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 Pn-PAR response curves. The rectangular hyperbolic model (RHM), Michaelis-Menten model (MMM), and modified rectangular hyperbolic model (MRHM) were used for fitting the Pn-Ci 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 Pn-PAR response curve was as follows: MRHM > MEM > NRHM > RHM. The 3 models for Pn-Ci 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), Pnmax(I), LSP, Rd, Pnmax(C) and CiSP was greater, the influence of different layers on LCP, α(C), CiCP and Rp was greater, while the influence of different directions on these all response parameters was little. The values of LSP, CiSP, α(C) and CiCP 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.