NSCPHD1061 Aroma components in food
Volume 2013/2014
Education
PhD education
Content
The course gives an understanding of the
role of aroma components in foods, and a thorough review of
techniques for sampling and analysis of aroma compounds.
Most - but not all - of the following will be included:
Instrumental (GC, MS, GC-O, multi-dimensional GC)
Sampling of aroma (Static and dynamic headspace sampling, SPME, extraction, distillation)
Quantification a.o. (standard curves, internal standard, multiple headspace extraction, detection limits, signal/noise, retention index, retention time locking, stable isotope dilution assay...)
Identification of most important components
Flavour release
PTR-MS
Adulteration
Data treatment (multivariate techniques (PCA, PLS, PARAFAC), warping, relevant software
Theories of olfaction
Occurrence, formation pathways, sensory quality of aroma compounds
Most - but not all - of the following will be included:
Instrumental (GC, MS, GC-O, multi-dimensional GC)
Sampling of aroma (Static and dynamic headspace sampling, SPME, extraction, distillation)
Quantification a.o. (standard curves, internal standard, multiple headspace extraction, detection limits, signal/noise, retention index, retention time locking, stable isotope dilution assay...)
Identification of most important components
Flavour release
PTR-MS
Adulteration
Data treatment (multivariate techniques (PCA, PLS, PARAFAC), warping, relevant software
Theories of olfaction
Occurrence, formation pathways, sensory quality of aroma compounds
Learning Outcome
The aim of the course is to give an
understanding of the role of aroma components in foods and how they
are measured.
Literature
Selected scientific papers and chapters
from textbooks
Teaching and learning methods
Preparation, before the
course:
Read course material/compendium. Bring one sample related to you project to be analysed during the course. Prepare: presentation of your own PhD project + one given subject.
5 days in Copenhagen:
9-16: Lectures, colloquia, exercises
Some evenings: data analysis, preparation
Report writing after course
Read course material/compendium. Bring one sample related to you project to be analysed during the course. Prepare: presentation of your own PhD project + one given subject.
5 days in Copenhagen:
9-16: Lectures, colloquia, exercises
Some evenings: data analysis, preparation
Report writing after course
Workload
- Category
- Hours
- Colloquia
- 8
- Lectures
- 25
- Preparation
- 50
- Project work
- 35
- Theory exercises
- 7
- Total
- 125
Sign up
Contact course
responsible
Exam (Evaluation of written project
report)
- Credit
- 5 ECTS
- Type of assessment
- Written assignmentThe report should describe the results obtained by the analysis of the participant's own sample during the course, describe related theory, alternative sampling methods etc.
- Marking scale
- passed/not passed
- Censorship form
- No external censorship
- Exam period
- Written report should be delivered 3 weeks after the course
- Re-exam
- After agreement with course responsible.
Course information
- Language
- English
- Course code
- NSCPHD1061
- Credit
- 5 ECTS
- Level
- Ph.D.
- Duration
- One week course
- Placement
- Block 2
Five consecutive days in November or December
- Schedule
- Monday-Friday 9-16 plus a few evenings with data analysis and preparation
- Course capacity
- Max. 25
- Study board
- Natural Sciences PhD Committee
Contracting department
- Department of Food Science
Course responsibles
- Mikael Agerlin Petersen (map@food.ku.dk)
Lecturers
Mikael Agerlin Petersen
Saskia van Ruth
Saved on the
29-01-2014