Foodomics and Plant Foods
Course content
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 learn how molecular profiles of foods are screened using analytical platforms. The course will cover analytical platforms including Gas Chromatography-Mass Spectrometry (GC-MS), Liquid Chromatography-Mass Spectrometry (LC-MS) and Proton (1H) Nuclear Magnetic Resonance (NMR) spectroscopy that are most often used to screen foods and human biofluids (blood, urine, and faecal). The course also covers design of foodomics/metabolomics experiments, from sample preparation to data acquisition and data pre-processing/analysis.
The course includes lectures, theoretical and hands-on laboratory exercises through which students will be familiarised with analytical platforms and standard operating procedures (SOPs) used for targeted and untargeted analysis of metabolites. The course also provides comprehensive teaching and practical exercises on foodomics/metabolomics data handling. This will include hands-on trainings in data pre-processing (metabolite identification and quantification) and data analysis using advanced data analysis methods.
MSc Programme in Food Science and Technology
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. Students will learn how to design, optimize, and evaluate foodomics/metabolomics protocols. Students will also learn data pre-processing methods to convert complex/raw data from analytical instruments into an annotated metabolite table. This will be achieved through hands-on training on foodomics/metabolomics data processing software. Finally, students will be familiarized with most common data analysis methods applied on foodomics/metabolomics datasets.
At the end of the course student will be able to do:
Knowledge
- Describe principles of GC-MS, LC-MS and 1H NMR, and their applications in foodomics
- Reflect on the advantages and disadvantages of GC-MS, LC-MS and 1H NMR
- Identify suitable analytical platforms and methods for detection of one or more classes of substances
- Describe foodomics data pre-processing and data analysis methods
Skills
- Ability to identify critical points when designing and executing foodomics/metabolomics studies
- Optimize biological sample processing (extraction) and analytical measurement steps
- Ability to process complex foodomics/metabolomics datasets
Competences
- Interpret, discuss and adapt foodomics/metabolomics methods from the literature
- Process GC-MS, LC-MS, and 1H NMR data
- Apply statistical analysis of foodomics/metabolomics datasets according to a pre-defined scientific question
The course will combine lectures, theoretical and laboratory exercises. Lectures will be divided into clusters including analytical platforms, design of foodomics/metabolomics experiments, applications, metabolite identification, data pre-processing and data analysis. Each lecture cluster will be followed by a theoretic exercise where students will solve given tasks in small groups. Students will be familiarized with existing analytical platforms at www.food.ku.foodomics during the laboratory exercises. During the laboratory exercises students will be divided into groups and apply analytical platforms to screen plant foods or other biological samples for small metabolites.
See Absalon for a list of course literature
Basic knowledge in chemistry, analytical chemistry and
multivariate data analysis (chemometrics) is recommended
Academic qualifications equivalent to a BSc degree is recommended.
Contact the course responsible if in doubt.
- ECTS
- 7,5 ECTS
- Type of assessment
-
Written assignmentOn-site written exam, 1 hour under invigilation
- Type of assessment details
- The students will be evaluated based on a short written
individual report (50%) and a following written exam (50%). Both
the report and the written exam must be passed in order to pass the
course.
Weight: Individual project report 50%, written exam 50%. - Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners
- Re-exam
-
Same as ordinary exam
If the written individual report is not passed, a revised version must be submitted no later than three weeks before re-exam.
Criteria for exam assessment
See Learning Outcome
Single subject courses (day)
- Category
- Hours
- Lectures
- 56
- Class Instruction
- 28
- Theory exercises
- 32
- Project work
- 81
- Guidance
- 8
- Exam
- 1
- English
- 206
Kursusinformation
- Language
- English
- Course number
- NFOK19003U
- ECTS
- 7,5 ECTS
- Programme level
- Full Degree Master
- Duration
-
1 block
- Placement
- Block 4
- Schedulegroup
-
A
- Capacity
- 30
The number of places might be reduced if you register in the late-registration period (BSc and MSc) or as a credit or single subject student. - Studyboard
- Study Board of Food, Human Nutrition and Sports
Contracting department
- Department of Food Science
Contracting faculty
- Faculty of Science
Course Coordinators
- Bekzod Khakimov (3-728a7f50767f7f743e7b853e747b)
- Søren Balling Engelsen (2-82744f757e7e733d7a843d737a)
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