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 d...
Guardado en:
| Autor principal: | |
|---|---|
| Formato: | info:eu-repo/semantics/article |
| Lenguaje: | spa |
| Publicado: |
UNIVERSIDAD ANTONIO NARIÑO
2014
|
| Materias: | |
| Acceso en línea: | https://revistas.uan.edu.co/index.php/ingeuan/article/view/351 https://repositorio.uan.edu.co/handle/123456789/10429 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: | 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. |
|---|
