Virtual representation of fresh produce washing in 4.0 industry: Modelling and calibration through optimal experimental design

This work presents a mechanistic mathematical model describing the dynamics of microbial contamination in water during the washing of fresh produce. The model accounts for key processes, including microbial transfer from food product to water, dilution effects, and inactivation by chlorine-based antimicrobials under varying organic matter loads. These mechanisms reflect those previously identified and endorsed by the European Food Safety Authority (EFSA) as relevant for assessing microbial risks in wash water systems. To enable its application across diverse industrial settings, we propose a methodology for case-specific model adaptation. This involves conducting a targeted experiment designed using principles of Optimal Experimental Design (OED), allowing for the collection of data that are sufficiently informative to confidently estimate unknown model parameters. Industrial relevance: The proposed framework provides the food industry with a flexible and efficient tool for estimating unknown parameters essential for microbial risk assessment and for optimizing fresh produce washing processes. • Dynamic model to describe microbial water contamination during produce washing. • Estimation of key parameters, such as contamination rates, based on industrial data. • Guidelines for adapting the model to specific cases. • Results may be used for optimizing operational conditions in the WaterManage4You EFSA app.