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 and used to detect 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 to screen foods and other biological mixture samples (e.g.  blood, urine, and faecal). The course also covers design of foodomics/metabolomics experiments, data acquisition, data pre-processing and data analysis.

The course includes lectures, theoretical and hands-on laboratory exercises through which students will be familiarised with analytical platforms, method optimization and establishment of standard operating procedures (SOPs) for targeted and untargeted analysis of metabolites. The course will 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-metabolomics datasets using advanced multivariate data analysis methods.

Education

MSc Programme in Food Science and Technology

MSc Programme in Food Innovation and Health

Learning outcome

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 and data handling methods to translate complex/raw data from analytical instruments into an annotated metabolite table. This will be achieved though hands-on training using foodomics datasets generated by students during the course.

 

At the end of the course student will be able to do:

 

Knowledge

Describe principles and applications of GC-MS, LC-MS and NMR

Explain and discuss existing methodologies (targeted versus untargeted) used in foodomics

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

 

Skills

Ability to identify critical points when designing and executing foodomics studies

Optimize biological sample processing (extraction) and analytical measurement steps

Ability to process complex foodomics datasets

 

Competences

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

Statistical analysis of foodomics/metabolomics datasets according to a scientific question

The course will combine lectures, theoretical exercises and laboratory work. Lectures will be divided in four clusters, analytical platforms in foodomics, design of experiment in small molecular analysis, assignment of metabolites and foodomics data pre-processing and data analysis. Each lecture cluster will be followed by a theoretic exercise where students will be divided in small groups to solve given tasks. Students will be familiarized with existing analytical platforms at KU.FOOD.FOODOMICS laboratory and will be divided into groups to perform metabolite analysis using one of the three analytical platform. During the period of two weeks, students will carry out hands-on data processing and analysis using the datasets they generate during the laboratory work.

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.

Written
Oral
Collective
ECTS
7,5 ECTS
Type of assessment
Oral examination, 20
Written assignment
Type of assessment details
The 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%.
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners
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 seats may be reduced in the late registration period
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)
Teacher

Bekzod Khakimov
Violetta Aru
Søren Balling Engelsen

Saved on the 28-02-2022

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