• Mohanadevi M
• Vinodhini V

This Data mining a techniques of examining large pre-existing databases in order to generate new information .It also pays a vital role in the field of Agriculture crop yield analysis. Data mining proves to be fertile ground for future innovations in agricultural statistics. Use of data mining techniques has been increased in agriculture field due to enhancement in the technology. Agriculture yield analysis is a very complex and vast research area as it deals with large data sets including different factors viz. yields of various crops, meteorological parameters affecting crop yields, diseases, pests [1]. So farmers are always curious about yield prediction. Crop yield depends on various factors like soil, weather, rain, fertilizers and pesticides. 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 decision and policies which lead to increased production [2]. In this paper discussed about applying various data mining techniques for agriculture growing crop yield prediction.

Data Mining Techniques, Agriculture, Crop Yield Analysis.

" A Study on Various Data Mining Techniques for Agriculture Crop Yield Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 9, page no.797-802, September-2018, Available :http://www.jetir.org/papers/JETIR1809626.pdf

" A Study on Various Data Mining Techniques for Agriculture Crop Yield Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 9, page no. pp797-802, September-2018, Available at : http://www.jetir.org/papers/JETIR1809626.pdf