Growth of agriculture also depends on diverse soil parameters, crop rotation ... Jute and Wheat. The prediction is based on analyzing a static set of data using Supervised Machine Learning techniques.

Interactions among different genetic, environmental, and management factors and uncertainty in input values are making crop yield prediction complex. Building upon a previous work in which we coupled ...

Instead, Descartes relies on 4 petabytes of satellite imaging data and a machine learning algorithm to figure out how healthy the corn crop is from space. Corn yield prediction is big business in ...

This project uses machine learning techniques ... for real-time yield predictions based on user-inputted farming conditions. The trained LightGBM model is deployed using Gradio. Users can input ...

Strictly speaking, Machine Learning ... to biophysical crop models (Basso and Liu, 2019) which have the added advantage of providing a framework for understanding the system. Such interpretability is ...