Estimation of photosynthesis parameters for a modified Farquhar–von Caemmerer–Berry model using simultaneous estimation method and nonlinear mixed effects model
► Light dependency of Rubisco activation was added to the FvCB photosynthesis model. ► Temperature dependency of the parameters was validated and adjusted. ► Simultaneous estimation method for model parameter estimation was applied. ► Parameter estimation was improved by using nonlinear mixed effect...
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Veröffentlicht in: | Environmental and experimental botany 2012-10, Vol.82, p.66-73 |
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Sprache: | eng |
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Zusammenfassung: | ► Light dependency of Rubisco activation was added to the FvCB photosynthesis model. ► Temperature dependency of the parameters was validated and adjusted. ► Simultaneous estimation method for model parameter estimation was applied. ► Parameter estimation was improved by using nonlinear mixed effects model. ► Measurements under wide environmental ranges yielded parameters with broad validity.
The aims of this paper was to modify the photosynthesis model of Farquhar, von Caemmerer and Berry (FvCB) to be able to predict light dependency of the carboxylation capacity (Vc) and to improve the prediction of temperature dependency of the maximum carboxylation capacity (Vcmax) and the maximum electron transport rate (Jmax). The FvCB model was modified by adding a sub-model for Ribulose-1,5-bisphosphate carboxylase (Rubisco) activation and validating the parameters for temperature dependency of Vcmax and Jmax. Values of parameters for temperature dependency of Vcmax and Jmax were validated and adjusted based on data of the photosynthesis response to temperature. Parameter estimation was based on measurements under a wide range of environmental conditions, providing parameters with broad validity. The simultaneous estimation method and the nonlinear mixed effects model were applied to ensure the accuracy of the parameter estimation. The FvCB parameters, Vcmax, Jmax, α (the efficiency of light energy conversion), θ (the curvature of light response of electron transport), and Rd (the non-photorespiratory CO2 release) were estimated and validated on a dataset from two other years. Observations and predictions matched well (R2=0.94). We conclude that incorporating a sub-model of Rubisco activation improved the FvCB model through predicting light dependency of carboxylation rate; and that estimating Vcmax, Jmax, α, θ, and Rd requires data sets of both CO2 and light response curves. |
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ISSN: | 0098-8472 1873-7307 |
DOI: | 10.1016/j.envexpbot.2012.03.014 |