1. Application of Modeling & Information Communication Technology (ICT) in Agriculture
Dr. M. Ahsan Latif
Department of Computer Science
University of Agriculture, Faisalabd

2. Contents What is Modeling? Why we need it? General Types of Models
Modeling in Agriculture
What is ICT?
ICT in Agriculture
GIS
GPS
Computer Vision
Conclusion

3. Do I have all these things in my computer?
What is Modeling?
Modeling is way to represent something (real or conceptual)
The representation is known as ‘the model’
These representations help me to understand how the things would be in reality

4. Four Main Reasons / Objectives
Why Modeling?
Four Main Reasons / Objectives
Descriptive
To characterize the systems.
Prediction
To forecast future system behavior
Postdiction
To explain after-the-fact what caused a given outcome
Prescription
To get guidance on how a system should be managed to meet some goal

5. General Types of Models
Dynamic
Deterministic
Static
Stochastic
Empirical & Mechanistic
Mathematical 3D

6. Modeling in Agriculture
Consultative Group on International Agricultural Research (CGIAR)
Earth Systems Science Partnership (ESSP)
Analysis of Crop Modelling for Climate Change and Food Security
Mission Statement
The aim of the survey was to collate information, opinions and expert feedback across a wide range of people involved, either directly or in--‐directly, on crop model development and application. The purpose of this was to provide information representing the crop modelling community’s current views on the state of model development, and how they can be improved to support research and decision making on issues of climate change impacts, mitigation and adaptation, and food security. From this it is hoped that improvements in crop modelling capabilities can be utilized to achieve food security, enhancing livelihoods and improving environmental management in the developing world, considering the threats posed by climate change.

7. Greenhouse Gas Emissions
Processes Modelled
Water
Nutrients
Crop Growth
CO2 Response
Greenhouse Gas Emissions
Agriculture

8. Modeling in Agriculture Open Pdf File ‘Survey Data’

9. Types of the Models Reported w. r. t Functionality

10. The Limiting Factors for Model Development

11. Information Communication Technology

12. Classical Agriculture Precision Agriculture
ICT For Agriculture
The state-of-the-art ICT technology has revolutionized the Agriculture
Classical Agriculture
GIS
GPS
Computer Vision
Precision Agriculture
(More Yield + Better Quality) @
Economical Resources
(Average Yield + Average Quality) @
Waste of Resources

13. Geographic Information System
A system designed to manipulate and analyze geographical data
GIS Geographic data Software Hardware
Geographic data: Links the data with spatial information
(e. g. topography, hydrography, roads, agriculture, buildings, etc)
Depends on Satellite or aerial photography
GIS combines Geographic data
Data is organized in thematic layers
Data is presented in graphical form
Helps in decision making

14. GIS in Agriculture Advantages
In a map of agricultural area, for example, one layer each for the following could be
produced, i. e., piece of land, soil types, crop yield, specific soil treatment, and irrigation.
The interrelationship among these layers can be concluded.
Possible applications are yield data analysis, site specific prescription, irrigation
planning, terrain analysis, crop growth modeling, etc.
Advantages
Greater support for precision farming
Better understanding of risk factors
Higher revenue generation
Better resource management
Better policy making
Possible layers for Agriculture

15. GPS - Global Positioning System
Space & Land based system to determine position precisely
Mostly used in Military and Agriculture
Millions of users around the world
Hand held or vehicle mounted

16. GPS-Applications in Agriculture

17. Computer Vision – Applications in Agriculture
Automation
A Typical Computer Vision System
Output
(Planting, Fertilizing, Spraying, Harvesting)
Sorting
The theme of computer vision has been to duplicate the abilities of human vision by electronically perceiving and understanding an image
Feature extraction (For Research)
Food quality inspection
Color, leaf-area, water status,
spectral analysis, etc

18. Conclusion We need to improve and strengthen our mathematics
Programming capabilities of the students / faculty should be improved
Interdepartmental cooperation for joint research and development needs progress
New courses on state-of-the-art technology must be inducted in the curriculum

19. For yours kind attention
Thanks
For yours kind attention