You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
This project aims to design, develop and implement the training model by using different inputs data. The machine will able to learn the features and extract the crop yield from the data by using data mining and data science techniques.
This is the ORCHIDEE-CROP model used in the paper "Future warming increases the chance of success of maize-wheat double cropping in Europe". For installing ORCHIDEE-CROP model, including the calculation environmental setting, please visit: https://forge.ipsl.jussieu.fr/orchidee/wiki/Documentation/UserGuide
A web application created to predict the crop yield based on historical data. It can perform basic analysis, along with plotting the crop harvest in various states.
Harness the power of machine learning to forecast rice and wheat crop yields per acre in India, aiming to empower smallholder farmers, combat poverty and malnutrition, utilizing data from Digital Green surveys to revolutionize agriculture and promote sustainable practices in the face of climate change for enhanced global food security.