2021, Vol. 2, Issue 1, Part A
Diagnosis of the crop disease based on machine learning
Author(s): Indraneel Parab
Abstract: India is known for the multiple types of crops the farmers here yield. But out of all these multiple crops Wheat is the most important crop. According to the database the total area under the wheat crop is about 29.8 million hectares in the country. However, India’s overall wheat yields per unit area of land are still well below the world average. Analysts suggest that to compete with other agriculture leading countries there is further room for development available for increasing wheat productivity in the country. According to world-grain.com India’s wheat consumption is forecast to increase in 2020-21 to 93 million tonnes due to the immense rate at which our population is growing which will result in excessive demand in domestic supplies. Every year the amount of wheat production lost owing to plant diseases varies between 10–25%. To yield and supply such a huge amount of wheat farmers across the country need to enhance their farming techniques as soon as possible. This project is one of the ways through which they can succeed in doing so. Disease diagnose system is a project designed primarily for use in the rural agricultural area where farmers take wheat crops on average sized farm lands. This project will allow farmers to increase the crop yield by reducing the possibility of crops catching a disease. This system also provides the user (farmer) with solutions for given disease. Common diseases and their symptoms are listed out in this project using which we will create an algorithm which helps the farmer to identify whether or not his crop is affected with the disease. The algorithm will help in identifying the pattern and make decisions with minimal human intervention. This project will not only help the farmers in their cultivation but it will also stop the wastage of crops because the farmers can start the appropriate treatment as soon as possible once the correct disease is identified. This will make farmer’s lives far easier.
Pages: 66-70 | Views: 450 | Downloads: 148
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How to cite this article:
Indraneel Parab. Diagnosis of the crop disease based on machine learning. Int J Res Circuits Devices Syst 2021;2(1):66-70.