Food Microbiology
| Title | Μικροβιολογία Τροφίμων / Food Microbiology |
| Code | ΕΤΔ101 |
| Faculty | Agriculture, Forestry and Natural Environment |
| School | Agriculture |
| Cycle / Level | 2nd / Postgraduate, 3rd / Doctorate |
| Teaching Period | Winter |
| Coordinator | Agapi Doulgeraki |
| Common | Yes |
| Status | Active |
| Course ID | 600017068 |
Programme of Study: FOOD SCIENCE AND NUTRITION
Registered students: 15
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| KORMOS | Compulsory Course | 1 | 1 | 10 |
| Academic Year | 2023 – 2024 |
| Class Period | Winter |
| Faculty Instructors |
|
| Weekly Hours | 4 |
| Class ID | 600243820
|
Course Type 2021
General Foundation
Course Type 2011-2015
General Foundation
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600243820
- Other: https://foodsn.agro.auth.gr/
Language of Instruction
- Greek (Instruction, Examination)
Learning Outcomes
At the end of this course, the student will be able to:
i. understand the principles of predictive microbiology and risk assessment
ii. to develop predictive microbiology tools based on experimental data
iii. to work with the available predictive microbiology software
iv. to use predictive microbiology tools for solving problems in the food industry including shelf life assessment, new product development, compliance to regulation etc
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Adapt to new situations
- Make decisions
- Work autonomously
- Work in teams
- Work in an international context
- Work in an interdisciplinary team
- Generate new research ideas
Course Content (Syllabus)
The course includes lectures and hands-on computer training to explain the principles of predictive food microbiology and microbial risk assessment (MRA). In the first part of the course the students are trained to develop predictive models for spoilage and pathogenic microorganisms as well as to use the available predictive modeling software. They further apply the models in their project work for new product development, self life assessment, compliance to microbiological criteria and establishment of critical limits in HACCP system based on both deterministic and stochastic approaches. The second part of the course provides a multi-disciplinary approach to microbiological risk assessment covering hazard characterization risk characterization, exposure assessment and risk characterization. The aim is to introduce the students to the concept of risk analysis as applied in national and international food safety and enable them to understand the use of risk assessment in food safety and quality management.
Keywords
Quantitative/Predictive Microbiology, Microbial Risk Assessment
Educational Material Types
- Notes
- Slide presentations
- Hands-on training on Predictive Microbiology Software
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
Description
-power point presentation during courses
-access to teaching material through elearning
-communication with students through email and elearning platform
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | |||||
| Laboratory Work | |||||
| Reading Assigment | |||||
| Exams | |||||
| Total |
Student Assessment
Description
All assignments and exams will be expected to be of professional quality and hand delivered in class. No late work will be accepted without prior approval from the instructor. The grade for the course will be determined as follows.
Grading:
Homework assignment 30%
Final Exams 70%
Total 100%
Student Assessment methods
- Written Exam with Problem Solving (Formative, Summative)
- Report (Formative, Summative)
Bibliography
Additional bibliography for study
Koutsoumanis, K.P. and Aspridou, Z. 2016. Moving towards a risk-based food safety management. Current Opinion in Food Science, 12:36–41
Koutsoumanis, K.P., Lianou, A. and Gougouli, M. 2016. Last developments in foodborne pathogens modeling. Current Opinion in Food Science, 8: 89–98.
https://www.combase.cc/index.php/en/
http://fssp.food.dtu.dk/
https://www.ars.usda.gov/northeast-area/wyndmoor-pa/eastern-regional-research-center/residue-chemistry-and-predictive-microbiology-research/docs/pathogen-modeling-program/pathogen-modeling-program-models/
Last Update
17-11-2023
