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GRiSPIntegrating physiology, Crop
Modeling and Geneticsto Tackle Thermal
Stresses inRice:
The RIDEV Approach
Michael Dingkuhn (IRRI/CIRAD)Cecile Julia (Ph.D. 2012, Montpellier)
Richard Pasco (IRRI)Jean-Christophe Soulie (CIRAD)
funded by GEZ, AfricaRice, CCAFS and CIRAD
GRiSP Topics
� Thermal factors affecting rice production
� History: Sahel irrigated rice and the 1st RIDEV tool
� New aspects: Transpiration cooling and TOA
� A multi-environment study on rice microclimate
� Modeling micro-climate based phenology and sterility with RIDEV V.2
� Applications of RIDEV V.2
� Mapping of thermal risks
� Heuristic phenotyping of phenology and thermal sterility
� Outlook
GRiSP Rationale
� Thermal adaptation is fundamental for agro-ecological fit and fitness
� CC is changing thermal environments
� Rice as species has diverse thermal adaptation, but broadly adapted genotypes are rare
� Accuracy of crop models is still poor re. thermal effects
� We need…
� Better predictive tools to map CC impact
� Better understanding of adaptive traits
GRiSP
Micro-climateWeather
Some thermal factors affecting rice production
Pheno-logy
Yield potential
canopy architecture
Ta Tmer
YieldT
pan
TOA
Resources
=> A, R
PP
RH
Rs
Genetic constitution:- Pollen production- Physiol. tolerance
Studied hereNot studied here
Spikeletsterility
GRiSP
India NARES
Research Landscape
IRRI
AfricaRice
CIRAD
NIAES
Hohen-heim
ORYTAGECrop model assisted
phenotyping
RISOCASCrop-climate intercations
GRiSPPhenotypingNetwork
IM2PACT projectRadiation balance modeling, CO2 interaction
1990s RIDEV project : Physiology & decision aid tools
Jagadish’s networks
GRiSP
History
Sahel irrigated rice and the1st RIDEV tool
GRiSPHistory 1 (WARDA 1990s): Thermal constraints to irrigated rice in Senegal
Sowing date vs. crop duration and sterility
⇒ Thermal and photoperiod effects on phenology⇒ Chilling causes spikelet sterility
Days to flowering
% sterility % sterility
Tw(min) at bootingSowing dateSowing date
GRiSP
8
BVP
PSP
REP
Filling
germ
PI
F
mat
Ta pollination
TwMicro-spore-genesis
PPphenology
T-sensitive phases
Taphenology
Twphenology
=> Water temperature governs phenologyand chilling-induced sterility in flooded rice
Tw(max)
History 2: basis of 1995 RIDEV
GRiSP
Sterility probability 1950-1982
History 3: Risk analysis with RIDEV / crop calendar s
Saint-Louis
Rosso
Matam
Tillaberi
Sterility(heat)
Sterility(cold)
Sowing date
% Sterility
1 year
GRiSP
Zoning of latest possible sowing date for Sahel wet se ason irrigated rice crop
History 4: Mapping sterility risks with RIDEV
GRiSP New study on rice phenology and sterility responses to T
(Thesis of Cecile Julia)
� Emphasis on microclimate� Meristem T for phenology
� Floodwater T for chilling stress at microspore stage
� Panicle T for heat stress at anthesis
� Time of day of anthesis (TOA)
� Towards a new RIDEV
� Funding: GEZ (Risocas project) and ARC (modeling research at IRRI)
GRiSP
BVP PSP Reproductive Maturation
PI
Panicle T at anthesis=> Heat sterility
Water tmin=> Cold sterility
Canopy T=> Poor panicle exertion=> Sterility
Day length
TOA
Development ratefn(thermal time)
Apex is below water line
Apex
emerges Apex at top of canopy
GRiSP
Date01/08 11/08 21/08 31/08 10/09 20/09 30/09
Tem
pera
ture
(°C
)
8
12
16
20
24
28
32
