Devdiscourse

From crop monitoring to AI analytics, drones redefine smart agriculture

The transformation is documented in the study A Review of Drones in Smart Agriculture: Issues, Models, Trends, and Challenges ...
IEEE

In-Season Corn Yield Prediction Using Satellite-Derived Solar-Induced Chlorophyll Fluorescence and Machine Learning Algorithms

Abstract: Accurate in-season crop yield prediction is critical for timely agricultural decision-making, food security, and climate-resilient farm management. This study presents a framework for ...
EurekAlert!

Machine learning offers growers a new tool for predicting crop water use

A new study shows that machine-learning models can accurately predict daily crop transpiration using direct plant measurements and environmental data. By training models on seven years of ...
GitHub

A GNN-RNN Approach for Harnessing Geospatial and Temporal Information: Application to Crop Yield Prediction

This codebase is the implementation of the GNN-RNN model (AAAI 2022) for crop yield prediction in the US. GNN-RNN is the first machine learning method that embeds geographical knowledge in crop yield ...
Frontiers

Integrating meteorological and breeding data to predict maize yields using machine learning algorithms

Introduction: Accurate crop yield prediction is vital for ensuring global food security, particularly amid growing environmental challenges such as climate change. Although deep learning (DL) methods ...
wqad

Record corn crop predictions could mean less profit for farmers in Iowa and Illinois

MOLINE, Ill. — The latest corn harvest numbers could be a concern for farmers. The U.S. Department of Agriculture's latest World Agricultural Supply and Demand Estimate (WASDE) predicted a record corn ...
Frontiers

Precision agriculture for improving crop yield predictions: a literature review

1 Department of Biotechnology, Institute of Applied Sciences & Humanities, GLA University, Mathura, Uttar Pradesh, India 2 Department of Environmental Management, Institute of Environmental ...
IEEE

Data-Driven Approaches for Crop Yield Prediction Using Machine Learning Techniques

Abstract: Sustainable development of agriculture along with food safety and precise resource handling depends on correct crop yield prediction. Traditionally yielded forecast systems find it ...