352-3 Application of Unmanned Aerial Systems for High-Throughput Phenotyping in Wheat.

See more from this Division: C01 Crop Breeding & Genetics
See more from this Session: Symposium--Applications of UAV-Based Remote Sensing for Assessing Crop Stress

Wednesday, November 18, 2015: 9:05 AM
Minneapolis Convention Center, 101 A

Jesse Poland, Wheat Genetics Resource Center, Department of Plant Pathology and Department of Agronomy, Kansas State University, Manhattan, KS, Daljit Singh, Interdepertmental Genetics and Department of Plant Pathology, Kansas State University, Manhattan, KS, Atena Haghighattalab, Geography, Kansas State University, Manhattan, KS and Dale Schinstock, Department of Mechnical and Nuclear Engineering, Kansas State University, Manhattan, KS
Abstract:
We have developed and applied small unmanned aerial systems for image-based high-throughput phenotyping of wheat.  Over 100,000 plot level measurements of normalized difference vegetation index (NDVI) and plot-height have been taken on breeding nurseries over the current growing season.  An efficient pipeline for image processing is being implimented, along with novel algorithms for efficient extraction of plot level data.  Following characterization of simple vegetation indexes, this information is being incorporated to predict yield in breeding lines using multivariate models encompassing high-throughput phenotypes and genomic information.  Taken together, the merging of genomic prediction with novel high-throughput phenotyping has the power to greatly accelerate the breeding program through accurate predictions of early generation material.

See more from this Division: C01 Crop Breeding & Genetics
See more from this Session: Symposium--Applications of UAV-Based Remote Sensing for Assessing Crop Stress