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Acta Agronomica Sinica ›› 2018, Vol. 44 ›› Issue (05): 750-761.doi: 10.3724/SP.J.1006.2018.00750


Correcting the Response of Maximum Leaf Photosynthetic Rate to Temperatures in Crop Models

Shen-Bin YANG1(), Sha-Sha XU2, Xiao-Dong JIANG1,3, Chun-Lin SHI3, Ying-Ping WANG4, Shuang-He SHEN1   

  1. 1 Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters / College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu, China;
    2 Yangzhou Meteorological Bureau, Yangzhou 225009, Jiangsu, China
    3 Jiangsu Academy of Agricultural Sciences, Nanjing 210014, Jiangsu, China
    4 CSIRO Marine and Atmospheric Research, PMB # 1, Aspendale, Victoria 3195, Australia
  • Received:2017-11-15 Accepted:2018-03-15 Online:2018-05-20 Published:2018-03-16
  • Supported by:
    This study was supported by Special Fund for Meteorology-scientific Research in the Public Interest (GYHY201306035, GYHY201306036) and Key Projects in the National Science & Technology Pillar Program during the Twelfth Five-year Plan Period (2011BAD32B01)


Crop photosynthesis is sensitive to temperature variations, and the temperature dependence of photosynthesis is known to vary with growth environments and crop varieties. Crop models based on light use efficiency model, seldom correct parameter values related to the temperature dependence of photosynthesis for a specific crop, which unavoidably increases the simulation errors in dry biomass. In this paper, a scheme used to correct those parameter values was put forward with the rice crop model ORYZA2000 as an example to evaluate the scheme’s performance. The temperature-controlled experiments were conducted to observe photosynthesis at heading stage of rice variety Liangyoupeijiu in 2012 and 2013. The data were first analyzed to retrieve photosynthetic characteristics from light response curves and CO2 response curve. Based on their relationship with temperatures, temperature effect functions were established for all temperature sensitive photosynthetic parameters using Arrhenius and Peaked functions. A biochemical photosynthesis model was applied to simulate the changes of maximum leaf photosynthetic rate with temperatures, based on which temperature response curve for maximum leaf photosynthetic rate was produced and normalized to replace the default parameter values in ORYZA2000. The observations of above ground biomass (WAGT) of Liangyoupeijiu in two years were used to validate simulations before and after the correction. The normalized temperature response curve for maximum leaf photosynthetic rate of Liangyoupeijiu was different from the default response curve in ORYZA2000. From the corrected response curve, the optimal temperature for photosynthesis was between 38-40°C, higher than the default, and temperature effect coefficient was lower than the default between 10-20°C. Compared with the default parameter values, average relative error of the corrected parameter values was reduced by 3.3%. In conclusion, the method used in this paper can be an important reference for improving biomass simulation accuracy and analyzing temperature dependence of photosynthesis for different crop varieties.

Key words: temperature dependence, phenology, dry biomass, climate warming, parameter value correction

Fig. 1

Default parameter values of REDFTT in ORYZA2000"

Fig. 2

Curves of Am with the change of temperatures (a) and AL with the change of Ia under different temperatures (b) It is assumed that Ia=1000 W m-2 leaf, SN=0.7 g N m-2 leaf, CCO2=400 μmol mol-1."

Fig. 3

Scheme for parameter value correction"

Fig. 4

Light response curve (a) and CO2 response curve of green leaf (b) of Liangyoupeijiu at heading stage under different temperature treatments"

Fig. 5

Changes of characteristic values retrieved from light response curves of rice with different temperature treatments(a) Light saturation point; (b) Light compensation point; (c) Maximum photosynthesis rate; (d) Apparent quantum efficiency; (e) Rd. Mean values with standard deviations (vertical bars) are shown in the bar charts."

Fig. 6

Changes of characteristic values retrieved from CO2 response curves of rice with leaf temperatures(a) Kc and Ko; (b) Vcmax; (c) Jmax; (d) Jmax/Vcmax; (e) Γ*; (f) Rd."

Table 1

Parameter values in temperature response functions for photosynthetic parameters"

Photosynthetic parameter
Function parameter
Parameter value
Kc a1 406.3 μmol m-2 s-1 1.0
b1 79.48 kJ mol-1
Ko a1 277.2 mmol m-2 s-1 1.0
b1 36.31 kJ mol-1
Vcmax k25 115.0 μmol m-2 s-1 0.93
Ea 65.1 kJ mol-1
ΔS 607.4 J mol-1
Hd 200 kJ mol-1
Jmax k25 230 μmol m-2 s-1 0.89
Ea 35.44 kJ mol-1
ΔS 626.3 J mol-1
Hd 198.7 kJ mol-1
Rd k25 3.25 μmol m-2 s-1 0.92
Ea 39.35 kJ mol-1
ΔS 0.084 J mol-1
Hd 33.3 J mol-1

Fig. 7

Changes of An, Rd, and An+Rd with TL Assuming PAR=1400 μmol m-2 s-1, Ci=340 μmol mol-1."

Fig. 8

Changes of An, Rd, and An+Rd with TL under different concentration of Ci Assuming PAR=1400 μmol m-2 s-1."

Fig. 9

Relationship between leaf temperature TL and air temperature Ta (a) and Change of temperature effect coefficient with air temperature Ta (b)"

Fig. 10

Relative errors of simulated WAGT with observations before and after the modification of parameter values of REDFTT(a) for 2012; (b) for 2013. Vertical bar is standard deviation."

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