Differential effects of day and
night temperature on leaf
elongation and determination of
apparent base temperature for
contrasted genotypes
Tanguy Lafarge
Estela Pasuquin, Bancha Wiangsamut
Temperature effect on grain yield
• Detrimental effect of elevated temperature on grain yield in rice (Peng et al., 2004; Sheehy et al., 2005)
• Crop response to temperature and its magnitude differed with regard to:
– the range in climate conditions and associated correlation between
climate factors, particularly radiation, day and night temperature
– the approach for analysis: correlations or models
⇒ Confounding effects make it difficult to quantify the differential effects of radiation, day and night temperature on a highly
integrated variable like grain yield which implies a long time scale approach
⇒ Analyzing the day and night temperature effect on underlying straight forward processes driving grain yield is a key step
Response of plant growth and development to
temperature: the thermal time concept
•
Calculation of thermal time in rice is reported
in the literature with a range of temperature
coefficients, with base temperature varying
from 8 to 14C depending on
– the genotype,
– the growing conditions (field and controlled),
– the process under consideration (leaf emergence,
time to flowering),
– the location of temperature measurement (air or
tissue temperature),
– the fitted mathematical function (linear and non linear
•
Calculation of thermal time, however, implies
that:
– distinct processes like development rate (leaf
emergence, time to flowering) and elongation rate (of different leaves, of different internodes) are related to temperature with the same parameters
– these parameters are stable in contrasted conditions
– the mathematical function used to account for the plant
response to temperature is valid in a wide range in conditions
•
The variability between genotypes needs to
be addressed
Response of plant growth and development to
temperature: the thermal time concept
• Organ elongation (blade, sheath, culm):
– is a key underlying process for leaf area production and time to flowering, directly driving grain yield
– is directly controlled by temperature in favorable growing conditions
• Measuring visible leaf elongation is a non- destructive technique and then reduces sampling errors
• Response of blade, sheath and internode elongation are dependent on the same processes and might be affected by temperature in the same way.
- Climatic demand (or air dryness or VPD) affects leaf elongation. And daytime temperature is highly correlated with VPD.
⇒ It is essential to consider low VPD conditions
when comparing differential day and night
temperature effects to differentiate the effect of high temperature from that of high VPD.
- Plant response is studied in a wider range in temperature conditions
• Elongation rate of leaves 6 and 9 are contrasted (LER increases with leaf position on the stem until about leaf 10)
• Elongation of leaf 6 started after seedling
establishment (transplanting was done at 3-leaf stage when leaf 4 was expected to emerge and leaf 5 was already growing)
• Elongation of leaf 9 finished before the start in culm elongation (so that non-destructive
observations accounted for leaf elongation only. Non-destructive observations of elongation of leaves from upper positions was the sum of leaf and internode elongation)
A fixed horizontal ruler was placed in contact to the leaf blade
Elongation of leaf only was measured (the culm was not yet growing)
Actual leaf length was measured
from the ruler to the tip
Measurements were done daily at 6am and 6pm
High-yielding IR8 I0
elite lines IR72 I1
IR64 I2
High-yielding IR75217H H1
hybrids SL-8 H3 IR78386H H5 Bigante H9
New plant types NPT 2nd N1
NPT 1st N7
Cold tolerant Imbonggo I31
genotypes Biniggon I32 SHZ-2 I33 IRKR22 I35
Drought tolerant Apo I21
genotypes Vandana I22 IR77843 H11
Sowing dates were organized by a regular time interval
so that leaves 6 and 9 of distinct sets of plants
were growing simultaneously
Leaf elongation of 16 contrasted genotypes was measured
