光合模型对无患子叶片光合响应参数计算结果的影响

张赟齐; 高世轮; 卫星杓; 史文辉; 马仲; 苏淑钗

doi:10.13332/j.1000-1522.20180163

光合模型对无患子叶片光合响应参数计算结果的影响

Effects of photosynthetic models on the calculation results of photosynthetic response parameters in Sapindus mukorossi leaves

摘要

摘要:
目的旨在探究光合模型对无患子冠层不同部位叶片光合响应参数计算结果的影响，并得到合适的光合响应应用模型和合理的光合响应参数。
方法本研究以福建建宁地区进入稳定结实期的无患子为研究对象，采用直角双曲线模型、非直角双曲线模型、直角修正模型和指数修正模型来拟合无患子冠层不同部位叶片的光响应曲线，采用直角修正模型、直角双曲线模型和Michaelis-Menten模型来拟合CO₂响应曲线，通过均方误差和决定系数来检验光合响应模型的拟合精度，采用Duncan多重比较法检验不同模型和不同部位叶片光合响应参数的差异并进行方差分析。
结果（1）4种模型对光响应曲线拟合结果的优劣为：直角修正模型 > 指数修正模型 > 非直角双曲线模型 > 直角双曲线模型，3种模型对CO₂响应曲线拟合优劣的结果类似：直角修正模型 > 直角双曲线模型/Michaelis-Menten模型。（2）层级间叶片光合响应参数的差异显著性因模型而有别，各模型得到的方向间叶片光合响应参数值的差异均不显著。（3）模型对初始量子效率、光响应最大净光合速率、光饱和点、暗呼吸速率、CO₂响应最大净光合速率和CO₂饱和点的影响更大，层级对光补偿点、初始羧化效率、CO₂补偿点和光呼吸速率的影响更大，方向对光合响应参数无显著影响，光饱和点、CO₂饱和点、初始羧化效率和CO₂补偿点还受到交互作用的显著影响。
结论相对于其他模型，直角修正模型能更好地拟合无患子光合响应曲线，得到的光合响应参数也较准确；模型对所有光合响应参数的影响是极显著的，模型的筛选很重要。

Abstract:
ObjectiveThe aim of this study was to explore the effects of photosynthetic models on the results of photosynthetic response parameters ’ values of leaves in different parts of Sapindus mukorossi canopy, and to obtain appropriate application model and reasonable values.
MethodIn this study, S. mukorossi trees with stable fruiting stage were selected as the test trees in Jianning County of Fujian Province, southern China for determining photosynthetic response parameters of leaves in different parts of canopy. The rectangular hyperbolic model (RHM), non-rectangular hyperbolic model (NRHM), modified rectangular hyperbolic model (MRHM), and modified exponential model (MEM) were used for fitting the P_n-PAR response curves. The rectangular hyperbolic model (RHM), Michaelis-Menten model (MMM), and modified rectangular hyperbolic model (MRHM) were used for fitting the P_n-C_i response curves. The fitting accuracy of the models was tested by comparing mean square errors and determinant coefficients. The differences of photosynthetic response parameters ’ values among different models and different parts of canopy were examined by Duncan multiple comparison method and the data were also analyzed with ANOVA.
Result(1) The fitting accuracy of the 4 models for P_n-PAR response curve was as follows: MRHM > MEM > NRHM > RHM. The 3 models for P_n-C_i response curve produced the similar results: MRHM > RHM/MMM. (2) The significant difference of photosynthetic response parameters’ values among different layers varied by different models and the difference of these values among different directions was not significant. (3) The influence of different models on α_(I), P_nmax(I), LSP, R_d, P_nmax(C) and C_iSP was greater, the influence of different layers on LCP, α_(C), C_iCP and R_p was greater, while the influence of different directions on these all response parameters was little. The values of LSP, C_iSP, α_(C) and C_iCP were also significantly influenced by interaction.
ConclusionCompared with other models, MRHM could be better for fitting the photosynthetic response curve and obtaining more accurate values. The influence of models on the values of all photosynthetic response parameters was very significant, so the screening of models was important.

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