Information and Electronic Technologies for Animal Production
A.Y. 2024/2025
Learning objectives
The aim of the "Information and electronic technologies for animal production" is to provide students with: knowledge of the main sensor systems and technological solutions of precision livestock farming (PLF) that can potentially be implemented in a livestock farm; methods and skills for analysing and interpreting data generated by sensor systems in order to optimise the herd management in a PLF perspective.
Expected learning outcomes
1. Knowledge and understanding: by the end of the course, the student should know the main PLF technological solutions that can potentially be implemented in an agro-zootechnical farm.
2. Applying knowledge and understanding: the student will have to demonstrate that he/she possesses knowledge and skills useful for processing and analysing data generated by sensor systems that can potentially be implemented in an agro-livestock farm in order to optimise livestock management a PLF perspective.
3. Making judgments: the student must demonstrate the ability of critically presenting the information acquired. Specific exercises will be addressed for sensor data management and analysis using specific software.
4. Communication: the student is expected to use scientifically appropriate language, in particular terminology referring to information and electronic technologies for animal production. The exercises are intended to stimulate the ability to use specific terminology and the ability to discuss scientifically with peers.
5. Lifelong learning skills: the student must gain the ability to use acquired knowledge to interpret new scenarios arising from the application of information and electronic technologies in animal production.
2. Applying knowledge and understanding: the student will have to demonstrate that he/she possesses knowledge and skills useful for processing and analysing data generated by sensor systems that can potentially be implemented in an agro-livestock farm in order to optimise livestock management a PLF perspective.
3. Making judgments: the student must demonstrate the ability of critically presenting the information acquired. Specific exercises will be addressed for sensor data management and analysis using specific software.
4. Communication: the student is expected to use scientifically appropriate language, in particular terminology referring to information and electronic technologies for animal production. The exercises are intended to stimulate the ability to use specific terminology and the ability to discuss scientifically with peers.
5. Lifelong learning skills: the student must gain the ability to use acquired knowledge to interpret new scenarios arising from the application of information and electronic technologies in animal production.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Responsible
Lesson period
First semester
Course syllabus
The course is divided into 40 hours of lectures and 48 hours of exercises.
Lectures:
Digital technologies and automation in livestock production (4 hours).
Precision livestock farming and areas concerned (animal welfare and health, management of reproduction, nutrition, milking) (4 hours).
Most commonly used non-invasive sensors for monitoring livestock animals (thermometers, accelerometers, radio-frequency identification - RFID tags, microphones, cameras) (12 hours).
Commercially available precision livestock technologies for cattle, pig and poultry (12 hours).
Analysis of some herd management software for dairy cows (8 hours).
Practical exercise:
Data analysis using electronic spreadsheet, statistical software, herd management software (36 hours).
Case study analysis (12 hours).
Lectures:
Digital technologies and automation in livestock production (4 hours).
Precision livestock farming and areas concerned (animal welfare and health, management of reproduction, nutrition, milking) (4 hours).
Most commonly used non-invasive sensors for monitoring livestock animals (thermometers, accelerometers, radio-frequency identification - RFID tags, microphones, cameras) (12 hours).
Commercially available precision livestock technologies for cattle, pig and poultry (12 hours).
Analysis of some herd management software for dairy cows (8 hours).
Practical exercise:
Data analysis using electronic spreadsheet, statistical software, herd management software (36 hours).
Case study analysis (12 hours).
Prerequisites for admission
There are no prerequisites for admission
Teaching methods
Lectures and practical exercises with electronic spreadsheet, statistical software and herd management software.
Teaching Resources
In electronic format (available on the Ariel website).
Scientific literature provided by the teacher.
Scientific literature provided by the teacher.
Assessment methods and Criteria
The examination consists of an interview.
- Assessment method: oral test.
- Types of questions: oral questioning.
- Assessment parameters: thoroughness of knowledge, ability to organise knowledge; ability to reason critically; quality of exposition, competence in the use of specific vocabulary.
- Type of assessment: grade in thirtieths.
No differentiated testing methods are foreseen for attending and non-attending students
- Assessment method: oral test.
- Types of questions: oral questioning.
- Assessment parameters: thoroughness of knowledge, ability to organise knowledge; ability to reason critically; quality of exposition, competence in the use of specific vocabulary.
- Type of assessment: grade in thirtieths.
No differentiated testing methods are foreseen for attending and non-attending students
AGR/09 - AGRICULTURAL MACHINERY AND MECHANIZATION - University credits: 8
Practicals: 48 hours
Lessons: 40 hours
Lessons: 40 hours
Professor:
Tangorra Francesco Maria
Shifts:
Turno
Professor:
Tangorra Francesco MariaProfessor(s)
Reception:
phone or e-mail appointment