ADVANCED AND PREDICTIVE FOOD MICROBIOLOGY
cod. 1008425

Academic year 2021/22
2° year of course - First semester
Professor
Giulia TABANELLI
Academic discipline
Microbiologia agraria (AGR/16)
Field
Discipline delle tecnologie alimentari
Type of training activity
Characterising
48 hours
of face-to-face activities
6 credits
hub:
course unit
in ENGLISH

Learning objectives

Knowledge and understanding
The main purpose of the course is to understand and discuss the role of the presence of microorganisms in food in relation to food safety, to critically apply some analytical approaches for risk assessment in different food type, to understand the factors involved in contamination, microbial adaptation and growth in relation to food safety. Moreover, the students will acquire the bases for the application of mathematical model and statistical procedures to the forecast of microbial growth or death kinetics in foods, also in relation to the application of process treatments in food industry.
Autonomy of judgement
The student will be able to understand and critically evaluate the microbial ecology aspects, applying the acquired knowledge to different food products in relation to production process and storage conditions. Moreover, the student will be able to evaluate the role of different microbial groups in foods and to apply mathematical models of predictive microbiology to assess product microbiological safety and quality and microbial population behaviour according to factors that regulate microbial growth.
Communication skills
Through lectures and practices, the student will acquire the technical terminology concerning advanced and predictive microbiology.
Learning ability
The student will be able to apply the principles and knowledge acquired during the course in the field of food technologies, innovation and product / process design.

Prerequisites

There are no compulsory propaedeutic courses. However, it is highly recommended to attend the course of "Food Technologies and Microbiology" (first year of the course) and to have knowledge of the principles of general microbiology.

Course unit content

Contamination and microbial growth in food, microbial control factors and basics of predictive microbiology with mathematical models for microbial growth or death.

Full programme

Basic knowledge of microorganisms and their potential interactions with the food-man-environment ecosystem
Contamination and risk of microbial growth in food: main control and management systems for the microbial growth in food production processes and in finished or ready to eat products
Complex microbial ecosystem organization and their adaptation and resistance characteristics; evaluation of the microbiological food shelf life
Predictive microbiology principles:
- Definitions, aims and development of predictive microbiology
- Primary models for microbial growth curves (Gompertz equation, Baranyi model, logistic equation).
- Microbial death curves: from the linear Bigelow equation to the description of nonlinear kinetics (loglinear model, Weibull equation)
- Use of secondary models to evaluate the effect of the control factors and variables applied
- Probabilistic models, Logit equation.
- Tertiary models
Practical applications (case studies) of predictive microbiology in the research sector and in the food industry:
- Production of molecules with potential healthy or negative effects (toxins) and study of the factors that regulate their accumulation
- Factors influencing foodborne pathogens growth and survival in food
- Evaluation of the effects of antimicrobials and their influence on the growth kinetics and on death curves also in association with a thermal treatment.
- Microbial alterations of fresh or ready to eat foods and strategies for their stabilization: evaluation of shelf life.

Bibliography

Lectures notes and selected papers from various journals and conferences.

Teaching methods

The teaching will be done through classroom lectures (5 CFU) with the help of slides for theoretical background, specialistic seminars and practical training lessons (1 CFU).
Teaching tools
Slides for theoretical background; Scientific paper for insights; specific software or tertiary models for practical training lessons.

Assessment methods and criteria

The evaluation of the preparation of the student will be assessed with an oral examination. Three questions will be requested to the student. The first two will regard theorical aspects of microbial modelization and advanced microbiology while the third will be related to the application of concepts to case studies to evaluate the student's ability to transfer theoretical concepts and predictive microbiology tools to real situations and practical aspects in food industry.
A maximum of 11 scores are awarded for each of the three questions. The examination will be considered positive if at least 18 scores will be assigned to the student. Honors (laude) are awarded if the total exceeds at least 31 points.

Other information

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2030 agenda goals for sustainable development

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Contacts

Toll-free number

800 904 084

Student's office

E. segreteria.scienzealimenti@unipr.it 
 

Quality assurance service 

Course quality assurance manager:
Dott.ssa Caterina Scopelliti
T. +39 0521 905969
E. service didattica.scienzealimenti@unipr.it
E. manager caterina.scopelliti@unipr.it

Course President

Prof.ssa Tullia Tedeschi
E. tullia.tedeschi@unipr.it 

Deputy Course President

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

 

Delegate for guidance

Prof.ssa Emanuela Zanardi
E. emanula.zanardi@unipr.it 

Delegate for career guidance

Prof.ssa Francesca Bot
E. francesca.bot@unipr.it  

Delegate for tutoring

Prof.ssa Emanuela Zanardi
E. emanuela.zanardi@unipr.it 

Member of the International student mobility commission

Prof. Francesco Martelli
E. francesco.martelli@unipr.it  
 

Responsible for Course Quality Assurance (RAQ)

Prof.ssa Chiara Dall'Asta
E. chiara.dallasta@unipr.it

 

Contact person for students with disabilities, specific learning difficulties,(SpLD) or vulnerable groups

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

 

Delegates for internships

Prof.ssa Tullia Tedeschi - Unipr
E. tullia.tedeschi@unipr.it 

Prof.ssa Paola Battilani - Università Sacro Cuore PC
E. paola.battilani@unipr.it

Prof. Pietro Rocculi - Unibo
E. pietro.rocculi3@unibo.it  

Prof. Emilio Stefani - Unimore
E. emilio.stefani@unipr.it

Prof. Nicola Marchetti - Unife
E. nicola.marchetti@unipr.it