Seed Yield Prediction Using Data Analytics

Seed Yield Prediction Using Data Analytics

Author Name : A. Bharanidharan, C. Naveen, M. Preetha

ABSTRACT A country's economy primarily depends on agriculture yield and the industries that use agro products. A successful yield depends on different parameter namely water, weather, soil characteristics, crop rotation, soil moisture, surface temperature, rainwater, NPK (soil, crop, fertilizer). Farmers need information regarding crop yield and crop rotation before sowing. In this paper predictive models are designed for crop yield and crop rotation using Data Analytics, as it is one of the affirmative platforms to implement large data tasks. The nominal Ratio Classification model and Linear Regression model are developed to calculate crop yield percentage and crop rotation for various crops.