Incorporation of data variability into process design.Pressure and/or temperature food pasteurization processes are traditionally designed with the mean values of critical parameters. However, data variability is often overlooked and processing conditions are arbitrarily adjusted, which results can result in over- or sub- processing. The Monte Carlo method permits to analyze the effect of data variability and therefore realize crucial decisions for food process design.

Application of the Monte Carlo Method in Microsoft Excel. There is a generalized impression that statistical software is required to perform risk analysis of foods. The current study was capable of performing a Monte Carlo simulation in Microsoft Excel with the pseudo-random number generator and literature reported kinetic data.

Proposal of Enzyme Risk Assessments. Food process calculations are frequently oriented towards microbial inactivation, but other intrinsic factors such as enzyme activity or sensorial characteristics can be more appropriate as critical design parameters, as in the case of orange juice PME.