
| Course Code | : TB231 |
| 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 |
With the developing technology, digital and smart agriculture systems called 4th Period agriculture have entered our lives. These technologies include smart irrigation systems, smart planting systems, unmanned aerial vehicles and pesticides and risk management determinations. Within the scope of this course, the achievements in the period called
In the 2010s, with the revolution in industry with industry 4.0, information technologies began to be used intensively in agriculture. This process is a production where agronomists are empowered with a variety of tools and technologies that help them be more productive and efficient. The transition process from intensive use of labor to information power is in question in this period. Among the main objectives of Agriculture 4.0 is to make the most suitable production for low cost, fast, economic and expectation or market. For this purpose, economical technological planting vehicles, irrigation equipment and unmanned agricultural vehicles are used.
| 1. | 1. Recognition of current technology in agriculture |
| 2. | 2. Integration of smart systems in agricultural production |
| 3. | 3. The ability to use unmanned vehicles in agricultural production |
| 4. | 4. Facilitation of risk management and early diagnosis systems due to digitalization in agricultural production |
| 5. | 5. Instant data flow and reporting methods with digital agricultural systems |
| 1. | 1. Zhang, Q. (2016). Precision agriculture technology for crop farming (p. 374). Taylor & Francis |
| 2. | 1. Zhang, Q. (2016). Precision agriculture technology for crop farming (p. 374). Taylor & Francis. 2. Ozguven, M. M. (2023). The Digital Age in Agriculture. CRC Press. 3. Mouazen, A., Castrignano, A., Moshou, D., Buttafuoco, G., & andRaj Khosla, O. N. (2020). Agricultural internet of things and decision support for precision smart farming. |
| 3. | 3. Mouazen, A., Castrignano, A., Moshou, D., Buttafuoco, G., & andRaj Khosla, O. N. (2020). Agricultural internet of things and decision support for precision smart farming. |
| Type of Assessment | Count | Percent |
|---|---|---|
| Seminar | 1 | %10 |
| Assignment | 1 | %10 |
| Midterm Examination | 1 | %20 |
| Final Examination | 1 | %60 |
| Activities | Count | Preparation | Time | Total Work Load (hours) |
|---|---|---|---|---|
| Lecture - Theory | 14 | 1 | 2 | 42 |
| Midterm Examination | 1 | 14 | 1 | 15 |
| Final Examination | 1 | 17 | 1 | 18 |
| TOTAL WORKLOAD (hours) | 75 | |||
PÇ-1 | PÇ-2 | PÇ-3 | PÇ-4 | PÇ-5 | PÇ-6 | PÇ-7 | PÇ-8 | PÇ-9 | PÇ-10 | PÇ-11 | |
OÇ-1 | 5 | 4 | |||||||||
OÇ-2 | |||||||||||
OÇ-3 | |||||||||||
OÇ-4 | 4 | ||||||||||
OÇ-5 | |||||||||||