Predicting bacterial growth in processed milk and dairy products

It is now recognised that physical and chemical factors such as temperature, pH, salt and lactate concentrations are prime determinants of microbial growth in foods. These interact in a complex and synergistic manner to control the growth of microorganisms and such interactions can now be rapidly computed. The main growth parameters for Listeria monocytogenes i.e. duration of the lag phase and generation times, were quantified with respect to the controlling factors and a database constructed for growth of the pathogen in a skim milk medium. Results show that the models give reasonable predictive estimates for growth of this pathogen in milk and dairy products such as processed milk, cream and soft cheese. The computed information base allows rapid assessment of the growth potential of the pathogen in a particular food environment and defines conditions under which any adventitious contaminants will not grow. This has potential for use in positive release of hygienically manufactured product into the market place, and for defining refrigeration and temperature abuse conditions which are critical in determining growth of the organism.