Temperature conditions were modified for each set of leaves 6 and 9 growing together
•
It is essential to measure micro-climate
data to access to the real conditions
affecting plants and to deal with
confounding factors:
– With regard to the vegetative phase, apical
meristem is the site where most growth processes are initiated and occur. Growth
processes are highly controlled by temperature. In flooded rice, meristem temperature is
equivalent to water temperature before PI
Microclimate data were measured continuously and stored every 30 minutes
Water temperature was measured in a large set of pots
Hours 0 40 80 120 160 200 240 LER (mm hr -1 ) 0 1 2 3 4 Leaf 6 Leaf 9
Diurnal variation of LER of leaves 6 and 9 in the greenhouse with time from transplanting
LERmax values corresponded to data collected during the first 2 days after leaf emergence only
Short period during which LER is maximal before reduction in LER due to leaf age
Water temperature (C) 10 15 20 25 30 LE R max of l e af 9 (mm hr -1 ) 0 2 4 6 night
Response of LER
maxof leaf 9 to water temperature
Increase in LER
maxin the range of water temperature
from 17 to 22 C for night time periods
Average daytime air VPD values were below 0.5 kPa Water temperature (°C) 10 15 20 25 30 LE R max of l e af 9 (mm hr -1 ) 0 2 4 6 day night
Increase in LERmax in the range of water temperature from 17 to 25 C Similarity of the response for night and day time periods
Response of LER
maxof leaf 9 to water temperature
Water temperature (°C) 10 15 20 25 30 LER max o f l e af 9 (m m hr -1 ) 0 2 4 6 day night Water temperature (°C) 10 15 20 25 30 LER max o f l e af 9 (m m hr -1 ) 0 2 4 6 day night Water temperature (°C) 10 15 20 25 30 LER ma x of le af 9 (mm hr -1 ) 0 2 4 6 day night
IR64 Hybrid rice
Water temperature (°C) 10 15 20 25 30 LER ma x of lea f 9 ( m m hr -1 ) 0 2 4 6 day night
Cold tolerant Drought tolerant
Response of LER
maxof leaf 9 to water temperature
Water temperature (°C) 10 15 20 25 30 LE R max ( mm hr -1 ) 0 2 4 6 day night regression
In the conditions from 17 to 25 °C, a linear response can be considered.
Some extra data at lower temperature will provide great information with regard to the shape of the response and its validity in a large range of conditions.
This linear response is at least valid in the tropics where the night temperature does not go below 20 °C.
Response of LER
maxof leaf 9 to water temperature
Water temperature (°C) 10 15 20 25 30 LE R max ( mm hr -1 ) 0 2 4 6 day night regression
Comparing the temperature response of LER
maxof
2 distinct leaves with contrasted absolute values
LERmax of leaves 6 and 9 were normalized with respect to their corresponding values obtained from the regression line at 21 C
Variety I2 (IR64)
LERreg = LERmax / LER21
LER21
LERreg was then calculated for each LERmax of leaf 6 and leaf 9:
and plotted against water temperature…
LER max (mm h -1 ) 0.0 0.4 0.8 1.2 1.6 2.0 leaf 6 day leaf 6 night leaf 9 day leaf 9 night regression Water temperature (°C) 10 15 20 25 0.0 0.4 0.8 1.2 1.6 10 15 20 25 30
Temperature response of LER
maxof leaves 6 and 9
IR64
Hybrid rice
Cold tolerant Drought tolerant
For a range of genotypes, normalized slopes and x-intercepts did not differ significantly: - for leaves 6 and 9
- for day and nighttime periods apparent base
Plant type r2 X-intercept
(°C)
High-yielding IR8 I0 0.82 13.56
elite lines IR72 I1 0.57 11.65
IR64 I2 0.85 12.20
High-yielding IR75217H H1 0.54 10.57
hybrids SL-8 H3 0.52 11.00
IR78386H H5 0.73 11.68
Bigante H9 0.65 11.24
New plant types NPT 2nd N1 0.45 10.41
NPT 1st N7 0.74 12.43
Cold tolerant Imbonggo I31 0.66 11.87
genotypes Biniggon I32 0.59 10.94 SHZ-2 I33 0.92 13.29 IRKR22 I35 0.79 12.74
Drought tolerant Apo I21 0.88 12.38
genotypes Vandana I22 0.65 11.66 IR77843 H11 0.81 13.03
Variability of the apparent base temperature for leaf
elongation assuming a linear response to temperature
Leaf elongation of leaves 6 and 9 measured in the field
Distinct growing periods were considered to get access to a range in temperature conditions : 10 sowing dates from early January to mid-May every 2 weeks to have plants growing during the cooler (January-February) and hotter (April-May) part of the season
