NFOK19003U Foodomics and Plant Foods
MSc Programme in Food Innovation and Health
Foodomics & Plant Foods is a multidisciplinary course covering a broad domain of scientific methods applied to the analysis of small molecules in plant foods and other biological samples. The course introduces the basics of the foodomics, which is the research field investigating molecular composition of foods and their impact on human health and wellbeing. Students will also learn how molecular fingerprints of foods can be related to food production and detection of food fraud and adulteration. The course will cover advanced hyphenated analytical platforms, Gas Chromatography-Mass Spectrometry (GC-MS), Liquid Chromatography-Mass Spectrometry (LC-MS) and Nuclear Magnetic Resonance (NMR) Spectroscopy that are most often used in chemical fingerprinting of plant foods and other biological samples including human blood, urine, muscle and faecal. The course also provides in-depth knowledge on large-scale foodomics/metabolomics study design, data acquisition, data pre-processing and data analysis, as well as identification of molecules using spectral information.
The course includes lectures, theoretical and practical exercises through which the students will be familiarised with analytical platforms, method optimization and establishment of standard operating procedures (SOPs) for targeted and untargeted analysis of metabolites in food and other biological samples. The course will also provide comprehensive teaching and practical exercises on data handling prior to convert raw instrumental data into an informative metabolite table. This will include hands-on trainings in processing and analysis of large foodomics datasets using advanced multivariate data analysis methods. Thus, if possible, students can bring their own foodomics/metabolomics datasets to train on them during the course.
The main aim of the course is to learn the state-of-the-art methods applied in high-throughput screening of small molecules in plant foods, and other biological samples performed within foodomics studies. Students will also learn data handling approaches to translate complex foodomics datasets into chemical information and to interpret the results. This will be achieved by learning crucial steps in foodomics, including optimization of protocols, data acquisition, data processing and data analysis.
At the end of the course student will be able to do:
Potentials of high-throughput and untargeted screening of small molecules
Explain and understand existing methodologies used in foodomics studies for small molecular analysis
Identify suitable analytical platforms and methods for detection of one or more classes of substances
Reflect on the advantages and disadvantages of different analytical platforms
Describe foodomics data processing and analysis procedures
Ability to identify critical points when designing and executing foodomics studies
Optimize biological sample processing and analytical measurement steps
Ability to process foodomics datasets
Interpret and be able to discuss and adapt foodomics/metabolomics methods from the literature
Process raw GC-MS, LC-MS, and NMR data and convert into an informative metabolite table
Perform chemometrics on foodomics data according to the investigated scientific question
See Absalon for a list of course literature
Academic qualifications equivalent to a BSc degree is recommended.
Contact the course responsible if in doubt.
- Class Instruction
- Theory exercises
- Project work
- 7,5 ECTS
- Type of assessment
- Oral examination, 20Written assignmentThe students will be evaluated based on a written report (50%) in groups of 3-4 students and a following final individual oral examination based on a presentation and discussion of the report and the course curriculum (50%). Both the report and the oral examination must be passed in order to pass the course.
Weight: Project report 50%, Oral examination 50%.
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners
Same as ordinary exam
If the written group report is not passed, a revised version must be submitted no later than three weeks before re-exam. Potentially the report is handed in individually.
Criteria for exam assesment
See Learning Outcome