ABSTRACT
In the context of plant breeding, high-throughput phenotyping is an assessment of plant phenotypes on a scale and with a level of speed and precision not achievable with traditional methods, through the application of emerging technologies such as automation and robotics, new sensors, and imaging technologies (hardware and software). In the present work, high-resolution digital images have been acquired with an unmanned aerial vehicle (UAV) prototype platform on an experimental phenotyping barley field. Six vegetation indices generated from the red–green–blue and near-infrared-based images were calculated for 912 experimental barley plots and provided high correlation with the indices determined from hyperspectral data taken at the ground (gt); the indices performance in discriminating the vigour of genotypes was finally assessed.
Acknowledgements
The authors are grateful to Silvia Baronti, Carolina Vagnoli (IBIMET—CNR), Luigi Cattivelli, Renzo Alberici, Ivana Tagliaferri (CREA) for their support in the field experiment. Special thanks to Whealbi Project (Whealbi Citation2014) that funds the phenotyping experiment through the European Union’s Seventh Framework Programme (grant agreement n°FP7-613556).
Disclosure statement
No potential conflict of interest was reported by the authors.