Microbiologia preditiva

Abstract

Predictive microbiology describes, quantitatively, the effects of intrinsic factors (water activity, redox potential, pH) and extrinsic factors (temperature, relative humidity, atmosphere) on the growth or inactivation of microorganisms in food. Therefore, mathematical models are constructed derivated from quantitative studies under given experimental conditions, generating growth curves / microbial inactivation. These mathematical models are capable of predicting the influence of each factor on the growth of micro-organisms. By varying conditions as pH, salt content in food, or time and temperature of storage of the same, its possible to determine if there will be increased contamination under the conditions tested at a level that may threaten the health of the population. The advantages of predictive models in food microbiology are numerous and include: describing the behavior of microorganisms in different physico-chemical conditions, allowing the prediction of the consequences in microbiological food storage, hygiene evaluate the efficiency of the processing and distribution, to determine the effect failures of the storage conditions, predict the microbiological safety of a product, predicting shelf life, assist in hazard analysis and critical control points in the development of new products, assist in decision-making and risk analysis. Such models are developed and applied to a wide range of foods, thereby reducing the amount of microbiological tests required for the development of new products, and perform fast predictions of safety and validity commercial, featuring long-term economic benefits. For this reason, predictive microbiology has been studied and used in order to promote and ensure the microbiological safety of foods.