Beating the heat for rice
Integrated pipeline to generate varieties adapted to
climate variability at a faster rate
M.C Rebolledo
E. Petro
A.Pena
C.Erazo
D.Jimenez
S.Delerce
E.Torres

• Climate variability explains ~32% of
rice yield variability globally.
• 25% to 38% in Latin America
(precipitation and temperature
variability).
Rice production is highly sensitive to climate conditions event under current climate scenarios
Ray et al, 2015
Climate variability and rice production

Our strategy:
1.Environment characterization “through the eyes of the crop”
2.Trait dissection for specific environments
3.Unlocking the gene bank to increase the adaptation for specific environments
We need to provide breeders with the phenomics, genomics and environmental
information, as well as target ideotypes, to generate better adapted varieties at a
faster rate.

Boxplots of conditional permutation based VI scores using CIF on cultivar F733 subset (Jimenez and
Delerce)
1.Environment characterization “through the eyes of the crop”:
Big data analysis of commercial data
Saldana :Yields limited by low
radiation accumulated during the
maturity stage
Saldana: yields limited by high night
temperature during the reproductive
stage (Tmin >23°C)

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Yields (kg/ha) Saldana Tolima
CT21375
FED2000
FED733
Saldaña
Yopal
Villavicencio
Aipe
Montería
1.Environment characterization “through the eyes of the crop”:
Multi-environmental trials
-Same management, same soil, just different sowing dates and a decrease
of almost 50% on grain yields

y = 1713.6x2 - 81520x + 975215
R² = 0.5883
y = -2148x2 + 97893x - 1E+06
R² = 0.6216
y = 256.18x2 - 14308x + 200986
R² = 0.7321
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Average Min Temperature ( C )
yield vs. Average Tmin Reproductive stage
CT21375
FED2000
FED733
An increase (1 °C) in night temperature during
reproductive stage will result in major crop
losses
1. Environment characterization “through the eyes of the crop”:
Validation of the main crop limiting factors
y = 6E-05x2 - 1.2994x + 12399
R² = 0.8526
y = -5E-05x2 + 2.066x - 13787
R² = 0.5803
y = 5E-05x2 - 0.9946x + 9760.8
R² = 0.8095
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Radiation accumulated at ripening stage Cal/cm2/day
yield vs. accumulated radiation maturity
CT21375
FED2000
FED733
A decrease in solar radiation during maturity
stage will result in major crop losses
Peng S et al. PNAS
2004;101:9971-9975
High night temperatures AND low radiation
occur together in the field
causing grain yield losses even under
current climates

-High night temperatures
will increase respiration
rates
-Low radiation will
decrease the
photosynthetic rate
NightDay
Photosynthesis Respiration
Co2 Co2
Role of non
structural
carbohydrate
Reserves ?
STARCH
Co2
Loss
Co2
Assimilation
Vegetative Reproductive Maturity
Rate of STARCH decrease?
Contribution to yield under
high night temperature and
low radiation?
2.Trait dissection to increase the adaptation of rice varieties to specific climatic conditions
Negative balance for CO2 in the plant

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starch contribution to grains (mg/gDM)
Traits, genes and promising parental lines that
will confer higher yield under high night
temperatures and low light in Saldana Tolima
High throughput
phenotypic tools
for breeding
Unlocking the gene bankPromising parental lines for breeding
3.Unlocking the gene bank to increase the adaptation of rice varieties to specific
climatic conditions
New genes conferring tolerance to low light and high night
temperatures for breeding

Site characterization
“through the eyes of the crop”
-Climate
-Soils
-cropping system
-management
-End use of the crop
Traits of interest/
promising parental
lines
- Trait dissection
- Genetic resources
Genes
- Genotyping and
phenotyping tools
- Local genetic
background
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA
DATA Varieties adapted to climate
change
New plant
types for
climate
variability
Empirical and
Mechanistic modelling +
Future spatial and
temporal climate
(CCAFS)
Breeding
1.Environment
characterization
2.Trait
Dissection
3.Unlocking
the gene
bank
Breeding
GRISP II ?