A LITERATURE STUDY ON APPLICATION OF DATA MINING TOOLS FOR RICE YIELD PREDICTION

Abstract

Data Mining is Knowledge Discovery in Databases. Collection technique for efficient automated discovery of understandable patterns in large databases. Data mining extract knowledge from historical data. Agriculture crop production depends on biology, climate, economy and geography. Crop yield prediction helps in food security. Different varieties of rice are grown in different time schedule of year. Crop need different cultivation plan for ensuring maximum output. Agricultural crop production depends on various factors such as biology, climate, economy and geography. Also, Scientific and policy communities have recognized the susceptibility of crop agriculture to climate change and questioned the ability of farmers to adapt because of direct and strong dependence of crop agriculture on climate. Several factors have different impacts on agriculture, which can be quantified using appropriate statistical methodologies. Applying such methodologies and techniques on historical yield of crops, it is possible to obtain information or knowledge which can be helpful to farmers and government organizations for making better decisions and policies which lead to increased production. Here our focus is on the literature study on application of data mining techniques to extract knowledge from the agricultural data to estimate crop yield for major cereal crops.