Abstract: Survey made on this area reveals the importance of data mining techniques on agriculture. Lots of data mining Techniques have been used in agriculture . We present some of the most used data mining techniques in the field of agriculture . In the near future the penetration of Information Technology and Agriculture results is more interesting area of research. The main aim of the work is to improve and substantiate the validity of yield prediction which is useful for the farmers . Agricultural crop production depends on various factors such as biology, climate, economy and geography. Several factors have different impacts on agriculture, which can be quantified using appropriate statistical methodologies. Agronomic traits such as yield can be affected by a large number of variables. In this survey, we analyzed a DM methods like clustering, classification models to select the most relevant method for the prospect .
Keywords: Agriculture, Yield Prediction, agricultural productivity, Classification, Clustering.