In this paper, a data-based mechanistic modelling approach was developed to real time monitoring and online adaptive control of three-dimensional temperature distribution in both an individual biological product and in a given movement. Boxes of potatoes were used as biological material. During the experiments, step inputs on an air inlet temperature were applied while airspace and potatoes temperature were recorded. The simplified refined instrument variable algorithm was used as a model parameter identification tool to obtain the best model order and parameters. By model compacting, several physically meaningful parameters were found to present the temperature distribution between the products and the airspace. A third order transfer function from the dynamic response of airspace from inlet air temperature with a high coefficient of determination (R-T(2) > 0.9) and a low standard error (SE < 0.01) explained the heat exchange in a system. Two physically meaningful parameters were found from the model parameters. A local volumetric fresh air concentration beta(1) was defined to the temperature distribution in the airspace, and a local 'cooling rate' alpha(2) was presented for the product temperature distribution. The values of beta(1) and alpha(2) existing in the model could be used to design a control system for real time monitoring and online adaptive control of three-dimensional temperature distribution in the process room. (C) 2007 Elsevier Ltd. All rights reserved.