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Precision agriculture for SAT;Near future or unrealistic effort?
Jana Kholová and col.
ICRISAT
AuSoRGM- 22nd July - 2015
Overview
• Characterizing target environment
• Relevant phenotype for SAT
• Genetic determination of relevant phenotype
• HT-phenotyping
• Phenotype value
• System complexity & link to socio-economy
average yield
0
200
400
600
800
1000
1200
vegetative pre-flowering post-flowering post-flowering
relieved
mild stress
we
igh
ed
yie
ld (
kg
/ha
)
vegetative
pre-flowering
post-flowering
post-flowering relieved
mild stress
4. Relevant phenotype???
1. Target environments
Kholová et al. 2013 3. Impact on production
7%
18%
18% 17% 40%
major stress patterns
0
0.2
0.4
0.6
0.8
1
0 100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600
thermal time (oDay)
S/D
vegetative
pre-flowering
post-flowering
post-flowering relieved
mild
2. Environmental patterns
Grain Yield
Grain Number Grain Size & N
BiomassRADN
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 ofGxExM
Research concepts – relevant phenotyping
Focus on the“causal phenotype”
Relevant phenotype for SAT?Grain Yield
Grain Number Grain Size & N
BiomassRADN
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)
Gra
in Y
ield
(g p
lant-
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
-an
thes
is w
ater
use
Pre-anthesis water use (g plant-1)
constitutive WU defines
grain-filling underterminal drought
Pre-/post-anthesis water use
Vadez et al. 2012
Relevant phenotype for SAT?
Constitutive WU :
Grain Yield
Grain Number Grain Size & N
BiomassRADN
TE T RUE Rint
vpd
kl LAISLNRoots k
TN LNo
A >A
Vapor Pressure Deficit (VPD; kPa)Tra
nsp
irati
on
rate
(g
cm
-2h
-
1)0 2 4
0
1
LA conductivity
LA
Thermal time
& LA
Basic research onWU components Vadez et al. 2010-2015
Kholová et al. 2010-2014
Grain Yield
Grain Number Grain Size & N
BiomassRADN
TE T RUE Rint
vpd
kl LAISLNRoots k
TN LNo
A >A
Example: WU components – genetic determination
Effect of QTL depends on genetic background (stg 3A&B!)
R16 (senescent parent) + stg3A&3B QTLVPD response -> high TE
S35 (senescent parent) + stg3A&3B QTL
small leaves
Vadez et al. 2011
Stay-green ILs
Grain Yield
Grain Number Grain Size & N
BiomassRADN
TE T RUE Rint
vpd
kl LAISLNRoot
s
k
TN LNo
A >A
“causal phenotype”(HT-phenotyping)
“consequential phenotype”(High precision field trials)
No
. of lin
es p
hen
oty
ped
% o
f lines h
old
ing
desir
ed
p
hen
oty
pe
Phenotyping principle
Platforms linkage! LeasyScan
Lysimetry
Field
Value of phenotype? – in silico predictions
Environment
0
500
1000
1500
2000
2500
200 300 400 500 600 700 800
LA
(cm
2)
thermal time (degree days)
S35
7001
6008
6026
6040
6016
Canopy size
+ = $ ?
-1000
-800
-600
-400
-200
0
200
400
600
800
1000
0 500 1000 1500 2000 2500 3000
Gra
in y
ield
ga
in (
kg
ha
-1)
original grain yield (kg ha-1)
Smaller canopy
(low TPLAmax)
Grain
Pre-flowering
Flowering
Post-flowering
Post-flowering relieved
No stress
Model
Example: System complexity
Crop value = f(quantity + quality; socio-economic context)
Stay-green sorghum; grain quality
0
2
4
6
8
10
12
14
16
S35 7001 6008 6026 6040 6008 S35 7001 6026 6040
pro
tein
s(%
)
stay-green isolines
~ 20% QTL effect
Control Drought
?Price per unit of protein?
Link to socioeconomics
4
5
6
7
8
9
10
11
12
pro
tein
(%)
management
Drought
~ 15% management effect
Control
RESEARCH APPLICATIONConclusions; Structure of research
Value of traits(crop model & GxExM)
Genetic determination of phenotype
Environmental characterization& relevant traits
ideotypes & managementto regions
(precision Ag for SAT)
Breeding populations
Socio-economics
R4D requires multidisciplinarity!
• Bioinformatists• Technology developers• Physiologists• Breeders• Modelers• Socioeconomists• Nutritionists….
Thank youMissionTo reduce poverty, hunger, malnutrition and environmental degradation in the dryland tropics
