IJEP 39(8): 740-745 : Vol. 39 Issue. 8 (August 2019)
Karunya Institute of Technology and Sciences, Department of Electronics and Instrumentation Engineering, Coimbatore – 641 114
The nutrient status of plant can be affected due to environmental changes. Also the use of fertilizers in agriculture can also contribute to environmental pollution. The aim of this paper is to provide nutrient deficiency detection and classification of leaf diseases in maize crop using image processing techniques. Human beings are prone to error in detection of plant leaf diseases. Most of the plant diseases are caused by bacteria, virus and fungi. This paper addresses a solution for plant leaf nutrient deficiency and diseases based on colour, texture and shape that might affect the crop and give accurate solution to the farmer and improve the productivity. Also it helps the farmers to use appropriate chemical for the land and to find the application injuries in the field crop. This paper also presents an automatic detection of plant nutrient detection, classification and bacteria infected disease using image segmentation technique. Simulation has been done in MATLAB environment. The performance of the method is analyzed with respect to accuracy. The proposed method of nutrient deficiency detection is simple, robust and requires less computational time.
Nutrient deficiency, Image processing, Support vector machine, Plant disease detection and classification