Diagnosis of Paddy Diseases using Data Mining Technique

Abstract

 Day by Day the population is increasing and there is an urgent need to produce more food, especially in Asia. According to India today survey the farmer’s suicides are reduced but not eradicated. The main reason for Agriculture is the most vital part of India’s economy as 70 percent of their village people primarily depend upon agriculture for livelihood. Agriculture also contributes a lot to India’s GDP. Rice plays a key role in India, majority of poor people consume rice as their daily food due to low cost and most available food. Committing suicide is yield loss. Rice production throughout the world is being affected due to many factors such as lack of capital, Unseasonal rains, Climatic changes, lack of proper management on pests and diseases etc. Even though increasing in pollution causing different types of unknown diseases to plants and also common farmers cannot identify type of disease, it results in damage of crops and low production. There is a lot of research is happening to identify the various diseases in paddy and providing advice to farmers accordingly  still it is not giving expected results and not able to address the problem thoroughly. So, there is an urgent need in the area of paddy diseases detection and prevention. This research work aims to identify most frequently occurred diseases using Data Mining Technique and also suggested the prevention mechanism to help farmers in a great way. This experimental result proves that Data mining algorithms can be used to diagnosis the plant diseases more effectively.