Effect of temperature and rainfall on paddy yield using data mining

Prediction of agriculture yield is a job that requires unification of knowledge from several areas such as data mining, statistics and agriculture. Subject of crop yield prediction has been very popular among various organizations working in agriculture, producers etc. Ρrediction of crop yield helps in managing the storage of crops as well as it directs the transportation decisions, and risk management issues related to crops. Pattern of rainfall and temperature aredynamic due to global warming, and resulting in undergoing impingement on crop productivity. Data Mining focuses upon methodologies for extracting useful knowledge from data and there are several tools to extract the knowledge that is it is a proficiency of examining the dataset such that the end results can be deduced easily and rapidly from the dataset. The knowledge gathered can be used ο forecast the paddy yield. But farmers do not use any knowledge discovery process approach on paddy yield data. Data mining can be used in agriculture for decision making. In this study, we collected data from different government organizations, after preprocessing and discretization of data applied Predictive Apriori algorithm using Data Mining tool (WEKA) for analysis of daily temperature, daily rainfall and paddy yield to predict the paddy yield and to analyze the effect of temperature and rainfall on the paddy yield.