Predictive microbiology: a rising science
Share
Date
Authors
Director(s)
Publisher
UNIVERSIDAD ANTONIO NARIÑO
Campus
Faculty
Program
Degree obtained
Document type
COAR type
http://purl.org/coar/resource_type/c_6501
Citation
Bibliographic Managers
item.page.resume
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.