SubjectsSubjects(version: 963)
Course, academic year 2024/2025
  
Interpretation of chromatographic and spectrometric data - M323017
Title: Interpretace chromatografických a hmotnostně-spektrometrických dat
Guaranteed by: Department of Food Analysis and Nutrition (323)
Faculty: Faculty of Food and Biochemical Technology
Actual: from 2024
Semester: winter
Points: winter s.:4
E-Credits: winter s.:4
Examination process: winter s.:
Hours per week, examination: winter s.:3/0, Ex [HT]
Capacity: unlimited / unknown (unknown)
Min. number of students: unlimited
State of the course: taught
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Level:  
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Stránská Milena prof. Ing. Ph.D.
Interchangeability : N323047
This subject contains the following additional online materials
Annotation -
The subject is focused on the analytical procedures employing chromatographic and mass spectrometric techniques for the analysis of organic compounds in complex matrices. The main discussed applications are food quality and safety, environmental and forensic analysis. The following topics are discussed: (i) connection of chromatographic and mass-spectrometric techniques; (ii) interpretation of mass spectra; (iii) software for analyte identification and data processing; (iv) targeted screening in food and analysis; (v) techniques for the quantification of analytes and their confirmation; (vi) statistical methods for the data processing and interpretation (multivariate analysis).
Last update: LACINAO (27.01.2018)
Aim of the course -

Students will be able to:

  • Choose right separation technique (GC or LC) in combination with particular type of mass analyser for different analytical tasks. They will understand the basic characteristics of different ionization techniques and mass spectrometers.
  • Analyse mass spectrum, find the molecular ion and analyse isotopic profile, calculate formula of simple moleule from an isotopic profile and calulate a number of double-bonds.
  • Qualitatively analyse LC-MS and GC-MS data, apply correct smoothing algorithms, spectral deconvolution, to use mass spectra libraries and retention indexes for the identification of analytes.
  • Quantify obtained data, confirm results, use different calibration approaches (external calibration cuve, method of standard addition, internal standards, isotopic dilution) in LC-MS and GC-MS.
  • Apply different chemometric tools for the data structure and get the maximum of information from recorded data.

Last update: LACINAO (27.01.2018)
Course completion requirements -

Student has to elaborate tasks assigned during lessons.

The subject is finished by an exam.

Last update: LACINAO (28.01.2018)
Literature -

Picó Y.: Food Toxicants Analysis, Elsevier, 2007, ISBN: 978-0-444-52843-8.

Otleş S.: Handbook of Food Analysis Instruments, CRC, 2008, ISBN: 9781420045666.

Smith R.M., Busch K.L.: Understanding Mass Spectra, Wiley, 1999 ISBN: 0-471-29704-6.

de Hoffmann E., Stroobant V.: Mass Spectrometry - Principles and Applications, Wiley, 2002 ISBN: 9780471485667.

Last update: Stránská Milena (14.09.2023)
Requirements to the exam -

Within the extent of the syllabus.

Last update: Vlčková Martina (30.01.2018)
Syllabus -

1. General requirements on quality of chromatographic and mass-spectrometric data, definition of basic concepts.

2. Connection of gas chromatography and mass spectrometry, ionization techniques, conventional detectors.

3. Connection of liquid chromatography and mass spectrometry, ionization techniques, conventional detectors.

4. Mass spectrometry (MS), different types of mass spectrometers, acquisition modes.

5. Interpretation of GC-MS spectra.

6. Interpretation of LC-MS spectra.

7. Mass spectrometry in food analysis.

8. Spectral libraries, retention indexes.

9. Spectral deconvolution, Software tools for an analyte identification/interpretation.

10. Application of targeted screening.

11. Quantification techniques.

12. Confirmation criteria in mass spectrometry.

13. Statistical methods for multivariate data analysis.

14. Software for automated data processing.

Last update: LACINAO (27.01.2018)
Learning resources -

http://www.chem.arizona.edu/massspec/

http://www.ionsource.com/tutorial/spectut/spec1.htm

http://www.chemguide.co.uk/analysis/masspecmenu.html

http://webbook.nist.gov/chemistry/

http://www.chemspider.com/

http://www.massbank.jp/

http://metlin.scripps.edu/

http://fiehnlab.ucdavis.edu/

http://ec.europa.eu/food/plant/pesticides/eu-pesticides-database/public/?event=homepage&language=EN

Last update: LACINAO (28.01.2018)
Entry requirements -

Analytical chemistry, Organic Chemistry

Last update: Pulkrabová Jana (30.01.2018)
Registration requirements -

Analytical chemistry, Organic Chemistry

Last update: Pulkrabová Jana (30.01.2018)
Teaching methods
Activity Credits Hours
Konzultace s vyučujícími 0.5 14
Účast na přednáškách 1.5 42
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi 1 28
Příprava na zkoušku a její absolvování 1 28
4 / 4 112 / 112
 
VŠCHT Praha