High throughput prediction of sugar beet root weight and sugar content using UAV derived growth dynamics

A research team employed an RGB camera on an unmanned aerial vehicle (UAV) to collect time series data on sugar beet canopy coverage and height. This data was used to predict root weight and sugar content with high accuracy. This innovative technique enhances breeder decision-making by providing pre-harvest selection criteria, reducing manual measurement needs. The UAV-based approach can also guide precision fertilization in production fields, demonstrating its value in improving agricultural efficiency and crop yield predictions.