作物模型中单叶最大光合作用速率的温度响应修订

作物的光合作用对温度变化敏感,其温度依存性随品种、生长环境的变化而改变。基于光效率模型的作物生长模型,在应用中很少对光合作用的温度影响参数值进行订正,且在全生育期使用相同的参数值,难免会增加干物质模拟的误差。为此,本文以ORYZA2000模型为例,提出了一种修订光合作用温度影响参数值的方法。为确定方法的有效性,结合2012年和2013年水稻品种两优培九的温度梯度控制实验,首先利用抽穗开花期光合作用观测曲线提取了不同温度水平的光合作用参数值,然后结合Arrhenius方程和Peaked方程建立了温度敏感性参数的温度影响方程。将这些方程代入机理性光合作用模型,模拟了单叶最大光合作用速率与温度的曲线关系。最后,以归一化后的曲线关系修订作物模型参数值,并利用两年地上部分生物量(WAGT)观测值对其验证。结果显示,两优培九单叶最大总光合作用速率随温度的变化关系不同于ORYZA2000的默认设置,修订后的最适温度为38~40°C,高于默认值。在10~20°C的低温段,修订后的温度影响系数低于默认值。从WAGT模拟值的相对误差看,修订后较修订前平均降低约3.3%。本研究为改进干物质模拟精度和分析不同品种光合作用的温度依存性提供了重要参考。

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

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.