest mushroom quality evolution model. The resulting model fits well to experimental data collected for mushrooms from three different growers. The model is suitable for use in MPC and the evaluation of cold-chains with any possibly occurring temperature trajectory. No such model is currently available in the literature. (C) 2003 Elsevier Science Ltd. All rights reserved.