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Course Code: 
AGR202
Course Period: 
Spring
Course Type: 
Core
P: 
2
Application: 
2
Credits: 
3
ECTS: 
6
Course Language: 
İngilizce
Course Coordinator: 
Course Objectives: 

Agricultural, meteorological, phenolic etc. Gathering data with methods and transferring the necessary information to make informed decisions with data processing based on models, explaining how information systems can be used to increase agricultural production.

Course Content: 

Data collection by methods such as sensors, soil analysis, satellite tracking. Processing of collected data with cloud operations and artificial intelligence algorithms, data processing based on models, decision-supported forecasting and reporting.

Course Methodology: 
1: Lecture, 2: Question-Answer, 3: Discussion, 4: Simulation, 5: Case-study
Course Evaluation Methods: 
A: Testing, B: Presentation, C: Homework, D: Project, E:Lab

Vertical Tabs

Course Learning Outcomes

Course Learning Outcomes

Program

Learning Outcomes

Teaching Methods

Assessment Methods

Can define the technologies used in data collection for agricultural production.

5,11

1,2,3

A,B,C,E

Can collect necessary data for agricultural production.

5,11

1,2,3

A,B,C,E

Can model the data it collects.

5,11

1,2,3

A,B,C,E

Can make decision-supported predictions with data.

5, 11

1,2,3

A,B,C,E

Can use information technologies to increase agricultural production and reduce inputs.

5,11

1,2,3

A,B,C,E

Can report the data it has obtained and the decisions based on this data.

8,9,11

1,2,3

A,B,C,E

 

 

 

 

Course Flow

COURSE CONTENT

Week

Topics

Study Materials

1

Introduction to agricultural information systems

Lecture notes

2

Data collection methods

Lecture notes

3

Data collection methods

Lecture notes

4

Modeling of data

Lecture notes

5

Modeling of data

Lecture notes

6

Data-based forecast: Drought, disease, yield, etc. predictions

Lecture notes

7

Data-based forecast: Drought, disease, yield, etc. predictions

Lecture notes

8

Midterm

Lecture notes

9

Reporting decision-supported forecasts and transforming data into the value chain

Lecture notes

10

Case study

Lecture notes

11

Case study

Lecture notes

12

Case study

Lecture notes

13

Case study

Lecture notes

14

Recap

Lecture notes

 

 

 

 

Recommended Sources

RECOMMENDED SOURCES

Lecture Notes

 

Additional Resources

Textbook and other recommended books

 

Material Sharing

MATERIAL SHARING

Documents

Lecture Notes

Assignments

Homework, Presentation

Exams

Midterm, Final exam

 

Assessment

ASSESSMENT

IN-TERM STUDIES

NUMBER

PERCENTAGE

Midterm

 

60

Homework & case studies

 

20

Presentation

 

20

Total

 

100

Final to Success

 

40

Semester to Success

 

60

Total

 

100

 
 

Course’s Contribution to Program

COURSE'S CONTRIBUTION TO PROGRAM

No

Program Learning Outcomes

Contribution

1

2

3

4

5

 

1

To be able to comprehend the economic problems of agriculture; collecting, analyzing and interpreting data at micro and macro levels for economic applications; analyzing the ways of increasing production by applying the basic principles of economy in agriculture; to make the right decision for the future; to produce project based solutions; ability to apply with contemporary techniques.

 

 

 

 

 

 

2

To be able to monitor national and international agricultural markets, to understand the behavior of market actors; ability to predict the effects of economic and political developments on the Turkish agricultural sector, and interpret and make decisions.

 

 

 

 

 

 

3

Marketing of agricultural products by using marketing principles and methods; have the basic knowledge about market research and ability to interpret.

 

 

 

 

 

 

4

Agricultural production tools, equipment, methods and equipment to recognize; application of plant and animal production techniques and models; Ability to use the theoretical and practical knowledge related to plant breeding, plant breeding, seed production, genetics, physiology, ecology, biotechnology, plant gene resources, organic agriculture and meadow-pasture management in the field of field crops.

 

 

 

 

 

 

 

5

To develop and deepen their knowledge in the field of information systems at the level of expertise; interpreting and integrating the information acquired in information systems with the information coming from related disciplines; ability to develop new approaches to complex problems in applications in information systems.

 

 

 

 

X

 

6

To be able to master scientific resources and jurisprudence in the field of law; to be able to make comparative law analysis in national and international field; to ensure that the knowledge acquired in the field of law is transferred to the social and economic field; to have the ability of interdisciplinary analysis.

 

 

 

 

 

 

7

Ability to set goals and objectives for the organization / institution; information on project management, risk management and change management; awareness about entrepreneurship and innovation; awareness of occupational health and safety issues; information on sustainable development.

 

 

 

 

 

 

8

Ability to communicate effectively in oral and written English; the ability to write and understand effective reports, to make effective presentations, to give and receive clear and understandable instructions.

 

 

 

 

X

 

9

Ability to work effectively in disciplinary and multidisciplinary teams; self-study skills.

     

X

   

10

To act in accordance with ethical principles, professional and ethical responsibility awareness; the ability to inform the society on issues related to biodiversity, natural resources, air, water, soil pollution, recycling, environmental sensitivity, environmental protection.

     

 

   

11

Awareness of the necessity of lifelong learning; the ability to access information, follow developments in science and technology, and constantly renew oneself.

   

X

 

   
 

 

 

 

ECTS

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities

Quantity

Duration (Hour)

Total Work Load (Hour)

Course hours (Including exams week: 15xtotal lecture hour)

14

2

28

Study hours out of class (Pre-study, practice)

14

6

84

Midterm

1

2

2

Homework

6

3

18

Presentation

2

4

8

Final

1

3

3

Total Work Load

   

143

Total Work Load / 25 (h)

   

5,72

ECTS Credit of the Course

 

 

6

 

 

 

 

 
2