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Methodology of Research in Food Science

Course developer

Replaced course

PārZM002 [GPARM002] Methodology of Research in Food Science

Course abstract

The aim of the study course is to acquire the theoretical and practical knowledge necessary for the implementation of studies and obtaining a scientific degree.
In the study course, master students acquire the basic principles of scientific work development, basics of research modeling and organization, principles of work scheme development, mathematical data processing, correct reading, display and interpretation of data, scientific work design and presentation. Get acquainted with the conditions for the development of the master's thesis, the basic principles of statistical data analysis and various data processing methods, ways of presenting the results of research work, formation of discussion, and interpretation of the results. Acquires analysis of scientific literature and its application in the development of scientific work, as well as the application of optimization methods and various presentation tools.

Learning outcomes and their assessment

After mastering the study course students get:
 acquires the theoretical and practical knowledge necessary for the realization of studies and obtaining a scientific degree by listening to lectures of the study course and successfully completing the tasks of practical works;
 the acquired skills allow to evaluate and select the most suitable sources of information, analysis and data processing methods, and presentation tools for scientific research;
 in the final test the student demonstrates understanding and competence of the generally accepted standards for the preparation of scientific papers, the procedure for organizing experiments to obtain correct data, demonstrates the importance of choosing a reasonable data processing method to obtain correct results, apply the most appropriate types of mathematical and graphical data processing methods, demonstrate the ability to properly interpret the obtained results;
 competences to develop independent work, where the ability to evaluate scientific literature and apply scientific literature sources in the development of individual work is demonstrated; is well versed in the research resources available at the university and apply them in the study process; evaluate the suitability of data processing methods for the specific research and perform their application; demonstrates the ability to create and organize large-format documents and various types of presentations using different application software in accordance with the requirements, this is reflected in the independent work.

Course Content(Calendar)

1. Structure of the study course, competencies that can be acquired in this course. (L-2h, PW-1h)
2. Actuality, title, hypothesis, aim and tasks of scientific work. Structuring of scientific work and research included in it. (L-1h, P-2h)
3. Selection, analysis and application of scientific literature. Basic of the development of the scientific work section "Problem description". (L-1h, P-2h)
4. Basic principles of scientific work section "Materials and methods" development. Basic principles of scientific work section "Results and discussion". (L-1h, P-2h)
5. Formatting of scientific work (styles, automatic table of contents, automatic table of figures, automatic table of tables, etc.). (L-1h, P-2h)
6. Formatting of scientific work (list of used literature sources, their types, creation of references, etc.). (L-1h, P-2h)
7. Statistics in food science. Methods and basic principles of statistical analysis. (L-1h, P-2h)
8. Specifics of food analysis. Types of scales for measurement. The concept of the result and its error (gross errors, systematic errors, etc.). (L-1h, P-2h)
9. Data organization, data matrix creation, data display possibilities. Summary and interpretation of results, discussion and conclusions (L-1h, P-2h)
10. Data processing and display options (functions, diagrams, cross-section tables, etc.). (P-3h)
11. Optimization methods and their application in the food industry. Solver data modeling tool for the food industry. (L-1h, P-2h)
12. Research presentation and speech skills. (P-3h)
13. Basic principles and conditions of presentation preparation. (L-1h, P-2h)
14. Creating presentations with various programs (MS PowerPoint, Prezi, etc. online presentation creation tools). (P-3h)
15. Final test. Presentation and defence of independent work. (P-3h)

16. Defence of independent work. Summary and evaluation of results. (P-3h)

Requirements for awarding credit points

The 12 practical works provided in the study course must be complete. Independent work (1) must be developed (it must be created in accordance with the requirements, submitted electronically and defended). A successful assessment (minimum 4 out of 10) must be obtain for the independent work and the final test. The study course ends with an assessment - a test with a mark. The final test mark obtains by calculation of the arithmetic mean from the independent work (all four parts, in total 4 marks) and the test (one mark). The final mark can be positively influence by the observance of the deadline for submission of independent work. The study course can be acquire in Latvian and English.

