Predictive Modelling of Antimicrobial Effects of Natural Aromatic Compounds in Model and Food Systems

The need to predict microbial behaviour has become pressing as the preservation techniques have become milder or shift ed to more ‘natural’ compounds. The past decade has been characterized by an increasing consumer demand for more natural-tasting food products, which means additive-free, fresher and minimally treated protocols but with a maintained microbiological safety (Gould, 1996). This trend has forced the search for new preservative techniques or for the combination of preservatives in the philosophy of the ‘Hurdle Technology’ concept in food safety proposed by Leistner (1995). The use of natural antimicrobial compounds and EOs, as preservation compounds, is thus of utmost interest in the food industry. An efficient exploitation of such compounds at the industrial level is still under study. To speed up this process, as well as to help in the scaling up of the usage of EOs in food, the predictive modelling approach can be seen as a useful tool. However, at present, few predictive models of EO-induced microbial inactivation can be found. Similarly, few works aiming to study the inhibitory eff ect of EOs or their constituents, in combination with other barrier factors such as temperature and pH, on microorganisms can be found.