Information Package / Course Catalogue
Introduction to Digital Agriculture Technologies
Course Code: DJTA002
Course Type: Required
Couse Group: Short Cycle (Associate's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 0
Credit: 2
Lab: 0
ECTS: 2
Objectives of the Course

The aim of the course is to introduce students to digital technologies used in agriculture and provide a foundation for further specialization.

Course Content

The course addresses the evolution of digital agriculture, current tools like sensors and automation, and case studies from precision farming.

Name of Lecturer(s)
Ins. Ali Kemali ÖZUĞUR
Learning Outcomes
1.Defines basic concepts and the historical development of digital agriculture.
2.Evaluates the contributions of digital applications to agricultural production.
3.Identifies fundamental digital tools used in agriculture.
4.Discusses the environmental and economic impacts of digital technologies.
5.Analyzes the role of farmers in the digital transformation process.
Recommended or Required Reading
1.Özdemir, D. (2020). Agricultural Information Systems and Smart Farming.
2.Zhang, Q. (Ed.). (2016). Precision Agriculture Technology for Crop Farming. CRC Press.
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to digital agriculture and its historical development
Week 2 - Theoretical
Agriculture 4.0 and principles of digital transformation
Week 3 - Theoretical
Sensor technologies and agricultural data collection
Week 4 - Theoretical
Digital tools used in agriculture (tablet, GPS, data logger, etc.)
Week 5 - Theoretical
Geographic Information Systems (GIS) and remote sensing
Week 6 - Theoretical
Digital monitoring of climate and environmental data
Week 7 - Theoretical
What is precision agriculture? Basic principles
Week 8 - Theoretical
Applications of IoT (Internet of Things) in agriculture
Week 9 - Theoretical
Introduction to decision support systems and artificial intelligence
Week 10 - Theoretical
Big data and analytics in digital farming
Week 11 - Theoretical
Smart farming machinery and automation
Week 12 - Theoretical
Digital livestock applications
Week 13 - Theoretical
Sustainability and the future of digital agriculture
Week 14 - Theoretical
General review and evaluation
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140228
Reading40416
Individual Work2024
Midterm Examination1022
Final Examination1022
TOTAL WORKLOAD (hours)52
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
PÇ-12
PÇ-13
PÇ-14
PÇ-15
PÇ-16
PÇ-17
PÇ-18
PÇ-19
PÇ-20
OÇ-1
3
OÇ-2
OÇ-3
3
OÇ-4
4
3
OÇ-5
Adnan Menderes University - Information Package / Course Catalogue
2026