Open AccessCrop Yield Prediction Using Machine Learning Techniques
Author(s) -
Ashwini I. Patil,
Ramesh Medar,
Vinod Desai
Publication year - 2020
Publication title -
international journal of scientific research in science, engineering and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-1990
pISSN - 2394-4099
DOI - 10.32628/ijsrset20736
Subject(s) - agriculture , decision tree , yield (engineering) , agricultural engineering , profit (economics) , damages , crop yield , crop , production (economics) , crop production , machine learning , environmental science , mathematics , computer science , agronomy , engineering , geography , forestry , economics , materials science , macroeconomics , archaeology , law , political science , metallurgy , biology , microeconomics
Today Indian economy depends upon agriculture. More than 70% of the people in India have taken it as a main occupation, day by day for a particular crop; the formers are not getting proper yield as well as profit due to environmental conditions like soil quality, weather, heavy rainfall, drought, seed damages, fertilizers, pesticides. The farmers not able to produce high production, so taking the historical agricultural data records we can predict the crop yield using machine learning techniques like Linear regression, comparative analysis are done with decision tree, KNN algorithms, using these to achieve the high accuracy and model performance is computed.