Crop Rotation

Crop rotation, the practice of planting different crops in a planned sequence on the same land, is being intensely studied to optimize agricultural yields and sustainability. Current research focuses on leveraging diverse data sources, including satellite imagery and farmer-reported crop rotations, with advanced machine learning models like deep learning architectures and YOLOv5, to improve crop classification accuracy and predict the impact of rotation practices on productivity. These advancements offer the potential for more precise agricultural management, enabling targeted interventions to enhance efficiency and resilience in the face of climate change and pest pressures.