Description of the organization and tasks of students’ independent work

The organization of independent work consists of the following activities:
•preparation for lectures - 3h;
•preparation for practical work (search for information in databases of scientific articles, application websites and other online databases related to the topic) - 16h;
•preparation for tests - 2h;
•development of independent final work - 51h.
One independent final work consisting of four parts must be developed: 1st part - report on the analysis of scientific articles (> = 8 pages); 2nd part - presentation on the analysis of scientific articles using MS PowerPoint (~ 10 slides); 3rd part - report on online presentation tool (> = 4 pages); 4th part - presentation using the online presentation tool described in the report. The independent final work must be done during the semester and submitted at the end of the semester at the times indicated by the lecturer of the study course. Each part of the independent final work receives evaluation with a mark.

At the end of the study course students write one final test on all theoretical and practical topics acquired in the study course.

Criteria for Evaluating Learning Outcomes

In this study course must have successfully written the final test and successfully completed the independent final work (assessment must be at least 4 points out of 10).
An unsuccessfully written final test must be rewritten until a successful grade is obtained (minimum 4 out of 10).

The final grade in this study course will be obtain from all marks (one test mark and four marks for independent final work) by calculating the arithmetic mean.

Compulsory reading

1. Bui Y. N., How to write a master's thesis. Los Angeles : SAGE, 2014, 313 p.
2. Corti L., Van den Eynden V., Libby Bishop & Matthew Woollard, Managing and sharing research data: a guide to good practice., Los Angeles : SAGE, 2014, 222 p.
3. Matthews M., Carole Matthews C., How to Do Everything: Microsoft Office Online. McGraw-Hill Education; 1 edition, 2015., 244 p.
4. Bower J. A., Statistical Methods for Food Science: introductory procedures for food practitioner. Oxford, UK ; Ames, Iowa : Wiley-Blackwell, 2009., 307 p.
5. Pripp A. H., Statistics in food science and nutrition. New York : Springer, 2013., 66 p.

6. Marti K., Stochastic optimization methods: Applications in engineering and operations research. Heidelberg : Springer, 2015., 368 p.

Further reading

1. Trochim W. M., Donnelly J. P., Arora K., Research methods : the essential knowledge base. Boston, MA : Cengage Learning, 2016., 422 p.
2. Lindemann K., Composing research, communicating results : writing the communication research paper. Hoboken, NJ : Wiley Blackwell, 2018., 166 p.
3. Fisher C., Researching & Writing a Dissertation: An Essential Guide for Business Students. Financial Times Prentice Hall; 3rd ed., 2010. 448 p.
4. Bluttman K. ,Excel formulas & functions for dummies. Indianapolis, IN: John Wiley & Sons, 2019., 383 p.
5. Ciproviča I., Galoburda R., Kārkliņa D., Rakčejeva T., Metodiskie noteikumi maģistra darba izstrādei un aizstāvēšanai. Jelgava: PTF, 2012. 44 lpp.
6. Arhipova, I., Bāliņa, S., Statistika ekonomikā. Risinājumi ar SSPS un Microsoft Excel: mācību līdzeklis. Rīga: Datorzinību centrs. 2003, 352 lpp.
7. Klieders J., Datorzinības. Microsoft Office 2013/2016: mācību līdzeklis., Rīga: Juridiskā koledža, 2018., 295 lpp.

8. Microsoft Office [tiešaiste] [Skatīts: 01.10.2020.]. Pieejams: https://www.office.com/

Periodicals and other sources

Scientific peer-reviewed articles on ScienceDirect. Pieejams: https://www.sciencedirect.com/ [skatīts: 01.novembris 2020.]
Scientific peer-reviewed articles on Scopus. Pieejams: https://www.scopus.com/home.uri [skatīts: 01.novembris 2020.]

Notes

The course is included in the compulsory part of the academic master’s study program “Food Science”.