The presence of wide heterogeneity in the investigational material that is often used in agricultural research, led to the application of data mining tools and as a result many refinements and newer developments in statistics followed. Data mining, in fact, provides scientific tools for representative data collection, appropriate analysis and summarization of data and inferential procedures for drawing conclusions in the face of uncertainty. There is a need to provide remunerative prices for farmers in order to maintain food security and increase income of framers. Farmer finds himself thriftily poor and the most of the grains of rich agriculture have been appropriated by other section of the community. The difference between the engineering industry profit and agriculture sector produce profit tend them to leap over to the other sector. For this they need a capital investment and they find better way to make money is selling away the valuable and cultivable land to non agriculture purpose. So the food producing land is lost to the non-food producing sector, year by year the population of cultivable farmer and crop cultivable land is diminishing in a large chunk. By using clustering techniques this paper examines the current usage and details of agriculture land vanished in the past seven years.

Data mining Clustering Agriculture Food Security