Application of

Modeling

&

Information Communication Technology (ICT)

in Agriculture

Dr. M. Ahsan Latif

Department of Computer Science

University of Agriculture, Faisalabd

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

What is Modeling?

• Modeling is way to represent something (real or conceptual)

• The representation is known as ‘the model’

Do I have all these things in my computer?

These representations help me to understand how the things would be in reality

• 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

Why Modeling?

Four Main Reasons / Objectives

General Types of Models

Deterministic

Stochastic

Dynamic Static

Empirical & Mechanistic

3D

Mathematical

Modeling in Agriculture

Analysis of Crop Modelling for Climate Change and Food Security

Consultative Group on International Agricultural Research (CGIAR) Earth Systems Science Partnership (ESSP)

Mission StatementThe 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.

Processes Modelled

WaterNutrients

Crop GrowthCO2 Response

Greenhouse Gas Emissions

Agriculture

Modeling in Agriculture

Open Pdf File ‘Survey Data’

Types of the Models Reported w. r. t Functionality

The Limiting Factors for Model Development

Information Communication Technology

ICT For Agriculture

The state-of-the-art ICT technology has revolutionized the Agriculture

Classical Agriculture Precision Agriculture

GIS

GPSComputer Vision

(More Yield + Better Quality) @ Economical Resources

(Average Yield + Average Quality) @ Waste of Resources

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

GIS in Agriculture

• 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

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

GPS-Applications in Agriculture

Computer Vision – Applications in Agriculture

Feature extraction (For Research)

Automation

(Planting, Fertilizing, Spraying, Harvesting)

Food quality inspection

Sorting

Color, leaf-area, water status, spectral analysis, etc

Output

A Typical Computer Vision System

The theme of computer vision has been to duplicate the abilities of human vision by electronically perceiving and understanding an image

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

ThanksFor yours kind attention