Concept for the integration of predictive microbiology tools and models in the efforts to secure the food supply chain in case of bioterroristic attacks
Quantitative microbiological risk assessments in the farm-to-fork continuum require mathematical models for growth, survival and inactivation of microorganisms in different matrices and under various physical conditions. The internationally published quantitative microbial risk assessments (QMRA) are characterized by a great heterogeneity in all aspects related to the analysis's (aims, data, process descriptions, modeling techniques and software). Experimental data for such models are currently collected internationally (e.g. Combase project). The goal of the concept presented here is to develop a community esource for the calculation of predictive microbiological models and their model parameters (e.g. D-, Z-values, lag-times, maximum growth rates etc.). Integral part of the concept is the development of a knowledge base on food matrices, food production processes, process parameters, microbial agents and predictive models. The database structure integrates a citation management resource (e.g. for scientific literature) and an information quality scoring feature. This lays the foundation to a comprehensive documentation on model quality considering the data used for model generation and the results from sensitivity analyses of the models. Depending on the available and integrated (experimental) data the developed software and data infrastructure can become an integral part of a strategy to safeguard the food supply chain in case of bioterroristic attacks.