A Review of Image Processing Software Techniques for Early Detection of Plant Drought Stress

 

 

Author: Chege A. Kirongo
Abstract: Water stress is one of the most important growth-limiting factors in crop production around the world, water in plants is
required to permit vital processes such as nutrient uptake, photosynthesis, and respiration. Drought stress in plants causes major
production losses in the agricultural industry worldwide. There is no sensor commercially available for real-time assessment of health
conditions in beans. Currently, there are several methods to evaluate the effect of water stress on plants and commonly practiced
method over the years for stress detection is to use information provided by remote sensing. Studies exist which determined the effect
of water stress in plants grown under the different watering regime, while other studies explore the performance of the artificial neural
network techniques to estimate plant yield using spectral vegetation indices. This review recognizes the need for developing a rapid
cost-effective, and reliable health monitoring sensor that would facilitate advancements in agriculture

Keywords: Image Processing, Artificial Neural Networks, Drought stress, Algorithm, Technique

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About the Author: Amos Chege

I am currently a PhD. Computer Science student with a research interest in the area of Image Processing, machine learning, and data mining. My PhD. proposed work is based on development of Algorithms that will result in the creation of solutions for farmers faced with challenges on detection of a variety of plan stresses and remedying the challenges through Technology. In the area of Assistive Technologies, my research team and I have done research work in the area of Competence Network for e-Inclusion and Assistive Technologies. The research team from University of Applied Sciences Austria and Meru University of Science and Technology Kenya, managed to attract seed fund, and conducted a pilot study. The study was based in Meru County in Kenya where we were able to identify the need for Information Communications Technology (ICT) Assistive Devices for Special school Learners with Physical Disability. The gap identified will lead to design and roll-out of Innovative technologies that will enable learners in Special Schools access learning content electronically and be able to learn like other children. Findings of this study were presented during the 10th Decolonizing the Spirit Conference in University of Embu in July 2016. In the area of Open Government Data, together with my co-authors, we succeeded in proposing a model for integration of Open Government Data to Content Management Systems in Kenya. The research findings have been presented during the Nairobi Innovation Week Research Symposium at the University of Nairobi in March 2017. During the 11th Egerton University's International Conference and Innovation Week, held in March 2017, we were awarded the Best Paper Presentation in the category of Governance, Law and Security. We have proposed a model for adoption of Open Government Data in Kenya. In the area of Electronic Learning, we have done with my co-authors research in the areas of eLearning adoption and use in Institutions of Higher Learning and presented in the KEMU 2016 Annual Research Conference We have also done papers on Electronic waste management and disposal and presented in the International Conference on University - Industry Linkages held in Meru University of Science and Technology in October 2017. Currently ongoing research interests are in the area of Image Processing, Assistive technologies, Open Government Data, Enterprise Resource Planning adoption initiatives, Information Systems Risks and Security, and Remote Sensing in Turbidity Measurement in Water.

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