Predictive microbiology: a rising science

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.

• Tipo de recurso: Article of journal
• Fecha de publicación: 2014
• Institución: Universidad Antonio Nariño
• Repositorio: Repositorio UAN
• Idioma: spa
• OAI Identifier: oai:repositorio.uan.edu.co:123456789/10429
• Acceso en línea: https://revistas.uan.edu.co/index.php/ingeuan/article/view/351; https://repositorio.uan.edu.co/handle/123456789/10429
• Palabra clave: Microbiología de alimentos; modelos predictivos; factores de crecimiento; algoritmos matemáticos; superficies de respuesta; APPCC; seguridad alimentaria; análisis de riesgos; PCC; Food microbiology; predicitve models; rising factors; APPCC; food security; risk analysis; PCC
• License: https://creativecommons.org/licenses/by-nc-sa/4.0