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Course unit
PRECISION FARMING
AVP5073559, A.A. 2019/20
Information concerning the students who enrolled in A.Y. 2019/20
ECTS: details
Type |
Scientific-Disciplinary Sector |
Credits allocated |
Core courses |
AGR/09 |
Agricultural Mechanics |
8.0 |
Course unit organization
Period |
Second semester |
Year |
1st Year |
Teaching method |
frontal |
Type of hours |
Credits |
Teaching hours |
Hours of Individual study |
Shifts |
Practice |
1.0 |
8 |
17.0 |
No turn |
Laboratory |
1.0 |
8 |
17.0 |
No turn |
Lecture |
6.0 |
48 |
102.0 |
No turn |
Examination board
Board |
From |
To |
Members of the board |
6 Commissione a.a. 2019/20 |
01/12/2019 |
30/11/2020 |
MARINELLO
FRANCESCO
(Presidente)
SARTORI
LUIGI
(Membro Effettivo)
CAVALLI
RAFFAELE
(Supplente)
GRIGOLATO
STEFANO
(Supplente)
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5
Commissione a.a. 2018/19 |
01/12/2018 |
30/11/2019 |
MARINELLO
FRANCESCO
(Presidente)
SARTORI
LUIGI
(Membro Effettivo)
CAVALLI
RAFFAELE
(Supplente)
GRIGOLATO
STEFANO
(Supplente)
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Prerequisites:
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General knowledge of agricultural mechanics and agricultural machinery |
Target skills and knowledge:
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The students will acquire basis for management of agricultural machineries in precision agriculture. In particular, knowing how to choose the modern information technologies in agriculture to maximize the potential of this technique. |
Examination methods:
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To be defined |
Assessment criteria:
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Students are evaluated and graded on the basis of their ability to:
- handle and discuss different topics covered by the lessons
- apply knowledge of precision farming principles to simple practical examples. |
Course unit contents:
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The course provides an overview of precision farming concepts and tools, including sensors, equipped instrumentation and software. Hands-on activities with local data will provide an initial experience in the use of these tools. Economic and environmental benefits are also discussed.
The course covers the following topics:
1. Introduction to Precision Agriculture and GNSS guidance systems
2. Remote and proximal sensors
3. Yield mapping
4. Map-based VRT
5. Sensors-based VRT
6. Telemetry, traceability and ICT in agriculture |
Planned learning activities and teaching methods:
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Teaching is based on lectures, working groups, case studies and on class exercises involving students individually.
Hands on or laboratory activities are also scheduled. |
Additional notes about suggested reading:
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The material used for the course will be made available to students through the Moodle platform of the School at
https://elearning.unipd.it/scuolaamv/login/index.php |
Textbooks (and optional supplementary readings) |
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