Paper Details

Agrarian territory in India is facing drastic problem to maximize the crop productivity. The problem of yieldprediction is a primary issue that remains to be solved based on receivable statistics. A new later evolution inInformation Technology for agriculture zone has become a charming research area to estimate the crop turn-out. Varieddata Mining techniques are utilized and appraised in agriculture for predicting the forthcoming year’s cropmanufacture. Data mining techniques are the better preference for this objective. The environmental parameters likerainfall, sunlight, evaporation, Humidity, Temperature etc. that impacts the yield of crop and to implant relationshipamong these parameters. Yield prediction boots the peasants in impairing the losses and to get best prices for the crops.Estimation of food grain production credible omnibus and timely info on the food situation may patronize to thegovernment policies. This paper represents a concise analysis of crop yield prediction using Multiple Linear Regression(MLR) technique for the selected domain. By applying Regression and finding the correlation of each parameter withYield we are getting our Regression Model that gives 0.95(95%) value of R Square (Coefficient of Determination).

Saniya Vhora, Ankita Gohil, Priya Shah, Bhagirath Prajapati, Priyanka Puvar, “CROP YIELDING PREDICTION APPLYING REGRESSION: FORECASTING WHEAT/RICE YIELD FOR ANAND DISTRICT”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 13, pp. -, January 2017.