th2_integrating physiology, crop modeling and genetics
DESCRIPTION
3rd Africa Rice Congress Theme 2: Intensification and diversification Mini symposium: determinants of agricultural productivity in Africa’s rice-based systems Author: Dingkuhn et al.TRANSCRIPT
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GRiSPIntegrating Physiology, Crop
Modeling and Geneticsto Tackle Thermal
Stresses inRice:
The RIDEV Approach
Michael Dingkuhn (IRRI/CIRAD), Julie Mae Pasuquin
(IRRI), Cecile Julia (CIRAD), Richard Pasco (IRRI),
Jean-Christophe Soulie (CIRAD)
funded by GIZ, AfricaRice, CCAFS and CIRAD
Context of GRiSP Global Rice Phenotyping Network
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GRiSP Rationale
Thermal adaptation is fundamental for agro-ecological fit
Temperature governs rice phenology and spikelet fertility
Climate change is changing thermal environments
Accuracy of crop models is still poor re: thermal effects
We need…
Better predictive tools to map climate change impact
Better understanding of adaptive traits: Physiology & Genetics
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GRiSPHistory: The 1990s research at WARDA Thermal constraints to irrigated rice in Senegal
Effect of sowing date on 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
Þ 1995 development of RIDEV predicting phenology and thermal sterility as risk analysis and decision aide for cropping calendars
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GRiSPNew study on rice phenology and sterility responses to T
(Thesis of Cecile Julia & ongoing CIRAD/IRRI/CCAFS project)
Emphasis on microclimate Meristem T => phenology Floodwater T => chilling stress at microspore stage Panicle T => heat stress at anthesis Time of day of anthesis (TOA)
RIDEV v.2 to characterize genetic diversity
NEW
NEW
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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 T
empe
ratu
re (
°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
Scope of study:
4 genotypesIR64IR72Sahel108Chomrong(N22 failed)
4 environmentsDS PhilippinesHDS SenegalCDS SenegalTemp. summer France
Traits observedPhenologyTOAPanicle transp. cooling
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GRiSP Results
Mean air temp (min) during last 7d before anthesis (oC)
Time of day of anthesis (TOA) shows adaptive plasticity
Warm nights advance TOA => Escape from midday heat
Humid days advance TOA => Escape from heat caused by absence of transpiration cooling
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GRiSP
Pan1Pan2
Flagleaf1
Flagleaf2
Pan3
Pan4
Flagleaf3
Flagleaf4
Leaf5
ca. 4900 IR observations on in-situ panicle TMicroclimate recording% sterility observed at maturity
Panicle temperature: IR imagery in the field
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GRiSP
0 1 2 3 4 5 6 7-4
-2
0
2
4
6
8
10
12
14
f(x) = 1.45344554944651 x − 0.991079944085128R² = 0.790388621127665
c
VPD (kPa)
TD
=T
a-T
p (
°C)
Relative humidity or vapor pressure deficit is the main determinant of Ta-Tp difference
Example: Senegal cool-dry season
Panicle warmer than air
Panicle cooler than air
Humid Arid
TD (predicted) [°C]
-4 -2 0 2 4 6 8 10 12 14
TD
(ob
serve
d) [°C
]
-4
-2
0
2
4
6
8
10
12
14
Senegal cool-dryseasonSenegal hot-dryseasonFrance summer
1:1
Model prediction (sim:obs)
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GRiSP
PHIL_DS SEN_HS SEN_CS FR_HS22
24
26
28
30
32
(b)
Site
Tem
per
atu
re (
°C)
Air and Panicle Temperature at TOA (calculated)
The panicle is warmest not in the hottest, but in the most humid environment
Phils Sen.-hot Sen.-cool France
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GRiSP
Disaggregate observed sterility into its components Incomplete panicle exertion Chilling at microspore stage Heat at anthesis (at TOA)
PHIL_DS SEN_HS SEN_CS FR_HS0
10
20
30
40
50
60
70
80
90
100(c)
Chomrong IR64 S108 IR72
Site
Ste
rili
ty (
%)
Temperature induced spikelet sterility
Phils Sen.-hot Sen.-cool France
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GRiSP
PHIL_DS SEN_HS SEN_CS FR_HS
40
60
80
100
120
140
160
Chomrong IR64 S108 IR72 Last grain
Neck node
Site
Pa
nic
le e
xs
ert
ion
(%
)
(b)
Incomplete panicle exertion occurred in cold-night environments explained some of observed sterility
Sterile fraction of paniclecaused by non-exertion
Phils Sen.-hot Sen.-cool France
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GRiSP
12 14 16 18 20 22 24 26 280
10
20
30
40
50
60
70
80
90
100 Phil-ds Sen-hs
Sen-cs Fr-hs
T water (min) at microspore stage (°C)
Ste
rili
ty (
%)
Chomrong
2. Chilling effect at microspore stage on sterility (Tmeristem = Twater)
3. Heat effect at flowering stage on sterility (Tp at TOA)
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GRiSP Conclusions from experimental study
Rice has highly effective adaptations to thermal stresses:
Avoidance Transpiration cooling of panicle Good panicle exertion (long peduncle)
Escape Time of day of anthesis (TOA) and its adaptive plasticity
Tolerance To cold, as shown for cv. Chomrong Heat tolerant check cv. N22 failed (seed problems)
Heat stress more likely in warm-humid than hot-dry climates!
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GRiSP A new modeling tool RIDEV V.2
Simulator of… Phenology incl. microclimate & photoperiod effects 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 TOA)
Prediction (forward mode) Climate change impact mapping, plant type optimization Agronomy (crop calendar; optimization)
Heuristic parameterization of genotypes (reverse mode) Phenomics (extraction of genotypic parameter values
from experimental data)
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GRiSP Outlook
Indica GWAS panel (>200 acc., ORYTAGE project)
Field-phenotyped for phenology and sterility in 12 environments: 6 sowing dates in Senegal 3 altitudes x 2 years in Madagascar
Extraction of genotypic response parameters across environments (Heuristics): Cardinal temperatures Tb and To Thermal duration of phenological phases Photoperiod-sensitivity Chilling sensitivity of microsporogenesis Chilling sensitivity of panicle exertion Heat sensitivity of anthesis
Association study using GBS and 700K Oryza SNP chip
Use of RIDEV for Phenomics/GWAS
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GRiSP
Thank youMerciSalamat po