|Teaching method||Contact hours|
|Course coordinator(s)||dr. ir. JK Heising|
|Lecturer(s)||dr. ir. M Dekker|
|dr. ir. JK Heising|
|Examiner(s)||dr. ir. M Dekker|
Language of instruction:
The aim of this course is to provide quantitative modelling tools to predict quality attributes of foods as well as the uncertainties therein. Such a tool is necessary for modern product and process design in the food industry to be able to respond quickly to changing demands in the market. The course integrates knowledge from the various food science disciplines to make quantitative predictions for quality attributes of foods. The basic theoretical principles and tools are taught and practiced in this course.
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;
- assess competing models on their ability to predict.
- knowledge clips, tutorials and feedback clips;
- guided practical training on modelling using excel.
The final grade is based on a remote proctored written exam with open and closed questions. A pass for the computer exercises is required.
Information will be made available in Brightspace. 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).
|Restricted Optional for:||MFT||Food Technology||MSc||K: Food Technology (Distance Learning)||2DL|