أمراض عن للكشف المعلومات تكنولوجيا في التقدم النباتات

ADVANCES IN INFORMATION TECHNOLOGY FOR DETECTION OF PLANT DISEASES

By الطويل/ مصطفي محمد د

والتكنولوجيا للعلوم العربية ،األكاديمية

المصرية البحثية المجموعة عضوSRGE 08/4/2014 – Cairo Egypt

Scientific Research Group in Egyptwww.egyptscience.net

Introduction UN’s Food and Agriculture Organization

(FAO) admitted that food insecurity continues to be a major development problem across the globe*. This problem usually affects to developing countries.

*http://www.libelium.com/es/food_sustainability_monitoring_sensor_network/

IntroductionFood Security Risk Index 2010

http://www.libelium.com/es/food_sustainability_monitoring_sensor_network/

Introduction Plant diseases have turned

into a dilemma as it can cause significant reduction in both quality and quantity of agricultural products.

The naked eye observation of experts is the main approach adopted in practice for detection and identification of plant diseases

Introduction

The Cost

Continuous monitoring of an expert is too

expensive and time consuming

Expert expenses + Value of damage +

Cost of control

The Solution

The use of Computer-based techniques to detect the plant

diseases in its early stages

Computer-based DetectionMachine Learning Tech.

Usually, Machine learning techniques are the first choice. The recent researches provide clues on their ability to detect and to identify the plant diseases in its early stages

Machine Learning Tech.

Al-Hiary, H., et al. "Fast and Accurate Detection and Classification of Plant Diseases."  International Journal of Computer Applications 17

Machine Learning Tech.

Al-Hiary, H., et al. "Fast and Accurate Detection and Classification of Plant Diseases."  International Journal of Computer Applications 17

Computer-based DetectionMachine Learning Tech.

An Indian researcher used ML to establish weather-based prediction models of plant diseases.

Kaundal, Rakesh, Amar S. Kapoor, and Gajendra PS Raghava. "Machine learning techniques in disease forecasting: a case study on rice blast prediction." BMC bioinformatics 7.1 (2006): 485.

Computer-based DetectionExpert Systems Expert systems have applications in many domains.

They are mostly suited in situations where the expert is not available.

In order to develop an expert system the knowledge has to be extracted from domain expert.

Computer-based DetectionExpert Systems

An Indian researcher had developed an Expert System for diagnosis of diseases in Rice Plant

Sarma, Shikhar Kr, Kh Robindro Singh, and Abhijeet Singh. "An Expert System for diagnosis of diseases in Rice Plant." International Journal of Artificial Intelligence 1.1 (2010): 26-31.

Computer-based DetectionExpert Systems

The rapid development of World Wide Web has provided another way of using expert systems.

A Palestinian Researcher developed Dr. Wheat.

Computer-based DetectionExpert Systems

Computer-based DetectionRemote Sensing

Hyperspectral sensors onboard of satellites or on AutoCopter to allow to continuously monitor the spatial and temporal physiological and structural changes in a plant production system  

Remote sensing provides growers with yield assessments, shows yield variations across fields and give information about the growth rate at important development stages. This includes detection of stress due to drought and nutrient deficiency as well as a result of plant diseases or animal pests.

Computer-based DetectionRemote Sensing

http://plantstress.bioiberica.com/Training/What_is/Plant_stress.html

Computer-based DetectionRemote Sensing

Computer-based DetectionWireless Sensor Networks

http://www.libelium.com/es/food_sustainability_monitoring_sensor_network/

Conclusion The applications of ICT, especially the

sensory based ones, will help the expert to accurately detect the problem attached to the corps.

Thank youE-mail: mohamed_mostafa@aast.edu