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Rice: Phenotyping for drought traits
Amelia Henry
Rice Drought Phenotyping objectives:
1. Large-scale screening of breeding lines
2. Characterization of diversity panels for association
mapping
3. Dissection of drought tolerance mechanisms in major
drought QTL lines
1. Ensure uniformity
in stress treatment
and characterize the
drought stress
2. Phenotyping
High throughput methods →detailed
methods
Sequence for drought phenotyping
Uniform drought stress treatment:
• use level fields
•separate the drought stress from flooded fields
•avoid areas of high soil variability
Soil mapping based on apparent electrical conductivity
Characterizing the severity of the drought stress
Volumetric soil water content
with depth
tensiometers
water table tubes (piezometers)
• rainfall
• water table depth
• soil moisture status
Characterization of drought at partner sites
Rajshahi, Bangladesh
• tensiometers
• soil analysis
• water retention curves
Large-scale phenotyping of breeding lines
Traits
1. Yield
• Plant height
• Time to flowering
• Shoot biomass/ harvest index
Aus lines 2010DS and 2011DS
220+ lines
Stress and control
• Early vigor
• Canopy temp
• NDVI
• Yield
• shoot and root biomass
Phenotyping of association panels
Greenhouse lysimeter facility
Capacity:
1200 cylinders
Throughput:
250 plants / day
Canopy reflectance
Normalized Difference Vegetation Index
NDVI = (NIR_reflected -Red_reflected)
(NIR_reflected + Red_reflected)
Soil-Adjusted Vegetation Index
SAVI = 1.5 * (NIR_reflected - Red_reflected)
(NIR_reflected + Red_reflected * 0.5)
If some genotypes show better water uptake when the soil is dry, we look
for root-related mechanisms
Canopy temperature
Root sampling in the field
Throughput: roots from about 100 soil cores sampled, washed, and
scanned within 2 weeks
Detailed measurements
Leaf gas exchange
Leaf water potential
Root hydraulic conductance
Microscopy
Screening of advanced breeding lines by India Drought Breeding Network
Hazaribag April 26 2011 2:45 PM
22.5
22.7
22.9
23.1
23.3
23.5
23.7
IR
83376-B-B-130-3
IR74371-54-1-1
IR
83377-B-B-48-3
IR
83380-B-B-124-3
IR
83387-B-B-110-1
IR
83383-B-B-141-2
IR
83388-B-B-108-3
IR
83387-B-B-27-4
IR
83383-B-B-141-4
IR64
IR74371-70-1-1
CanopyTemp(C)
IRT.
Canopy Temperature
Sonic sensor
Plant Height
Crop Circle Multispectral Sensor
Biomass, Development, Nutrient, Stress Response
NDVI, PRI, RI, TCARI, OSAVI, WDVI...
24 m boom
RTK GPS Auto Steer
+/- 2 cm accuracy
CR1000 data logger & AM16 multiplexor
Sensor control and data processing
PAR/Pyranometer T/RH
Ambient Monitoring
Fixed IRT
Plant Ref
Unplanted
Check
Reference
Crop Circle– 3 band multispectral sensor with dedicated logger
Plant IRT and sonic Ht data processing on CS logger
Ambient PAR, SW, T/RH, and soil T on CS logger
Reference plots to monitor temporal variability
Check plots to monitor spatial variability
Unplanted plots to monitor soil background
8 – 16 plot system
Example 1 m wide plots
linearconical
Sensor Measurement
Field of View
SpectraIIRT/sonic
Ambient
PAR, SW, and T/RH Sensor
IRT
Soil Ref
On our wish list:
Mobile field-based
phenotyping
platform
Dissection of drought tolerance mechanisms in major drought
QTL lines: Aday Sel x IR64 NILs
+QTL
14-1-2-10
-QTL
14-1-2-13
IR64
-QTL
14-1-2-13
+QTL
14-1-2-10
Aday Sel NIL pairs show large differences in canopy temp under severe drought
+QTL
5-6-18
-QTL
5-6-11
Aday Sel
Aday Sel NIL pairs did not show large differences in root length density at depth
Expt 4s Aday Sel ROS
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
IR 64 IR77298-14-1-2-
10
IR77298-14-1-2-
13
IR 77298-5-6-18 IR77298-5-6-11
RLD(cmcm-3
)
30-45 cm
45-60 cm
+ QTL - QTL + QTL - QTL
Root function for water uptake: hydraulic conductance
IR
64
IR
77298-14-1-2-10
(+)IR
77298-14-1-2-13
(-)IR
77298-5-6-18
(+)IR
77298-5-6-11
(-)
logSapfluxat500kPa(m
3
s
-1
)
1e-12
1e-11
1e-10
1e-9
well-watered control
dry-down from field capacity
dry-down from 75% field capacity
Lower Lpr in + QTL lines
from Aday Sel x IR64
14-1-2-10 (+ QTL) 14-1-2-13 (- QTL)
+ QTL lines had smaller root and xylem vessel diameters
Hypothesis: smaller xylem vessel diameters in +QTL lines result in decreased
xylem cavitation under severe stress
Summary for rice drought phenotyping:
1. Use a uniform field and characterize the type of drought stress
2. Phenotyping for drought breeding: focus on yield
3. Phenotyping for physiology: start at high throughput (NDVI and
canopy temp)
 More detailed methods
Acknowledgements:
IRRI Drought Physiology Group
Generation Challenge Program
Gates Foundation (STRASA project)
Ken McNally
Arvind Kumar

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Rice Phenotyping for Drought Traits

