High-throughput phenotyping (HTP) using unmanned aerial vehicles is a valuable approach to accelerate the collection of phenotypic data in large field trials. Our primary objective was to investigate the differences between early (EF) and late (LF) sugarcane flowering time groups in an association mapping panel based on vegetation indices (VI), such as canopy cover (CC), excess greenness (EXG), plant volume and plant height obtained from RGB images, and stalk number by manual counting.