PREDICTIVE MICROBIOLOGY
cod. 1001778

Academic year 2017/18
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
50 hours
of face-to-face activities
6 credits
hub: -
course unit
in ITALIAN

Integrated course unit module: INDUSTRIAL AND PREDICTIVE MICROBIOLOGY

Learning objectives

Aim of the course i sto reach knowledge about the main instruments of predictive microbiology. The student ha sto demonstrate a critical analysis of the potential of predictive microbiology , of application fields (new products, shelf life, HACCP, risk analysis). Moreover, it ha sto be able to explain, elaborate and discuss problems associated to food microbiology.
The final goal of this course is to provide the students intellectual tools in order to judge and comprehend the main topics of food predictive microbiology according to the main goals of the Corso di laurea magistrale in Food Science and to microbiological area teaching field

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.

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. Springer Italia
Educational material used during frontal lessons.

Teaching methods

The theoretical topics of the course are explained by means of lectures.
Basis and applications of Predictive microbiology will be dicussed during lessons. The study, elaboration and discussion of specific "study cases (exercises and business cases)" are proposed on the practical parts of the course and could permit to verify the student comprehension and elaboration capacity

Assessment methods and criteria

Specific lessons aimed to assess the state of learning will be carried out at the end of each part of the course. During the course, some lessons will be devoted to student presentation and discussion of "study cases (business cases are discussed as examples of the main theoretical arguments of the course)" useful to understand and verify the state of comprehension and the elaboration capacity reached concerning predictive microbiology application fields.
Final examination will be carried out by a written test, either in form of multiple choices or open questions. The final evaluation will depend on the percentage of correct answers.
"Predictive microbiology" course is a part of "Predictive microbiology and industrial microbiology" course. For the final evaluation both industrial microbiology and predictive microbiology test will have to be overcome with at least 18/30 and predictive microbiology evaluation will contribute to 50% of the final evaluation.

Other information

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2030 agenda goals for sustainable development

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Contacts

Toll-free number

800 904 084

Student registry office

segreteria.scienzealimenti@unipr.it
 

Quality assurance office

Education manager
Rag. Andrea Barchi
T. +39 0521 906430
E. servizio didattica.scienzealimenti@unipr.it
 

President of the degree course

Prof.ssa Claudia Folli

claudia.folli@unipr.it

 

Faculty advisor

Prof.ssa Marilena Musci
E. marilena.musci@unipr.it

 

Tutor professor

Prof.ssa Valentina Bernini
E. valentina.bernini@unipr.it

Erasmus delegate

Prof.ssa Barbara Prandi
barbara.prandi@unipr.it 

 

 

Career guidance delegates

prof. Francesca Bot
E. francesca.bot@unipr.it 

 

Internships

prof. Pedro Miguel Mena Parreno
E. pedromiguel.menaparreno@unipr.it