Jan 28, 2020   1:44 p.m. Alfonz
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Course syllabus N436P0_4I - Predictive Microbiology and Risk Assessment (FCFT - WS 2019/2020)

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University: Slovak University of Technology in Bratislava
Faculty: Faculty of Chemical and Food Technology
Course unit code: N436P0_4I
Course unit title: Predictive Microbiology and Risk Assessment
Mode of delivery, planned learning activities and teaching methods:
lecture2 hours weekly (on-site method)

Credits allocated: 2
Recommended semester/trimester: Food, Hygiene, Cosmetics - master (semi-compulsory), 3. semester
Level of study: 2.
Prerequisites for registration: none
Assesment methods:
Seminar work evaluated within the system: A (> 90%), B 89-80%), C (79-70%), at least D (69-60%), E (59-55%).
Learning outcomes of the course unit:
A graduate describe/evaluate and predict the behavior of microorganisms in foods (growth, reproduction, survival, inactivation) with respect to food intrinsic and extrinsic environmental factors. He knows the primary, secondary models and expert systems to be used for predicting microbial behavior. He can apply the knowledge in defining period for safety food storage, implementation and evaluation of storage and challenge tests (required by European legislation). A graduate knows about the ground principles of the concept of risk analysis. He is familiar to  qualitative and quantitative microbiological risk/exposure assessment using deterministic and stochastic models. He knows the latest outcomes of the European Food Safety Authority (EFSA) in the field, as well as the role of active and responsible for risk minimization in the food chain.
Course contents:
The concept and definition of the subject of predictive microbiology. Characteristic behaviors of microorganisms in the processing of raw materials, production, storage, preparation and consumption of food. Planning an experiment in predictive microbiology. Microbial growth, growth line, growth parameters - using mathematical models in describing the course of the growth lines and calculation of growth parameters. The primary models used in predictive microbiology. Secondary models used in predictive microbiology. Accessible user programs. Models 'growth/no growth". Tertiary models used in predicting the growth of microorganisms in food, scientific databases and expert systems. Survival of microorganisms - a quantitative description of the survival of microorganisms relevant parameters of survival - using mathematical models is the description of survival. Interactions of microorganisms in foods and co-cultures vs. pathogenic microbe. Lactic acid bacteria in fermented foods. Modern concepts of food safety. Sector risk assessment, purpose and meaning. Structure risk analysis. Ranking of microorganisms in terms of severity and likelihood of disease. Qualitative microbiological risk assessment. Current scientific opinion of the European Food Safety Authority (EFSA).
Recommended or required reading:
ZWIETERING, M. -- NAUTA, M. -- BASSETT, J. Tools for Microbiological Risk Assessment. Brussels: ILSI Europe, 2012. 42 p.
VALÍK, Ľ. -- MEDVEĎOVÁ, A. -- LIPTÁKOVÁ, D. -- HUDECOVÁ, A. Application of predictive microbiology and risk-based metrics in production of ewes lump cheese: A.S. aureus case. In Food Micro 2010, 22nd International ICFMH Symposium. 2010.
VALÍK, Ľ. Predictive microbiology - laboratory. In Food Safety, Quality and Nutrition, 14 August 2011 - 27 August 2011..
VALÍK, Ľ. -- MEDVEĎOVÁ, A. Exposure and risk assessment of Staphylococcus aureus in food chain in Slovakia. Potravinárstvo, 7. p. 58--62. ISSN 1337-0960.
HESTER, R. -- HARRISON, R M. Risk Assessment and Risk Management. Cambridge : Royal Society of Chemistry, 1998. 168 p. ISBN 0-85404-240-7.

Language of instruction: slovak or slovak
Courses evaluation:
Assessed students in total: 3

66,7 %33,3 %0 %0 %0 %0 %
Name of lecturer(s): doc. Ing. Pavel Ačai, PhD. (instructor, lecturer) - slovak, english
prof. Ing. Ľubomír Valík, PhD. (person responsible for course) - slovak, english
Last modification: 29. 1. 2019
Supervisor: prof. Ing. Ľubomír Valík, PhD. and programme supervisor

Last modification made by Ing. Tomáš Molnár on 01/29/2019.

Type of output: