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 ...
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 ...
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 ...
Accurate almond yield prediction is essential for supporting decision-making across multiple scales, from individual growers to international markets. This is crucial in the Mediterranean region, ...
Monoclonal antibody (mAb) manufacturing must continually improve to keep up with increasing demands. To do this, biomanufacturers can deploy machine learning tools to augment traditional process ...
Alerian MLP ETF (AMLP) holds energy infrastructure MLPs that earn through fee-based long-term contracts. The ETF pays an 8.22% dividend yield. Invesco KBW Premium Yield Equity REIT ETF (KBWY) offers a ...
Abstract: Predicting crop yields accurately is essential to improve agricultural planning, maximize resource allocation, and ensure food security. Predictive models can help farmers and policymakers ...
Your harvest data can be a treasure trove of information. However, without the proper approach, all that data can be overwhelming and a jumbled mess. Whether you have corn yield data or soybean yield ...
1 Department of Biotechnology, Institute of Applied Sciences & Humanities, GLA University, Mathura, Uttar Pradesh, India 2 Department of Environmental Management, Institute of Environmental ...
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