Information Package / Course Catalogue
Use of Artificial Intelligence in Animal Husbandry
Course Code: ZT477
Course Type: Area Elective
Couse Group: First Cycle (Bachelor's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 0
Credit: 2
Lab: 0
ECTS: 3
Objectives of the Course

The objective is to provide students with a theoretical understanding of how artificial intelligence technologies are utilized in the livestock sector, the problems they address, examples of applications from around the world, and their potential for the future.

Course Content

It encompasses topics such as the fundamentals of artificial intelligence, machine learning, big data analysis, image processing, monitoring animal behavior and health, animal feeding, genomic breeding strategies, farm automation, decision support systems, ethical considerations, and sector-specific examples.

Name of Lecturer(s)
Learning Outcomes
1.Explains the fundamental concepts and working principles of artificial intelligence, machine learning, and data science, as well as their potential applications in animal husbandry.
2.Describes data sources, sensor technologies, machine vision systems, and data collection methods used in animal husbandry.
3.Evaluates the applications of artificial intelligence-based methods in animal production, herd management, animal health monitoring, nutrition, and breeding programs.
4.Interprets the role and contributions of big data analytics and artificial intelligence-driven decision support systems in livestock enterprises.
5.Discusses the ethical, legal, environmental, and societal implications of artificial intelligence applications in animal husbandry and analyzes current developments and future trends.
Recommended or Required Reading
1.De Baerdemaeker, J., Hemming, S., Polder, G., Chauhan, A., Petropoulou, A., Rovira-Más, F., ... & Hostens, I. (2023). Artificial intelligence in the agri-food sector: Applications, risks and impacts. Panel for the Future of Science and Technology, EPRS, European Parliamentary Research Service.
2.FAO, AGRIS
Weekly Detailed Course Contents
Week 1 - Theoretical
Course Introduction and Fundamentals of Artificial Intelligence
Week 2 - Theoretical
What is Artificial Intelligence? The Principles of its mecanism
Week 3 - Theoretical
Fundamentals of Machine Learning and Data Science
Week 4 - Theoretical
Types and Algorithms of Artificial Intelligence
Week 5 - Theoretical
Agriculture 4.0 and Smart Livestock
Week 6 - Theoretical
Image Processing and Machine Vision Systems
Week 7 - Theoretical
Digitalization, Sensor Technologies, and Data Collection in Animal Husbandry
Week 8 - Theoretical
Big Data and Its Applications in Animal Husbandry
Week 9 - Theoretical
Applications of Artificial Intelligence in Rumminants
Week 10 - Theoretical
Applications of Artificial Intelligence in Small Rumminants
Week 11 - Theoretical
Applications of Artificial Intelligence in Poultry, Aquaculture, and Apiculture
Week 12 - Theoretical
Animal Health Monitoring Systems and Animal Welfare
Week 13 - Theoretical
Ethics, Data Security, and Regulations
Week 14 - Theoretical
Future Trends and Potential of Artificial Intelligence in Animal Husbandry
Assessment Methods and Criteria
Type of AssessmentCountPercent
Quiz2%10
Midterm Examination1%30
Final Rate1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory142256
Quiz2114
Midterm Examination1819
Final Examination1819
TOTAL WORKLOAD (hours)78
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
OÇ-1
4
3
1
3
2
1
4
1
1
OÇ-2
3
3
2
4
4
1
3
1
1
OÇ-3
3
4
2
4
3
1
3
1
2
2
OÇ-4
3
4
2
4
4
1
4
1
3
2
OÇ-5
2
2
1
2
1
1
4
4
3
4
Adnan Menderes University - Information Package / Course Catalogue
2026