PREDICTIVE MICROBIOLOGY
cod. 1008524

Academic year 2022/23
1° year of course - Second semester
Professor
- Valentina BERNINI
Academic discipline
Microbiologia agraria (AGR/16)
Field
Discipline delle tecnologie alimentari
Type of training activity
Characterising
122 hours
of face-to-face activities
6 credits
hub:
course unit
in ITALIAN

Learning objectives

Knowledge and understanding
At the end of the course the student is expected to be able to:
-to know the role of microorganisms in food processing and storage
-to know the role of environmental and process parameters in the development and inactivation of microorganisms
-to know predictive models for the study of the behaviour of microorganisms in food
-to know the potential of predictive tools, experimental designs and challenge tests for the formulation of new products and food processing processes, shelf life prediction, safety assessment, risk analysis and HACCP.
-know the principles underlying the microbiological risk analysis process.
Ability to apply knowledge and understanding
At the end of the course the student is expected to be able to:
-apply predictive models for assessing the behaviour of microorganisms
-choose the most appropriate predictive approach for the analysis of microbial behaviour
-Interpreting data from predictive analyses to assess the impact of the presence and development of microorganisms and/or their metabolites on food quality and safety
-develop simple experimental designs and plan challenge tests to assess the behaviour of microorganisms and/or the production of specific metabolites.

Prerequisites

Basic knowledges of general microbiology and food microbiology, mathematics and statistics.

Course unit content

The first part of the course concerns about the general concepts of predictive microbiology, the applications in food microbilogy area, models characteristics. in the second part knowledges about primary and secondary models are exhamined. In particolar, about primary models are descrive the kinetics of growth and inactivations, Gompertz equativo, baranyi model, Weibull model. In secondary models, ratkowsky model, experimetal design, polinomial equations. The microbiologicla risk analysis step are also addressed. In the last part of the course product and process challenge test are studied, towards practical examples. Moreover, the students will examine cases of applicative researches in predictive microbiology and challenge test field. Laboratory is proposed (2 CFU for 3 groups for a total of 90 hours) concerning the design and execution of microbiological challenge tests.

Full programme

Concepts of microbiology: the structure of microbial cell; microbial growth, microbial metabolism.
The origins of predictive microbiology, the first models and application fields.
Definitions of primary, secondary and tertiary models. Probabilistic, cinetic, empirical and mechanistic models. Structural and non structural models.
Primary models. Growth modelling (Gompertz equativo, Baranyi model). Survival models (linear, biphasic, Weibull model).
Secondary models. Ratkowsky model. Experimental design. Polynomial equations.
Tertiary model. Use of Combase.
Challenge test: applications to foods and processes.

Bibliography

Fausto Gardini, Eugenio Parente. Manuale di microbiologia predittiva. Concetti e strumenti per l'ecologia microbica quantitativa (suggested/optional). Springer Italia
Educational material used during frontal lessons (necessary) represented by slides. The slides will be available on the course’s Elly page in pdf format for students. The slides will be uploaded to Elly before each topic.

Teaching methods

Lessons will be organized face-to-face. In case of specific indications, supplementary material, i.e. recorded lesson, will be made available on the Elly page of the course. The teaching will be carried out through lectures (4 CFU 28 hours. During the lessons, the appropriate use of technical language will be reiterated, and the links between the various parts of the course will be emphasized.
The course includes laboratory practices (2 CFU, 30 hours for 3 groups for a total of 90 hours) concerning challenge test and detection of microorganisms in food. The teaching materials made available to students will also include those relating to the methods used. Attendance at laboratory lessons is mandatory and the student will be admitted to take the exam if he/she has attended 80% of the scheduled exercises.

Assessment methods and criteria

During the course, some lessons will be dedicated to the evaluation of the state of learning. At the end of the course will take written exam consisting of part A (10 closed questions) and part B (10 open questions). The questions will also include the topics covered during the laboratory exercises. You will be assigned 1 point for each correct answer related to Part A and up to 2 points for each answer related to Part B. The time available will be 75 minutes. The test will be passed with the achievement of a score of 18.
The student will have to demonstrate, with the scientific language and the specific lexicon of predictive microbiology, the acquired concepts. The assessment of the level of knowledge acquired takes into account the ability of the student to express himself correctly, with the specific scientific language of predictive microbiology.
The assessment of the level of knowledge acquired takes into account the ability of the student to express correctly, with the specific scientific language of food microbiology.
In case of impossibility to carry out the written examination in presence due to force majeure imposed by the University, the examination will be carried out at a distance
by means of a written test on Elly platform and connection via Teams. The test will consist of 33 closed-ended questions to be carried out in 30 minutes. A point will be assigned to each correct answer. The exam will be passed to reach 18 points.

Other information

In the event of a serious health emergency, the methods of teaching and verifying learning may be subject to changes which will be promptly communicated on Elly and / or on the course website.