36
40
44
Date
01/03 11/03 21/03 31/03 10/04 20/04 30/04
Tem
pera
ture
(°C
)
8
12
16
20
24
28
32
36
40
44
Tair Max Tair Min Twater max Twater min
Date
15/01 25/01 04/02 14/02 24/02 06/03 16/03 26/03
Tem
pera
ture
(°C
)
8
12
16
20
24
28
32
36
40
44
Date10/05 20/05 30/05 09/06 19/06
Tem
pera
ture
(°C
)
8
12
16
20
24
28
32
36
40
44
France - Temperate Summer 2009
VP
D (
KP
a)
012345
Senegal - Cold and dry season 2010
VP
D (
KP
a)
012345
Senegal - Hot and dry season 2010
VP
D (
KP
a)
012345
Philippines - Hot and dry season 2009
VP
D (
KP
a)
012345
Thesis study:(Cecile Julia)
4 genotypesIR64IR72Sahel108Chomrong(N22 failed)
4 environments
DS PhilippinesHDS SenegalCDS SenegalTemp. summer France
Traits observedPhenologyTOAPanicle Tr cooling
GRiSP
Mean Ta(min) during last 7d before anthesis ( oC)
Time of day of anthesisshows adaptive plasticity
Warm nights advance TOA => Escape midday heat
Humid days advance TOA => escape heat caused by absence of transpiration cooling
Results
GRiSP
20
22
24
26
28
30
32
34
36
38
40
0 20 40 60 80 100 120 140 160 180 200
Hou
rly a
vera
ge T
(°
C)
Position from the ground (cm)
(a)
inside canopy
above
canopypanicle layer
28/05/2010Water
7:00
8:00
9:00
10:00
11:00
12:00
13:00
Time
25
26
27
28
29
30
31
32
33
34
0 20 40 60 80 100 120 140 160 180 200
Hou
rly a
vera
ge T
(°
C)
Position from the ground (cm)
(b)
inside
canopy
above
canopy
panicle layer
16/04/2009Water
7:00
8:00
9:00
10:00
11:00
12:00
13:00
Time
Microclimate in IR64 canopy: Examples of sunny days
Senegal, hot-dry season Philippines, dry-season
GRiSPPan1
Pan2
Flagleaf1
Flagleaf2
Pan3
Pan4
Flagleaf3
Flagleaf4
Leaf5
Ca. 4900 IR observations on in-situ panicle TMicroclimate recordingAgronomic observations incl. %sterility
Panicle temperature
GRiSP
y = 1.66x - 1.31R² = 0.70
-4
-2
0
2
4
6
8
10
12
14
0 1 2 3 4 5 6 7
TD
=Ta-
Tp
( °C
)
VPD (kPa)
b
y = 1.45x - 0.99R² = 0.79
-4
-2
0
2
4
6
8
10
12
14
0 1 2 3 4 5 6 7
TD
=Ta-
Tp
( °C
)
VPD (kPa)
cy = 2.07x - 0.59R² = 0.15
-4
-2
0
2
4
6
8
0.5 1.0 1.5 2.0
TD
=Ta-
Tp
( °C
)
VPD (kPa)
a
Panicle-air temperature difference
y = 2.07x -0.59
R² = 0.15
-4
-2
0
2
4
6
8
0.5 1.0 1.5 2.0
TD
=Ta-
Tp
( °C
)
VPD (kPa)
a
Philippines Senegal hot-dry season Senegal cool-dry s eason
GRiSP
TD (predicted) [°C]
-4 -2 0 2 4 6 8 10 12 14
TD
(ob
serv
ed)
[°C
]
-4
-2
0
2
4
6
8
10
12
14
Senegal cool-dryseasonSenegal hot-dryseasonFrance summer
1:1
Multiple regression model predicting TD from…VPD, Rs, Ta, Sun angle, and Panicle height from groundTD1 = -1.578 + 1.093*VPD+0.189*Tair - 3.367E-02*TopP-3.99E-03*Rs + 3.31E-02*Hdeg
Panicle-air temperature difference (=>RIDEV): Regression model adopted for simulation
GRiSPy = 0.56x - 0.70
R² = 0.72
-15
-10
-5
0
5-15 -5 5
Tp-
Ta o
bsev
ed (°
C)
Tp-Ta calculated ( °C)
CHOMRONG
IM2PACTcalc vs…
y = 0.86x - 0.56R² = 0.76
-15
-10
-5
0
5-15 -5 5
Tp-
Ta o
bsev
ed (°
C)
Tp-Ta calculated ( °C)
CHOMRONG
RIDEVcalc vs…
y = 0.74x - 1.14R² = 0.83
-15
-10
-5
0
5-15 -5 5
Tp-
Ta o
bsev
ed (°
C)IR64
IM2PACTcalc vs…
y = 1.05x - 0.06R² = 0.87
-15
-10
-5
0
5-15 -5 5
Tp-
Ta o
bsev
ed (°
C)IR64
RIDEVcalc vs…
y = 1.13x + 0.20R² = 0.81
-15
-10
-5
0
5
-15 -5 5 Tp-
Ta o
bsev
ed (°
C)
Tp-Ta calculated ( °C)
Sahel 108
RIDEVcalc vs…
y = 0.77x - 1.07R² = 0.74
-15
-10
-5
0
5
-15 -5 5 Tp-
Ta o
bsev
ed (°
C)
Tp-Ta calculated ( °C)
Sahel 108
IM2PACTcalc vs…
RIDEV vs.
