Airborne Remote Sensing for High Throughput Phenotyping of Wheat
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| Title: | Main Title: Airborne Remote Sensing for High Throughput Phenotyping of Wheat |
| Description: | Abstract: High resolution remote sensing (RS) of light spectra reflected from plants allows for non-intrusive monitoring of physiological characteristics such as canopy temperature, hydration status, and pigment composition, as well as permitting estimates of agronomic traits such as biomass and yield. While satellite mounted RS platforms have proven efficient at measuring some of these characteristics at a field scale, their spatial resolution is too low for accurate data retrieval at plot level in a plant breeding context. While ground based remote sensing is used for predicting physiological and agronomic traits at a plot scale, temporal variations of environmental variables such as air temperature can introduce confounding factors especially when applied to large trials. Low level airborne remote sensing platform overcomes these restrictions, allowing for fast, non-destructive screening of plant physiological properties over large areas, with enough resolution to obtain information at plot level while being able to measure several hundred plots with one take. Sampling was performed with a helium filled tethered blimp and an 8 rotor unmanned aerial vehicle (UAV). Instruments mounted on the UAV alternate between a 3 channel multispectral imaging spectrometer and a thermal camera. A 12 channel multispectral camera was fixed on the tethered blimp. Flight altitude, between 50-100 m, was a function of the spatial resolution of the camera, wind speed and target plot lengths; ranging from 0.50-8.5 m. Multiple flights were conducted during the 2012 and 2013 cycles over experimental wheat trials. Images were corrected, geo-referenced where possible and processed to determine a data point for each plot within the trial. Aerial images collected were used to calculate a wide range of indices relating to temperature, vegetation, pigments, water status, and biomass. Indices derived from the airborne imagery data were validated by equivalent indices collected at ground level. Correlations between airborne data and yield/biomass at plot level proved to be similar or even better to the equivalent correlations using data collected from instruments on the ground. Results give confidence to the application of such airborne remote sensing techniques for high throughput phenotyping, in particular the ability to evaluate the level of stress and performance of thousands of genetic resources under extreme heat and drought conditions. |
| Identifier: | 10.5880/TR32DB.KGA94.17 (DOI) |
Responsible Party
| Creators: | Maria Tattaris (Author), Matthew Reynolds (Author), Julian Pietragalla (Author), Gemma Molero (Author), Mariano C. Cossani (Author), Marc Ellis (Author) |
| Contributors: | Juliane Bendig (Editor), Georg Bareth (Editor), Transregional Collaborative Research Centre 32 (Meteorological Institute, University of Bonn) (Data Manager), University of Cologne (Regional Computing Centre (RRZK)) (Hosting Institution) |
| Publisher: | Geographisches Institut der Universität zu Köln - Kölner Geographische Arbeiten |
| Publication Year: | 2014 |
Topic
| Subjects: | Keywords: UAV, Remote Sensing, NDVI, Canopy Temperature |
File Details
| Filename: | Tattaris_et_al_2013_KGA94.pdf |
| Data Type: | Text - Book Section |
| Sizes: | 12 Pages 1639 Kilobytes |
| File Size: | 1.6 MB |
| Date: | Issued: 10.06.2014 |
| Mime Type: | application/pdf |
| Language: | English |
Constraints
| Download Permission: | Free |
| Licence: | [TR32DB] Data policy agreement |
Geographic
Metadata Details
| Metadata Creator: | Constanze Curdt |
| Metadata Created: | 10.06.2014 |
| Metadata Last Updated: | 10.06.2014 |
| Subproject: | Z1 |
| Funding Phase: | 2 |
| Metadata Language: | English |
| Metadata Version: | V50 |
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| Page Visits: | 418 |
| Metadata Downloads: | 0 |
| Dataset Downloads: | 29 |
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