Predictive microbiology: a rising science
Keywords:
Food microbiology, predicitve models, rising factors, APPCC, food security, risk analysis, PCCAbstract
In recent years, researchers on food microbiology started to use mathematical and statistical tools more frequently. These tools are important to obtain a mathematical model able to describe the evolution of microorganisms in food. Researchers have applied the models to food industries in order to determine a priori the process conditions that lead to the activation and deactivation of microorganisms. It is worth noting that microorganisms can be harmful both to consumers as well as the food´s nutritional properties. Therefore, determining the susceptible conditions is important to prevent the consequences. The mathematical models frequently used include polynomials, logarithmic, exponential and differential equations. I distinguish three classes: primary models, secondary and tertiary. These models are important for reaching robust and reliable predictions regarding the behavior of microorganisms in food. This article presents a revision of microbiological predictive models, applied to the food field. The models presented often use the most studied parameters in predictive microbiology: temperature and pH.
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