IM2PACT(Tsukuba, field-
calibrated in Japan)
GRiSP
22
24
26
28
30
32
PHIL_DS SEN_HS SEN_CS FR_HS
Tem
pera
ture
(°
C)
Site
(b)
Air and Panicle Temperature at TOA (calculated)
22
24
26
28
30
32
Chomrong IR64 IR72 S108
Tem
pera
ture
(°
C)
Variety
(a)
Site means
Genotype means
GRiSP
Disaggregation of observed sterility into its components
- Incomplete panicle exertion- Chilling at microspore stage- Heat at anthesis (TOA)
GRiSP
40
60
80
100
120
140
160
PHIL_DS SEN_HS SEN_CS FR_HS
Pan
icle
exs
ertio
n (%
)
Site
Chomrong IR64 S108
IR72 Last grain Neck node
(b)
Panicle exertion at flowering
0
10
20
30
40
50
60
70
80
90
100
PHIL_DS SEN_HS SEN_CS FR_HS
Ste
rility
(%
)
Site
(c)
Chomrong IR64 S108 IR72
Spikelet sterility Incomplete panicle exertion- occurred in cold-night environments- explained some of observed sterility
Observed spikelet sterility
GRiSP
0
10
20
30
40
50
60
70
80
90
100
12 14 16 18 20 22 24 26 28
Ste
rility
(%
)
Tw(min) at microspore stage ( °C)
Phil-ds Sen-hs
Sen-cs Fr-hs
Chomrong
Chilling effect at microspore stage on sterility
GRiSP Heat effect at anthesis on sterility
GRiSPConclusions of experimental study
(Thesis C. Julia)
Reproductive-stage adaptations to thermal stresses:
� Tolerance� Pollen viability under heat/cold (anti-oxidants? OA ?
Membrane & protein properties?)
� Avoidance� Transpiration cooling of panicle� Good panicle exertion (long peduncle)
� Escape� Time of day of anthesis (TOA)� Adaptive plasticity of TOA
� Temporal spread of anthesis (e.g., 2 wk)
Heat stress more likely in warm -humid than hot-dry climates!
GRiSP
Modeling with RIDEV
GRiSP
BVP PSP Reproductive Maturation
PI
Panicle T at anthesis=> Heat sterility
Water tmin=> Cold sterility
Canopy T=> Poor panicle exertion=> Sterility
Day length
TOA
Development ratefn(thermal time)
Apex is below water line
Apex
emerges Apex at top of canopy
Processes considered
in RIDEV
GRiSP RIDEV, new tool for crop -model assisted phenomics
� Simulator of…� Phenology incl. microclimate & PP effects� Sensitive phases to T of reproductive processes� G and E effects on TOA� Sterility caused by…
� Chilling effects on microsporogenesis (water Tmin)� Chilling effects on panicle exertion (air Tmin)� Heat effects on pollination (Tpanicle at anthesis)
� Prediction (forward mode)� CC impact mapping, plant type optimization� Agronomy (optimize genotype and crop calendar; risk studies)
� Heuristic parameterization of genotypes (reverse mo de)� Phenomics (extraction of genotypic parameter values from
experimental data)
GRiSP RIDEV Interface for point simulationsHTP Optimization of genotypic parameters by R-Genoud (genetic algo) against observation file (heuristics):
- Tbase, Topt- Duration BVP & Matu- PP-sensitivity (4 models)- crit. T Cold1, Cold2, Heat
Programming languages: C++, R
GRiSP
Spi
kele
t ste
rility
(to
tal,
as fr
actio
n)
0.0
0.2
0.4
0.6
0.8
1.0Total sterility (sim.)Total sterility (obs., ORYTAGE)Total sterility (obs., thesis Stuerz)
Error bars = SE (ORYTAGE data)
cv. Sahel 108, Ndiaye, Senegal
Cro
p du
ratio
n (d
)
40
60
80
100
120
140
160Flowering (sim.)Maturity (sim.)Flowering (obs., ORYTAGE)Flowering (obs., thesis Stuerz)Maturity(obs., ORYTAGE)Maturity (obs., thesis Stuerz)
Sowing date
Spi
kele
t ste
rility
(co
mpo
nent
s, a
s fr
actio
n)
0.0
0.2
0.4
0.6
0.8
1.0
SterCold1 (sim.)SterCold2 (sim.)SterHeat (sim.)