  • 1. Rice: Phenotyping for drought traits Amelia Henry
  • 2. Rice Drought Phenotyping objectives: 1. Large-scale screening of breeding lines 2. Characterization of diversity panels for association mapping 3. Dissection of drought tolerance mechanisms in major drought QTL lines
  • 3. 1. Ensure uniformity in stress treatment and characterize the drought stress 2. Phenotyping High throughput methods →detailed methods Sequence for drought phenotyping
  • 4. Uniform drought stress treatment: • use level fields •separate the drought stress from flooded fields •avoid areas of high soil variability Soil mapping based on apparent electrical conductivity
  • 5. Characterizing the severity of the drought stress Volumetric soil water content with depth tensiometers water table tubes (piezometers) • rainfall • water table depth • soil moisture status
  • 6. Characterization of drought at partner sites Rajshahi, Bangladesh • tensiometers • soil analysis • water retention curves
  • 7. Large-scale phenotyping of breeding lines Traits 1. Yield • Plant height • Time to flowering • Shoot biomass/ harvest index
  • 8. Aus lines 2010DS and 2011DS 220+ lines Stress and control • Early vigor • Canopy temp • NDVI • Yield • shoot and root biomass Phenotyping of association panels
  • 9. Greenhouse lysimeter facility Capacity: 1200 cylinders Throughput: 250 plants / day
  • 10. Canopy reflectance Normalized Difference Vegetation Index NDVI = (NIR_reflected -Red_reflected) (NIR_reflected + Red_reflected) Soil-Adjusted Vegetation Index SAVI = 1.5 * (NIR_reflected - Red_reflected) (NIR_reflected + Red_reflected * 0.5)
  • 11. If some genotypes show better water uptake when the soil is dry, we look for root-related mechanisms Canopy temperature
  • 12. Root sampling in the field Throughput: roots from about 100 soil cores sampled, washed, and scanned within 2 weeks
  • 13. Detailed measurements Leaf gas exchange Leaf water potential Root hydraulic conductance Microscopy
  • 14. Screening of advanced breeding lines by India Drought Breeding Network Hazaribag April 26 2011 2:45 PM 22.5 22.7 22.9 23.1 23.3 23.5 23.7 IR 83376-B-B-130-3 IR74371-54-1-1 IR 83377-B-B-48-3 IR 83380-B-B-124-3 IR 83387-B-B-110-1 IR 83383-B-B-141-2 IR 83388-B-B-108-3 IR 83387-B-B-27-4 IR 83383-B-B-141-4 IR64 IR74371-70-1-1 CanopyTemp(C)
  • 15.
  • 16.
  • 17.
  • 18. IRT. Canopy Temperature Sonic sensor Plant Height Crop Circle Multispectral Sensor Biomass, Development, Nutrient, Stress Response NDVI, PRI, RI, TCARI, OSAVI, WDVI... 24 m boom RTK GPS Auto Steer +/- 2 cm accuracy CR1000 data logger & AM16 multiplexor Sensor control and data processing PAR/Pyranometer T/RH Ambient Monitoring Fixed IRT Plant Ref Unplanted Check Reference Crop Circle– 3 band multispectral sensor with dedicated logger Plant IRT and sonic Ht data processing on CS logger Ambient PAR, SW, T/RH, and soil T on CS logger Reference plots to monitor temporal variability Check plots to monitor spatial variability Unplanted plots to monitor soil background 8 – 16 plot system Example 1 m wide plots linearconical Sensor Measurement Field of View SpectraIIRT/sonic Ambient PAR, SW, and T/RH Sensor IRT Soil Ref On our wish list: Mobile field-based phenotyping platform
  • 19. Dissection of drought tolerance mechanisms in major drought QTL lines: Aday Sel x IR64 NILs +QTL 14-1-2-10 -QTL 14-1-2-13
  • 20. IR64 -QTL 14-1-2-13 +QTL 14-1-2-10 Aday Sel NIL pairs show large differences in canopy temp under severe drought +QTL 5-6-18 -QTL 5-6-11 Aday Sel
  • 21. Aday Sel NIL pairs did not show large differences in root length density at depth Expt 4s Aday Sel ROS 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 IR 64 IR77298-14-1-2- 10 IR77298-14-1-2- 13 IR 77298-5-6-18 IR77298-5-6-11 RLD(cmcm-3 ) 30-45 cm 45-60 cm + QTL - QTL + QTL - QTL
  • 22. Root function for water uptake: hydraulic conductance IR 64 IR 77298-14-1-2-10 (+)IR 77298-14-1-2-13 (-)IR 77298-5-6-18 (+)IR 77298-5-6-11 (-) logSapfluxat500kPa(m 3 s -1 ) 1e-12 1e-11 1e-10 1e-9 well-watered control dry-down from field capacity dry-down from 75% field capacity Lower Lpr in + QTL lines from Aday Sel x IR64
  • 23. 14-1-2-10 (+ QTL) 14-1-2-13 (- QTL) + QTL lines had smaller root and xylem vessel diameters Hypothesis: smaller xylem vessel diameters in +QTL lines result in decreased xylem cavitation under severe stress
  • 24. Summary for rice drought phenotyping: 1. Use a uniform field and characterize the type of drought stress 2. Phenotyping for drought breeding: focus on yield 3. Phenotyping for physiology: start at high throughput (NDVI and canopy temp)  More detailed methods
  • 25. Acknowledgements: IRRI Drought Physiology Group Generation Challenge Program Gates Foundation (STRASA project) Ken McNally Arvind Kumar