Smart Farming in Crop Production (5cr)
Code: 9A00CY59-3002
General information
- Enrollment
- 15.04.2025 - 03.09.2025
- Registration for the implementation has ended.
- Timing
- 01.09.2025 - 12.10.2025
- Implementation has ended.
- Number of ECTS credits allocated
- 5 cr
- Local portion
- 5 cr
- Mode of delivery
- Contact learning
- Unit
- SeAMK Agriculture
- Campus
- SeAMK Seinäjoki, Frami
- Teaching languages
- Finnish
- Degree programmes
- Bachelor of Natural Resources, Agriculture and Rural Enterprises
- Teachers
- Juha Tiainen
- Jori Lahti
- Groups
-
MAGRO23Bachelor of Natural Resources
-
AGRO23TABachelor of Natural Resources, Agriculture and Rural Enterprises
-
AGRO23PRBachelor of Natural Resources, Agriculture and Rural Enterprises
-
AGRO22TABachelor of Natural Resources, Agriculture and Rural Enterprises
-
AGRO22PRBachelor of Natural Resources, Agriculture and Rural Enterprises
- Course
- 9A00CY59
Evaluation scale
Passed/failed
Objective
The student is able to evaluate the suitability of new solutions in the agrotechnology field as an enhancer of agricultural production processes and is currently able to utilize information in the development of exemplary state of the art technologies. They are able to introduce versatile technologies for cultivation measures and to describe the technological basics of precision farming. He / she is able to choose different cultivation technologies and assess their relevance and usability.
Content
New innovations in agrotechnology
- Precision farming concept and technology
- Harvesting Equipment
- Driving signals and automatic steering
- ISOBUS equipment principles
- Drones and utilizing the image information they produce, practice
- Commercial examples and their use
Materials
-Pesonen, L., Kaivosoja, J. ja Suomi P. 2010. Täsmäviljely ja ravinteiden käytön
tarkentaminen. Teho-hankkeen julkaisuja 5/2010. Saatavana: https://www.doria.fi/bitstream/handle/10024/94183/T%C3%A4sm%C3%A4viljely%20ja%20ravinteiden%20k%C3%A4yt%C3%B6n%20tarkentaminen.pdf?sequence=2
-Riikonen, A. 2017. Big Data päätöksenteon apuvälineenä kasvinviljelytilalla. YAMK opinnäytetyö. Savonia. Saatavana: https://www.theseus.fi/bitstream/handle/10024/131282/Riikonen_Aila.pdf?sequence=1&isAllowed=y
-Material gathered during the studies
Teaching methods
-Contact teaching
-Practical exercises
-Literal assignments
Student workload
Total work load of the course is 134 h of which
-Lectures 39 h
-Practical exercises 95 h
Assessment criteria, approved/failed
Accepted: The student is able to analyze the possibilities of new innovations in agrotechnology for Finnish farms. The student is, also, able to evaluate and choose precision farming technology to an example farm.