FQD-37403 Predicting Food Quality - Solving food science problems by modelling (online)

Course

Credits 3.00

Language of instruction:

English.

Assumed knowledge on:

Basic knowledge in Statistics and Mathematics at BSc level.

Contents:

The focus of this course lies on analysis, evaluation and solution of problems related to food quality by mathematical modelling existing food science problems from scientific literature. Knowledge from the various food science disciplines need to be integrated to use quantitative modelling tools to predict quality attributes of foods as well as the uncertainties therein.

Learning outcomes:

After successful completion of this course students are expected to be able to:
- explain and infer the nature of food quality attributes in relation to food quality;
- classify and infer food quality attribute changes from thermodynamic and kinetic principles;
- calculate uncertainties in parameters and predictions in case of kinetic models;
- practice with the nature and properties of mathematical equations relevant for food quality;
- deduce models, parameters and model predictions and their uncertainties;
- assess competing models on their ability to predict;
- Appraise models on food quality that are applied in food science literature.

Activities:

- knowledge clips, tutorials and feedback clips;
- guided practical training on applying models using excel;
- case studies to apply modelling for food science problems from literature.

Examination:

There will be a remote proctored written exam with open and closed questions. This counts for 75% in the final result. The case studies 1 and 2 are to practice (0%), while case 3 counts for 25% in the final result.

Literature:

Information will be made available via Blackboard. A textbook is available for additional background reading, but it is not necessary to buy the textbook (M.A.J.S. van Boekel, Kinetic modelling of reactions in foods. CRC/Taylor & Francis, Boca Raton, 2008.