The study evaluates the accuracy of two FvCB model sub-models (I and II) in estimating the maximum electron transport rate for CO₂ assimilation (J_A-max) by comparing estimated values with observed maximum electron transport rates (J_f-max) in four C₃ species: Triticum aestivum L., Silphium perfoliatum L., Lolium perenne L., and Trifolium pratense L. Significant discrepancies were found between J_A-max estimates from sub-model I and observed J_f-max values for T. aestivum, S. perfoliatum, and T. pratense (p < 0.05), with sub-model I overestimating J_A-max for T. aestivum. Sub-model II consistently produced higher J_A-max estimates than sub-model I. This study highlights limitations in the FvCB sub-models, particularly their tendency to overestimate J_A-max when accounting for electron consumption by photorespiration (J_O), nitrate reduction (J_Nit), and the Mehler reaction (J_MAP). An alternative empirical model provided more accurate J_f-max estimates, suggesting the need for improved approaches to model photosynthetic electron transport. These findings have important implications for crop yield prediction, ecological modeling, and climate change adaptation strategies, emphasizing the need for more accurate estimation methods in plant physiology research.

This study analyzes stomatal conductance (g_sc) in Trifolium repens L., Lolium perenne L., and Triticum aestivum L. under varying environmental conditions. Light-response curves for photosynthesis (A_n–I) at 420 μmol mol⁻¹ CO₂ were used to determine saturating irradiance (I_sat) using a light-response model for photosynthesis, and CO₂-response curves for photosynthesis (A_n–C_i) were measured at I_sat and half I_sat for these C₃ plant species. The Ball–Woodrow–Berry (BWB) model, Medlyn model, and a new model were compared for their ability to describe the net photosynthetic rate (A_n) relative to g_sc under changing irradiance or CO₂. The BWB model overestimated g_sc response, simplifying stomatal behavior, while the Medlyn model deviated at high A_n values, indicating limitations in dynamic responses. The new model showed a better empirical fit under the tested conditions, achieving high R² values and low AIC values across all three species, and demonstrated a strong alignment with empirical data. Our findings highlight the complexity of g_sc regulation and the need for improved models to better represent stomatal dynamics under different environmental conditions. This research is vital for optimizing water use efficiency, enhancing crop productivity, and understanding plant resilience to climate change.