Authors: Nitin Vamsi Dantu; Shriram K. Vasudevan; K. Vimalkumar
Addresses: Department of Computer Science and Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, 641112, India ' K. Ramakrishnan College of Technology, Kariyamanikam Road, Samayapuram, Trichy – 621112, India ' Department of Computer Science and Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, 641112, India
Abstract: The farmers are facing a lot of challenges and one of the main problems they face is because of plant diseases. The energy to the disease fungi is taken from the plants which they live on. They are responsible for the huge damage and the damages are classified into wilting, rusts, blotches, scabs, mouldy coatings, and rotted tissue. Most of the farmers are being affected with huge losses as they do not find the right solution for a certain disease that their crops have. The primary goal of this research is to find the common diseases in the plants and suggest the optimal solution that helps in reducing the fault rate of crops and in turn, it increases the crop yield. This would lower the crop damage drastically and the consumers can purchase better quality products. We propose to use deep learning techniques to identify diseases in crops in real-time, the same can be made as a mobile app that could help farmers or anyone to detect the diseases for the plants. The system is found to be functionally very stable and works under all ideal conditions.
Keywords: plant diseases; image processing; convolution neural network; CNN; classification; technology for agriculture; deep learning.
International Journal of Sustainable Agricultural Management and Informatics, 2021 Vol.7 No.1, pp.1 - 16
Received: 12 Jun 2020
Accepted: 29 Jun 2020
Published online: 26 Feb 2021 *