16 genotypes as in the phytotron
Similar crop management and data collection
Continuous micro-climate data collection including water
Calendar time 2/ 1/ 06 3/ 1/ 06 4/ 1/ 06 5/ 1/ 06 Temperature (C) 20 24 28 32 36
Max Climate Unit Min Climate Unit Max field
Min field Max water Min water
Dealing with temperature in the field: water temperature in
irrigated rice at night was 2C higher than air temperature
Water temperature 10 15 20 25 30 35 LE Rmax (mm h r -1 ) 0 2 4 6 day night Water temperature 10 15 20 25 30 35 LE Rmax (mm h r -1 ) 0 2 4 6 day night Water temperature 10 15 20 25 30 35 LE Rmax (mm h r -1 ) 0 2 4 6 day night Water temperature 10 15 20 25 30 35 LE Rma x ( mm h r -1 ) 0 2 4 6 day night
Comparing the temperature response of LER
maxin the phytotron and in the field
Field Phytotron Field Phytotron Field Phytotron Field Phytotron
IR64 Hybrid rice
Drought tolerant Cold tolerant
Water temperature 10 15 20 25 30 35 LE Rma x ( mm h r -1 ) 0 2 4 6 day night Water temperature 10 15 20 25 30 35 LER ma x ( mm h r -1 ) 0 2 4 6 day night Water temperature 10 15 20 25 30 35 LE Rma x ( mm h r -1 ) 0 2 4 6 day night Water temperature 10 15 20 25 30 35 LE Rmax (mm h r -1 ) 0 2 4 6 day night Field Phytotron Field Phytotron Field Phytotron Field Phytotron
Comparing the temperature response of LER
maxin the phytotron and in the field
IR64 Hybrid rice
Drought tolerant Cold tolerant
Water temperature (°C) 10 15 20 25 30 35 LER max (mm hr -1 ) 0 2 4 6
Comparing the temperature response of LER
maxin the phytotron and in the field
IR64 Leaf 9
Is there a different response to temperature in field and phytotron? Is there a contrasted response to night and daytime temperature?
LERmax LERreg VPDa 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 (LER max - LER re g ) / LE Rreg (mm h -1 ) -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2
Effect of air VPD on daytime LERmax
Higher VPD in the field may explain the reduction in daytime LERmax What about at night?
G rain y iel d (tons ha -1 ) 3 6 9 S hoot dry w ei ght (g m -2 ) 1200 1400 1600 Maximum temperature (0C) 28 29 30 31 32 33 34 35 36 H a rvest index 0.30 0.35 0.40 0.45 0.50 0.55 3 6 9 1200 1400 1600 Minimum temperature (0C) 23 24 25 26 27 28 0.30 0.35 0.40 0.45 0.50 0.55 3 6 9 1200 1400 1600 1800 Radiation (MJ m-2 day-1) 15 16 17 18 19 20 0.30 0.35 0.40 0.45 0.50 0.55 r2 = 0.73 r2 = 0.70 r2 = 0.62 r2 = 0.59
IR64, Climate conditions from sowing to maturity
Maximum tiller (no. m-2) 500 600 700 800 900 G rain Y ie ld (t ha -1 ) 3 4 5 6 7 8 9
Panicle number (no. m-2)
280 300 320 340 G rain Y ield (t ha -1 ) 3 4 5 6 7 8 9
Filled grain (no. m-2)
15000 20000 25000 30000 Grain Y ie ld ( t ha -1 ) 3 4 5 6 7 8 9
Tiller mortality rate
0.40 0.45 0.50 0.55 0.60 0.65 0.70 Grain Y ield (t ha -1 ) 3 4 5 6 7 8 9 r2 = 0.35 r2 = 0.05 r2 = 0.35 r2 = 0.88
G ra in y iel d (to n s ha -1 ) 3 6 9 S h oot dr y w ei ght (g m -2 ) 1200 1400 1600 Maximum temperature (0C) 28 29 30 31 32 33 34 35 36 Ha rv e s t in de x 0.30 0.35 0.40 0.45 0.50 0.55 3 6 9 1200 1400 1600 Minimum temperature (0C) 23 24 25 26 27 28 0.30 0.35 0.40 0.45 0.50 0.55 3 6 9 1200 1400 1600 1800 Radiation (MJ m-2 day-1) 12 15 18 21 24 0.30 0.35 0.40 0.45 0.50 0.55 r2 = 0.33 r2 = 0.51 r2 = 0.42 r2 = 0.44 r2 = 0.63 r2 = 0.72
IR64, Climate conditions from flowering to maturity
• In temperature conditions lower than 26C, the effect of day and night temperature on leaf elongation is similar
• In temperature conditions higher than 26C, the response of leaf elongation to daytime temperature appears to be affected by VPD conditions for values as low as 1 kPa
• In temperature conditions higher than 26C, the response of leaf elongation to nighttime temperature is not clear and further data are under collection
• Apparent base temperature varies across genotypes. There is a tendency for lower value for hybrid rice compared to elite lines
• Differential response of day and night temperature on growth processes during grain filling appears to play a key role in determining grain yield
