From the results it could be concluded that in some batches considerable intrabatch variability was obtained. In general, however, the interbatch variability was significantly higher than intrabatch variability. Concerning the two above mentioned methods for challenge tests, it can be stated that the first approach (simple challenge test) can be set up rather rapidly and is cost-effective for SMEs (small and medium enterprises) but provides only a single isolated outcome. This implies that challenge tests should be redone if changes occur in composition or production process. The second (modelling) approach, using extended challenge tests to establish growth parameters needs larger set ups and more complicated data analysis, which makes them more expensive. Using available tertiary models has the major advantage that the most important intrinsic and extrinsic factors can be included for the prediction of the growth parameter. It was clear that product specific models, taking into account the interaction effects with background flora, performed the best. Regarding the challenge tests, it can be concluded that the best approach to choose will depend on the particular context as in the end both approaches will lead to the same conclusion.