TY - GEN
T1 - Small plot identification from video streams for high-throughput phenotyping of large breeding populations with unmanned aerial systems
AU - Wang, Xu
AU - Amos, Cameron
AU - Lucas, Mark
AU - Williams, Grant
AU - Poland, Jesse
N1 - Generated from Scopus record by KAUST IRTS on 2022-09-13
PY - 2019/1/1
Y1 - 2019/1/1
N2 - In breeding and genetics programs, thousands of small plots in the size of a few square meters each having a unique genetic entry, are used to evaluate huge numbers of candidates and large mapping populations. Low-altitude remote sensing with unmanned aerial systems (UAS) can generate high geospatial resolution measurements of plants and enable high temporal resolution measurements through multiple crop growth stages. However, to identify individual plot from aerial images robustly and automatically becomes a key challenge in high throughput phenotyping (HTP) using UAS. In this case study, we captured super high-resolution video clips of wheat canopies by a UAS at low altitude. We proposed an image processing pipeline for identifying individual plot from video frames. Preliminary results indicate the methods can highly accelerate the process of linking genotypes to individual plot images and can be fully automated. This research provides a proof-of-concept and has broad implications of novel phenomics application of UAS that is scalable to tens-of-thousands of plots in crop breeding and genetic studies.
AB - In breeding and genetics programs, thousands of small plots in the size of a few square meters each having a unique genetic entry, are used to evaluate huge numbers of candidates and large mapping populations. Low-altitude remote sensing with unmanned aerial systems (UAS) can generate high geospatial resolution measurements of plants and enable high temporal resolution measurements through multiple crop growth stages. However, to identify individual plot from aerial images robustly and automatically becomes a key challenge in high throughput phenotyping (HTP) using UAS. In this case study, we captured super high-resolution video clips of wheat canopies by a UAS at low altitude. We proposed an image processing pipeline for identifying individual plot from video frames. Preliminary results indicate the methods can highly accelerate the process of linking genotypes to individual plot images and can be fully automated. This research provides a proof-of-concept and has broad implications of novel phenomics application of UAS that is scalable to tens-of-thousands of plots in crop breeding and genetic studies.
UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11008/2518532/Small-plot-identification-from-video-streams-for-high-throughput-phenotyping/10.1117/12.2518532.full
UR - http://www.scopus.com/inward/record.url?scp=85072631313&partnerID=8YFLogxK
U2 - 10.1117/12.2518532
DO - 10.1117/12.2518532
M3 - Conference contribution
SN - 9781510626812
BT - Proceedings of SPIE - The International Society for Optical Engineering
PB - [email protected]
ER -