Microbiological hazards associated with the use of water in the post‐harvest handling and processing operations of fresh and frozen fruits, vegetables and herbs (ffFVH). Part 2 – A dynamic mass balance model for handling and processing operations in ffFVH using water - EFSA Panel on Biological Hazards (BIOHAZ); Ana Allende; Avelino Alvarez‐Ordóñez; Valeria Bortolaia; Sara Bover‐Cid; Alessandra De Cesare; Wietske Dohmen; Laurent Guillier; Lieve Herman; Liesbeth Jacxsens; Lapo Mughini‐Gras; Maarten Nauta; et al. (EFSA Journal)
Abstract A dynamic mass balance model was developed to simulate contamination dynamics in the process water of fresh and frozen fruits, vegetables and herbs (ffFVH) during processing and handling operations. The mass balance relates to the flux of water and product in a wash tank and the number of microbial cells released in the water, inactivated by the water disinfectant or transferred from the water back to the product. Critical variables describing microbial dynamics in water are: (i) the chemical oxygen demand (COD), as an indicator of the concentration of organic matter; (ii) free chlorine (FC) and particularly its antimicrobial fraction, hypochlorous acid (HOCl); and (iii) the microbial population levels. Model parameters include: (i) the dilution rate of the process water, representing the speed of system saturation, equal to the water flux divided by the tank volume; (ii) the transfer rates of total bacterial counts (TBC) and COD from product to water; and (iii) the specific inactivation rate of microorganisms due to HOCl. The protective effect of COD on microbial cells against FC is encompassed in the inactivation rate. HOCl is expressed as a function of temperature, pH and total chlorine. The model can simulate ‘what if scenarios’, based on user‐defined process‐specific and product/microorganism‐specific parameters through a web R‐based application. This model can help food business operators when selecting intervention strategies and conditions to maintain the microbiological quality of the process water or identify conditions that represent poor or proper water management practices. Testing alternative model structures and collecting data about operational conditions of handling and/or processing operations, microbial dynamics and the magnitude of the product‐specific protective effect on microorganisms are recommended to improve the application of the model.