Abstract
An induction-dependent empirical model was developed to simulate the C3 leaf photosynthesis under fluctuating light and different temperatures. The model also takes into account the stomatal conductance when the light intensity just exceeds the compensation point after a prolonged period of darkness (initial stomatal conductance, $$ g_{{{\text{S}}_{\text{ini}} }} $$ ). The model was parameterized for both Chrysanthemum morifolium and Spinacia oleracea by artificially changing the induction states of the leaves in the climate chamber. The model was tested under natural conditions that were including frequent light flecks due to partial cloud cover and varying temperatures. The temporal course of observed photosynthesis rate and the carbon gain was compared to the simulation. The ability of the current model to predict the carbon assimilation rate was assessed using different statistical indexes. The model predictions were accurate but the model slightly underestimated the actual overall carbon gain. The accuracy of the simulation was largely dependent on the parameters that were calculated for the particular plant species, of which the simulation is intended for. In particular, the rate of change of induction and the initial stomatal conductance were found to be highly important and these were species-specific parameters for the predictions. The model is suitable for estimating instantaneous leaf CO2 assimilation for different herbaceous plant species under dynamic environmental conditions. It can be simply calibrated for other crops, by estimating the individual parameters.
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