Accurately predicting complex agronomic traits remains a major bottleneck in crop breeding. This study demonstrates how optimized genomic prediction models can reliably forecast flowering time, yield ...

AI-driven platforms increasingly assist farmers in choosing when to plant, irrigate, fertilize, or harvest. These systems ...

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

By combining machine learning, robotics and analytics, farmers are gaining financial benefits by improving crop yields and ...

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 ...