Crop Yield Prediction

Abstract

Agriculture growth mainly depends on diverse soil
parameters, namely Nitrogen, Phosphorus,
Potassium, Crop rotation, Soil moisture, pH, surface
temperature and weather aspects like temperature,
rainfall, etc. Technology will prove to be beneficial
to agriculture which will increase crop productivity
resulting in better yields to the farmer. The proposed
project provides a solution for Smart Agriculture by
monitoring the agricultural field which can assist the
farmers in increasing productivity to a great extent.
This work presents a system, in a form of a website,
which uses Machine Learning techniques in order to
predict the most profitable crop in the current
weather and soil conditions. This system can also
help in predicting the yield of the crop using weather
parameter, soil parameter and historic crop yield.
Thus, the project develops a system by integrating
data from various sources, data analytics, prediction
analysis which can improve crop yield productivity
and increase the profit margins of farmer helping
them over a longer run.