Developing An Agricultural Web Portal For Crop Disease Prediction Using Data Mining Techniques

Research Article
Samiksha Bhor., Shubha Kotian., Aishwarya Shetty and Prashant Sawant
CBIR, Crop disease, data mining, naïve bayes, image comparison, prediction, sugarcane.

Agriculture is the basic occupation of all Indians. Farmer is said to be man of nation. We consider this as our responsibility to explore this occupation and take it to a higher level from technology point of view. The basic purpose for developing this system is crop disease prediction using various data mining techniques. Our project describes a new approach to crop disease prediction which helps to prevent future economical losses. This project emphasizes on every single concept related to crop diseases. This is accomplished by building a web platform in which farmers can interact with expert, share their experiences and knowledge. This results in a dynamically-growing online survey, which ultimately helps in data collection that can be used to identify various crop diseases and helps to prevent them. This portal can be used for multiple purposes where agro based industries can use our data to launch their products as well as acquire feedbacks. Agricultural institutes can explore new patterns in crop diseases and use required technology to prevent them. This system will be helpful for students perceiving agriculture studies, they can collect the correct information from the appropriate source and in precise manner.