2008 2009 2010
2008 2009 2010
2008 2009 2010
Model parameters:Tbase = 10.6 oCTopt = 31.7 oCPPexp = 0.281PPsens = 1.032SumBvp = 748 oC.dSumRepr = 400 oC.d (preset)SumMatu = 409 oC.dCritSterCold1 = 10.6 oCCritSterCold2 = 18.7 oCCritSterHeat = 29,7 oCSterBase = 0.08 (=8%)
Example offitting RIDEV
-SAHEL 108- Many sowing dates- Different data sources
BUT: still problems with fitting some trad. cvs.
Observed duration to flowering (d)
60 80 100 120 140
Sim
ulat
ed d
urat
ion
to fl
ower
ing
(d)
60
80
100
120
Senegal
Y = 7.5 + 0.91X, R2 = 0.92Madagascar
GRiSP Issues
� Methodological (RIDEV)
� Phenology of some traditional cvs. is difficult to simulate (complex T x PP interaction?)
� More validation needed before extrapolation
� New scientific questions
� Trade-offs between water-saving and transpiration cooling (extend RIDEV to water limited situations)
� Transpiration cooling under high CO2?
� Genetics of heat avoidance (transpiration cooling) and escape (adaptive plasticity of TOA)
GRiSP Outlook (1)Use of RIDEV for Phenomics /GWAS
� Indica GWAS panel (200 acc., ORYTAGE project)
� Field-phenotyped for phenology and sterility in 12 en vironments:� 6 sowing dates in Senegal� 3 altitudes x 2 years in Madagascar
� Extraction of genotypic response parameters across environments:� Cardinal temperatures Tb and To� Thermal duration of phenological phases� PP-sensitivity� Chilling sensitivity of microsporogenesis� Chilling sensitivity of panicle exertion� Heat sensitivity of anthesis
� Association study using 700K Oryza SNP chip
GRiSPAPO 91-385 DA5 JAMAJIGI PA TOU HUNG TAICHUNG NATIVE 1 WAB 706-3-4-K4-KB-1
ASD 1 93-11 DA9 JC120 PAPPAKU TAMCAU 9 AWAS105-B-IDSA-B-WAS2-1-FKR-1
AZUCENA ADNY 11 DANAU LAUT TAWAR JC91 PATIK TELIMANI WAS169-B-B-4-2-1BASMATI 370 AI CHIAO HONG DE ABRIL JENGAR PEH KUH TELOVOLANA 177 WAS170-B-B-1-1BULU PANDAK ANGIFOTSY 685 DHOLA AMAN KALILA MENA PEH KUH TSAO TU TETEP WAS173-B-B-6-2-2DOM SOFID APURA DOURADO AGULHA KALINGA III PELITA JANGGUT THAPACHINIYA WAS174-B-3-5DULAR ARANG DR92 KARKATI 87 PETA THIERNO BANDE WAS181-B-6-3FANDRAPOTSY 104 B2997C-TB-4-2-2-1 FEDEARROZ 2000 KASALATH PIN TAWNG TOKAMBANY 663 WAS182-B-1-1FR13A B6144-MR-6-0-0 FEDEARROZ 50 KATI POKKALI TOKAMBANY 669 WAS183-B-6-2-3WAS 33 B-B BADKALAMKATI GAJPATI KAW LUYOENG POKKALI TSAKA WAS194-B-3-2-5GIZA 171 BAGUAMON 14 GAMBIAKA KOKOUM KHAO HAWM POPOT