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

Artificial intelligence is quietly reshaping how crops are bred, and the biggest gains may come not in corn or wheat but in ...

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 ...

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 ...

1 Rice Research Institute, Guangdong Academy of Agricultural Sciences/Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China (Co-construction by Ministry and Province), ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

Abstract: The backbone of India's economy is Agriculture. There is an increased requirement to predict the future crop yield to match the crop demands. Farmers want to know which crop to plant and ...

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 ...