Opportunities and challenges in phenotyping row crops using drone‐based RGB imaging. Issue 1 (30th May 2022)

• Record Type: Journal Article
• Authors: Sweet, Dorothy D.; Tirado, Sara B.; Springer, Nathan M.; Hirsch, Candice N.; Hirsch, Cory D.
• Is Part Of: Plant phenome journal. Volume 5:Issue 1(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-05-30
• Subjects: Phenotype -- Periodicals; Plant genetics -- Periodicals; Periodicals; 581.35
• DOI: 10.1002/ppj2.20044
• Languages: English
• ISSNs: 2578-2703

Abstract

Abstract: Developing the resilient crops of the future will require access to a broad set of tools. While advances in sequencing and marker technologies have facilitated marker‐trait associations and the ability to predict the phenotype of an individual from its genotypic information, other tools such as high‐throughput phenotyping are still in their infancy. Advances in sensors, aeronautics, and computing have enabled progress. Here, we review current platforms and sensors available for top‐down field phenotyping with a focus on unoccupied aerial vehicles (UAVs) and red, green, blue sensors. We also review the ability and effectiveness of extracting traits from images captured using combinations of these platforms and sensors. Improvements in trait standardization and extraction software are expected to increase the use of high‐throughput phenotyping in the coming years and further facilitate crop improvement. Core Ideas: High throughput phenotyping is an area of active development. Aerial imagery from drones allows for high spatial, temporal, and potentially spectral resolution. Variability in ability and effectiveness of extracting traits from images from different platforms and sensors are reviewed.