LeasyScan: A novel concept combining 3D imaging and lysimetry for hi-throughput phenotyping of traits controlling plant water budget
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LeasyScan: A novel concept combining 3D imaging and lysimetry for hi-throughput phenotyping of traits controlling plant water budget.
QUT2015 - 21 July 2015
LeasyScan: A novel concept combining 3D imaging and lysimetry for hi-throughput phenotyping of traits controlling plant water budget
LeasyScan:
a novel concept combining 3D imaging and
lysimetry for high-throughput phenotyping of
traits controlling plant water budget
Vincent Vadez – Jana Kholová et al. JXB 2015
ICRISAT
QUT – 21th July 2015
• ICRISAT is a non-profit, non-political, International Agricultural
Research Institute
• Established in 1972, operating with an annual budget of US$ 83
million (2013)
• Member of the Consultative Group on International Agricultural
Research (CGIAR)
• Our mandate crops: Sorghum, Pearl millet, Pigeon pea, Chick
pea & Groundnut
• To reduce poverty, hunger, malnutrition and
environmental degradation in dryland tropics
Our Mission
Grain Yield
Grain Number Grain Size & N
Biomass RADN
TE T RUE Rint
vpd
kl LAISLNRoots k
TN LNo
A >A
APSIM Generic Crop Template, from Graeme Hammer
Which ”phenotype” is linked to yield
improvement in target agro-ecology
(SAT – terminal drought)?
Yield is consequence of
GxExM
Research concepts – relevant phenotyping
Focus on the
“causal phenotype”
Biomass
& yield
Water&Nutrients
Lysimetric facility at ICRISAT
• Field-like
• Gravimetric - manual (WU, TE)
• Long term (3 Wks-maturity)
• Medium throughput (5000 PVCs/wk)
• Stress scenarios
Relevant phenotype?
Relevant phenotype for SAT?
Grain Yield
Grain Number Grain Size & N
Biomass
RADN
TE T RUE Rint
vpd
kl LAISLNRoots k
TN LNo
A >A
R² = 0.7108
0
4
8
12
16
20
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
WU 3 weeks after stress imposition (L plant-1)
GrainYield(gplant-1) Grain yield and water use
R² = 0.7436
0
2000
4000
6000
8000
10000
12000
0 2000 4000 6000 8000 10000 12000 14000 16000
Post-anthesiswateruse
Pre-anthesis water use (l plant-1)
constitutive WU
defines
grain-filling under
terminal drought
Pre-/post-anthesis water use
Vadez et al. 2012
Relevant phenotype for SAT?
Constitutive WU :
Grain Yield
Grain Number Grain Size & N
Biomass
RADN
TE T RUE Rint
vpd
kl LAISLNRoots k
TN LNo
A >A
Vapor Pressure Deficit (VPD; kPa)
Transpirationrate(gcm-2h-
1)
0 2 4
0
1
LA conductivity
LA Thermal time
& LA
Basic research on
WU componentsVadez et al. 2010-2015
Kholová et al. 2010-2014
• Outdoors – environment of growth matters
• Rapid access to canopy/water use at key time
• Early development defines crop success
• Rapid evaluation of environmental effects
(Soil moisture, VPD)
What HT-phenotyping platform?
LA scanner Leaf area development
scales
Water extraction dynamics
WU dynamics =LA x LA conductivity
[transpiration/LA]
Plant Eye prototypeTechnology testing
Pushing technology limits in outdoor environment
• Light, wind, plant structure
Development of hardware/software not trivial
• Reciprocal learning process
Selection of relevant data expressing canopy properties
y = 26.23x + 13346
R² = 0.8198
0
20000
40000
60000
80000
100000
120000
0 1000 2000 3000 4000
3Dleafarea(mm2)
Destructive LA (cm2)
LA extracted 4 h in the morning
peanut
y = 24.832x + 9606.3
R² = 0.9126
0
10000
20000
30000
40000
50000
60000
70000
80000
90000
100000
0 1000 2000 3000 4000
3Dleafarea(mm2)
Destructive LA (cm2)
LA extracted for whole day
Open canopy
during the day
Closed canopy
during the night
Which scans express whole canopy the best?
y = 34.002x + 3224.5
R² = 0.9206
0
20000
40000
60000
80000
100000
120000
140000
160000
0 1000 2000 3000 4000 5000
3DLA(mm2)
Destructive LA (cm2)
LA extracted at night
863B
H77/833-2
PRLT
Selection of relevant data expressing canopy properties
y = 30.876x + 6258.7
R² = 0.859
0
20000
40000
60000
80000
100000
120000
140000
160000
0 1000 2000 3000 4000 5000
3DLA(mm2)
Destructive LA (cm2)
LA extracted during morning
863B
H77/833-2
PRLT
Canopy
&
wind
Canopy
&
no wind
Which scans express whole canopy the best?
Rapid evaluation of environmental effects; e.g. NaCl treatment
Vadez et al. 2015
Hypothesis validation!
A1
A
B
Vadez et al. 2015
Testing the
production zone
adapted genotypes;
A1-severe drought
A-mild drought
B-rare drought
Genotypes vary
for drought
related
phenotype
Take-home message:
Phenotyping for the relevant traits
(assessing causes of drought adaptation rather than consequences!)
Phenotyping outdoors/environmental variables
(environment of development matters!)
Validation of technology & tech. development
(each crop/conditions are different – link to developers)
Bioinformatics
(learning of the best ways of working with massive datasets)
Phenotyping is a continuous learning process
HT-phenotyping - a way to precision agriculture!
Development requires multidisciplinarity!
• Technology developers & engineers
• Bioinformatists
• Physiologists
• Breeders
• Modelers
Thank you
Mission
To reduce poverty, hunger,
malnutrition and environmental
degradation in the dryland tropics