A UAV-based system for monitoring crop growth in wheat, barley and triticale phenotyping field trials

This research evaluated the capability of an unmanned aerial vehicle (UAVs) –based system to monitor the plant heights of several wheat, barley and triticale field trials over time, by applying a customised object-based image analysis algorithm to the digital surface models created with the structure-from-motion technique. Comparisons between UAV-based and ground-based measurements over time reported an overall coefficient of determination (R2) of 0.917 and an average root mean square (RMS) error of 0.10 m. With a target of field phenotyping, a ranking of genotypes in term of plant heights and crop growth was accurately provided, which can facilitate the decision making process in cereal breeding programs.