Predictive food microbiology and preservation

• Describe environmental factors in food and their quantitative effect on microbial responses.
• Obtain relevant information from databases and literature on microbial responses in food.
• Characterise microbial kinetics in food by appropriate mathematical models.
• Develop a predictive microbiology model of relevant complexity for a specific food.
• Evaluate the performance of predictive microbiology models for specific microorganism/food combinations.
• Evaluate shelf-life and food losses in distribution chains by using predictive food microbiology models.
• Describe the use of predictive food microbiology models in assessment and management of microbial food safety and quality.
• Analyse and present predictive food microbiology models and data both orally and in writing as a report.

The course is based on lectures and computer exercises to explain the development, validation and application of predictive food microbiology models. The students use this information in their project work to develop and/or evaluate a predictive microbiology model for a selected microorganism/food combination. This course allow students to predict microbial responses in food including effects of processing, product characteristics and conditions of storage and distribution to consumers. Mathematical models to predict growth or inactivation and the effect of constant or dynamic product characteristics and storage conditions are presented. Predictive models for the growth boundary of human pathogens are described together with their application for development of new food products and recipes. Software for development and application of deterministic and stochastic predictive models are presented in relation to assessment and management of microbial food quality and safety. The use of predictive food microbiology models to evaluate food losses in distribution chains is introduced.

Knowledge of and interest in microbial quality and safety of food

Lectures, group work/exercises, project work

Maximum: 30.

Please be aware that this course has a limited number of seats available. If there are too many applicants, a pool will be created for the remainder of the qualified applicants, and they will be selected at random. You will be informed 8 days before the start of the course, whether you have been allocated a spot.