TSIPALA 1231 WAS197-B-6-3-11IAC 165 BALA GIE 57 KIANG CHOU CHIU PTB 25 TSIPALA B160 WAS198-B-3-1-3IR64 BENGALY 389 GOCHI BORO KITRANA 1890 PURBIA TSIPALA FOTSY 1883 WAS199-B-1-2-1KAUKKYI ANI BETSILAIZINA GOPAL KITRANA 508 RATHAL 2 TSIPALA MENA 626 WAS200-B-B-1-1-1KHAO DAM BG90-2 GUAN YIN TSAN KOGONI 91-1 RATHUWEE UPL RI-5 WAS202-B-B-1-1-2KHAO DAWK MALI 105 BH2 GWA NGASEIN LAITRA RAY JAZAYKAYZ UPL RI-7 WAS203-B-B-2-4-1M 202 BODOMANO H15-23-DA LAL AMAN RAY NABJA VANDANA WAS206-B-B-2-2-1
MOROBEREKAN BOTOHAVANA 139 HASAN SERAI LATSIBOZAKA-112-1 ROJOFOTSY 693VARY LAVA DE MAROVATO WAS207-B-B-3-1-1
N 22 BOTOHAVANA B13 IM 16 LOHAMBITRO 224 ROJOKELY VARY MADINIKA 3494 WAS208-B-B-5-1-1-3NIPPONBARE BOTRA MAITSO IR1561-228-3-3 MACAN BINUNDOK ROJOMENA 1034 VARY VATO 154 WAS20-B-B-1-2-2TEQUING BOTRIKELY IR19746-28-2-2 MADINIKA 1329 ROJOMENA B48 VARY VATO 462 WAS21-B-B-20-4-3-3
BOTRY 731 IR20 MAKALIOKA 34 RTS 12 VATO MATSOAMALONA WAS30-11-4-6-2-2-1BOUAKE 189 IR2006-P12-12-2-2 MALADY RTS 14 ZALCHA WAS33-B-B-15-1-4-5
Chromrong BR24 IR22 MAMORIAKA 114 RTS 4 ARC15872 WAS49-B-B-9-1-4-2
SAHEL 201 C21 IR2307-247-2-2-3MANGAVAVA FOTSILANSTSIKA 1177 RTS 5 ELONI WAS50-B-B-24-4-2-1
C4 63G IR2344-P1PB-9-3-2B MENAHODITRA 1234 S 624 WASSA WAS55-B-B-2-1-2-5CARREON IR28 MTU 9 SAHEL 108 WAY RAREM WAS57-B-B-3-1-4-6CERE AIR IR36 NAM ROO SAHEL 159 WAS62-B-B-17-1-1-3CHAU IR5 NAM SA GUI 19 SAHELIKA WAS63-22-5-9-10-1CHERIVIRUPPU IR50 NGAJA SALUMPIKITCHIEM CHANH IR52 NIONOKA SAMBALA MALOCHITRAJ IR53236-275-1 NONA BOKRA SAO
CICA 8 IR55411-50 O LUEN CHEUNG SATHI34-36
CT6510-24-1-2 IR55419-04 ORYZICA LLANOS 5 SEBERANG MR77IR57920-AC-25-2-B ORYZICA SABANA 10 SEBOTA 65IR57924-24 SHAI KUHIR60 SHORT GRAINIR62266-42-6-2 SINNA SITHIRA KALIIR72 SINTANE DIOFORIR74371-54-1-1 SOMCAU 70 AIR8 SOMIZY
SONASWARNA Indica panel (200)
ARC cvs.
IRRI cvs
Oryza SNP panel (all genetic groups)
A rich phenomics resource available for phenoloy & sterility:
- Madagascar: 3 altitudes x 2 yrs -Senegal: 6 sowing dates
⇒ RIDEV para optimization⇒ GWAS
GRiSP Outlook (2)Use of RIDEV for CC impact mapping and
agronomic decision support
� Joint global mapping of thermal risks with IRRI’s GIS group (A Nelson)
� CCAFS collaboration: Future climate scenarios
� RIDEV incorporation into Rice Manager for Africa
GRiSP
Thank youMerciSalamat po
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