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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) Do I have all these things in my computer? • The representation is known as ‘the model’ These representations help me to understand how the things would be in reality 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 General Types of Models Deterministic Static Dynamic Stochastic Empirical & Mechanistic Mathematical 3D 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. Processes Modelled Nutrients Water Agriculture CO2 Response Crop Growth Greenhouse Gas Emissions 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 (Average Yield + Average Quality) @ Waste of Resources (More Yield + Better Quality) @ Economical Resources GIS Computer Vision GPS Geographic Information System A system designed to manipulate and analyze geographical data GIS Geographic data Software • 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 Hardware 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 Automation A Typical Computer Vision System (Planting, Fertilizing, Spraying, Harvesting) Sorting Output Feature extraction (For Research) Food quality inspection Color, leaf-area, water status, spectral analysis, etc 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 Thanks For yours kind attention