Survey on Soil Prediction for Agriculture Using Data Mining Techniques

  • P.Sakthi Murugan et. al


Abstract Agriculture is the backbone of Indian Economy. The agriculture is fully based on the soil wealth, climatic conditions, irrigation, quality of seeds, harvesting etc.  It plays a vital role all over the world. Only an experienced farmer can identify the type of soil and choose the crop that suits it.  Primarily, the prediction of the soil type and its environmental atmosphere at a particular field is much important for the better yield of crop in future. This paper focuses on using various data mining techniques to predict the soil condition and getting the better yield of crops in future. The data mining techniques such as GIS, spatial mining, k-nearest neighbor, clustering are used in the research. These types of data mining techniques are used systematically to predict and analyze the bearing of the soil for the enhanced production of crops. This system would be of greater help to the farmers in classifying the nature of the soil and its wealth, which on the other hand, aids them in choosing the crop that is appropriate to their soil, soil fertility, in detecting the diseases and for the maximum yield of production.