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An Aerial Remote Sensing Platform for High Throughput Phenotyping of Genetic Resources

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Remote sensing –Beyond images
Mexico 14-15 December 2013

The workshop was organized by CIMMYT Global Conservation Agriculture Program (GCAP) and funded by the Bill & Melinda Gates Foundation (BMGF), the Mexican Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), the International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Maize, the Cereal System Initiative for South Asia (CSISA) and the Sustainable Modernization of the Traditional Agriculture (MasAgro)

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An Aerial Remote Sensing Platform for High Throughput Phenotyping of Genetic Resources

  1. 1. An Aerial Remote Sensing Platform for High Throughput Phenotyping of Genetic Resources Maize Physiology, (Zimbabwe) Wheat Physiology, (Mexico) CIMMYT Observing with “artificial eyes”
  2. 2. Remote sensing for field phenotyping at CIMMYT  Why do we need remote sensing? • • • • Non-intrusive measurements Coverage of large areas Accessibly Reduce error variance  Sensors • • • Ground-based: e.g. Thermal, Hyperspectral, Ground Penetrating Radar Airborne: Thermal, multispectral Space-borne: Multispectral  Remote Sensing for field phenotyping CIMMYT 1. Phenotyping: Drought, irrigation, low nitrogen 2. Field variability: 3. Stress Evaluation
  3. 3. Ground-based Remote Sensing for Field Phenotyping Spectroradiometer IR Thermometer Greenseeker Cossani et al, 2013 Weber et al. 2012; Zia et al. 2012; Cairns et al. 2012
  4. 4. Problems with hand-held measurements
  5. 5. Reducing field variability Increasing the “signal to noise” ratio should increase breeding efficiency Current methods to characterise field variability are too slow to be incorporated into the breeding pipeline Weber et al. 2012; Cairns et al. 2013; Prasanna et al. 2013;; Araus and Cairns, 2014
  6. 6. Airborne Remote Sensing Platform for High Throughput Phenotyping • • • • • • AB1100 helium filled blimp. Tethered. L8.0m, W3.1m. Payload approx 6 kg Max flight height 300 m. Max wind speed 13 m/s. • • • • • Astec Falcon 8, 8-rotar UAV. Remote controlled. 650 g payload. Max flight height approx 130 m. Max wind speed 10 m/s. • • Airelectronics Skywalker Autonomous flying
  7. 7. Airborne Remote Sensing Platform Platoform Instrument Specifications Helium Blimp Tetracam mini MCA 12 Channel Imaging Spectrometer • Tetracam ACD Light Multispectral Camera • ASTEC Falcon/Skywalker • • Resolution: 1280 x 1024 (1.3 megepixels) Spectral Range: 12 channels between 445-980 nm Resolution: 2048 x 1536 (3.1 megapixels) Spectral Range: 3 bands in Green, Red and NIR FLIR Tau 640 LWIR Uncooled Thermal Imaging Camera • ASTEC Falcon SONY NEX-5N Digital Camera • Resolution: 4588 x 3056 (14 megapixels) Skywalker Miricle 307 KS Thermal Camera • 640x480 detector resolution: (0.3 megapixels) and 25μm pitch KS ASTEC Falcon • Resolution: 640 x 512 (0.3 megapixels) Spectral Range: 7.5-13 μm
  8. 8. Airborne Remote Sensing Platform Physiological parameter Indices (from skywalker) Plant water use Canopy temperature Canopy conductance Canopy temperature Plant growth (biomass) NDVI Nutrient deficiency Senescence/color Collaboration with Crop Breeding Institute (Zimbabwe), University of Barcelona and CSIC
  9. 9. Airborne Remote Sensing Platform Field variability assessment: • Priority setting of trials • Incorporating variation into field design Crop status: • NDVI → green biomass → crop senescence • Reflectance → water content → chlorophyll content
  10. 10. Airborne VS Ground 0.80 0.80 r=-0.86 NDVI GROUND NDVI GROUND r=0.84 0.70 0.60 0.70 0.60 MSAVI BLIMP VS NDVI Ground Drought_1 0.50 0.50 0.60 0.70 NCPI BLIMP VS NDVI Ground Drought_1 0.50 0.10 0.80 0.75 0.30 NDVI BLIMP VS NDVI Ground Irrigation_1 0.70 0.65 0.75 PSND BLIMP VS NDVI Ground Irrigation_1 0.70 0.65 r=-0.91 r=-0.91 0.60 0.20 0.25 0.30 NDVI BLIMP 0.40 NCPI BLIMP NDVI GROUND NDVI GROUND MSAVI BLIMP 0.20 0.35 0.60 0.56 0.61 PSND BLIMP 0.66
  11. 11. Airborne VS Yield, Biomass NDVI Ground Trial CIMCOG_H_1 CIMCOG_H_2 SEED_SEL DIVERSITY SET FIGS NDVI UAV NDVI GROUND NDVI UAV NDVI GROUND NDVI UAV NDVI GROUND NDVI UAV NDVI GROUND NDVI UAV NDVI GROUND Trial Diversity_Set Thermal Index (UAV) Yield (g/m2) 0.85 0.77 0.63 0.79 0.74 0.67 0.43 0.64 0.63 0.60 0.58 0.89 0.82 0.71 0.90 CT Ground (oC) 0.59 Biomass (g/m2) -0.64 -0.60 -0.73 -0.78 -0.55 0.76 (oC) Yield (g/m2) -0.57 -0.56 CT Ground (oC) CIMCOG_H_1 Thermal Index (UAV) CT Ground Biomass (g/m2) 0.79 0.58 0.72 0.64 0.76 0.66 0.69 0.66 -0.61 -0.74 -0.78 -0.62 -0.67 CIMCOG_H_2 Thermal Index (UAV) 0.73 CT Ground (oC)
  12. 12. Worldview-2 Satellite Imagery 8 band multispectral imagery + panchromatic image. 770 km altitude. 46 cm panchromatic (single band) spatial resolution + 1.85 cm multispectral spatial resolution Pan-sharpened multispectral WV-2 satellite image. 8.5 x 2.4 m plots Multispectral UAV image
  13. 13. Worldview-2 Satellite Imagery Pansharpened multispectral image (46 cm spatial resolution) applied to large-plot trial (8.5 x 2.4 m) to derive NDVI. Although at high spatial resolution, still too coarse to be applied to small plots (approx 2m x 0.8 m) UAV Multispectral Camera Satellite Imagery
  14. 14. Conclusion  Airborne remote sensing can be used for non-destructive screening of plant physiological properties over large areas.  Enough resolution to obtain information at plot level while being able to measure several hundred plots with one take.  Potential to be used as selection tool for breeders (e.g. CT, spectral indices); avoiding time and costs involved with harvesting to increasing breeding efficiency. Yield distribution of 3 years mean drought trials (Cd Obregon, Mexico) 45 40 35 Conventional crosses 25 20 15 Physiological trait crosses 10 5 % of check <1 20 % 11 5% <= <1 15 % 11 0% <= <1 10 % 10 5% <= <1 05 % 10 0% <= <1 00 % 95 % <= <9 5% <= 90 % <= 90 % 0 85 % % 30
  15. 15. THANKS 

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