Investigation on intrinsic properties of photosynthetic pigment molecules participating in solar energy absorption and excitation, especially their eigen-absorption cross-section (σ_ik) and effective absorption cross-section (σ^′_ik), is important to understand photosynthesis. Here, we present the development and application of a new method to determine these parameters, based on a mechanistic model of the photosynthetic electron flow-light response. The analysis with our method of a series of previously collected chlorophyll a fluorescence data shows that the absorption cross-section of photosynthetic pigment molecules has different values of approximately 10⁻²¹ m², for several photosynthetic organisms grown under various conditions: (1) the conifer Abies alba Mill., grown under high light or low light; (2) Taxus baccata L., grown under fertilization or non-fertilization conditions; (3) Glycine max L. (Merr.), grown under a CO₂ concentration of 400 or 600 μmol CO₂ mol⁻¹ in a leaf chamber under shaded conditions; (4) Zea mays L., at temperatures of 30°C or 35°C in a leaf chamber; (5) Osmanthus fragrans Loureiro, with shaded-leaf or sun-leaf; and (6) the cyanobacterium Microcystis aeruginosa FACHB905, grown under two different nitrogen supplies. Our results show that σ_ik has the same order of magnitude (approximately 10⁻²¹ m²), and σ^′_ik for these species decreases with increasing light intensity, demonstrating the operation of a key regulatory mechanism to reduce solar absorption and avoid high light damage. Moreover, compared with other approaches, both σ_ik and σ^′_ik can be more easily estimated by our method, even under various growth conditions (e.g., different light environment; different CO₂, NO₂, O₂, and O₃ concentrations; air temperatures; or water stress), regardless of the type of the sample (e.g., dilute or concentrated cell suspensions or leaves). Our results also show that CO₂ concentration and temperature have little effect on σ_ik values for G. max and Z. mays. Consequently, our approach provides a powerful tool to investigate light energy absorption of photosynthetic pigment molecules and gives us new information on how plants and cyanobacteria modify their light-harvesting properties under different stress conditions.

The models used to describe the light response of electron transport rate in photosynthesis play a crucial role in determining two key parameters i.e., the maximum electron transport rate (J_max) and the saturation light intensity (I_sat). However, not all models accurately fitJ–Icurves, and determine the values ofJ_maxandI_sat. Here, three models, namely the double exponential (DE) model, the non-rectangular hyperbolic (NRH) model, and a mechanistic model developed by one of the coauthors (Z-P Ye) and his coworkers (referred to as the mechanistic model), were compared in terms of their ability to fitJ–Icurves and estimateJ_maxandI_sat. Here, we apply these three models to a series of previously collected Chlafluorescence data from seven photosynthetic organisms, grown under different conditions. Our results show that the mechanistic model performed well in describing theJ–Icurves, regardless of whether photoinhibition/dynamic down-regulation of photosystem II (PSII) occurs. Moreover, bothJ_maxandI_satestimated by this model are in very good agreement with the measured data. On the contrary, although the DE model simulates quite well theJ–Icurve for the species studied, it significantly overestimates both theJ_maxofAmaranthus hypochondriacusand theI_satofMicrocystis aeruginosagrown under NH₄⁺-N supply. More importantly, the light intensity required to achieve the potential maximum ofJ(J_s) estimated by this model exceeds the unexpected high value of 10⁵μmol photons m⁻²s⁻¹forTriticum aestivumandA. hypochondriacus. The NRH model fails to characterize theJ-Icurves with dynamic down-regulation/photoinhibition forAbies alba,Oryza sativaandM. aeruginosa. In addition, this model also significantly overestimates the values ofJ_maxforT. aestivumat 21% O₂andA. hypochondriacusgrown under normal condition, and significantly underestimates the values ofJ_maxforM. aeruginosagrown under NO₃^–N supply. Our study provides evidence that the ‘mechanistic model’ is much more suitable than both the DE and NRH models in fitting theJ–Icurves and in estimating the photosynthetic parameters. This is a powerful tool for studying light harvesting properties and the dynamic down-regulation of PSII/photoinhibition.

Accurate determination of photosynthetic parameters is essential for understanding how plants respond to environmental changes. In this study, we evaluated the performance of the Farquhar-von Caemmerer-Berry (FvCB) model and introduced a novel model to fit photosynthetic rates against ambient CO₂ concentration (A_n–C_a) and intercellular CO₂ concentration (A_n–C_i) curves for Lolium perenne and Triticum aestivum under 2% and 21% O₂ conditions. We observed significant discrepancies in the FvCB model’s fitting capacity for A_n–C_a and A_n–C_a curves across different oxygen regimes, particularly in estimates of key parameters such as the maximum carboxylation rate (V_cmax), the day respiratory rate (R_day), and the maximum electron transport rate for carbon assimilation (J_A-max). Notably, under 2% and 21% O₂ conditions, the values of V_cmax and R_day derived from A_n–C_a curves using the FvCB model were 46.98%, 44.37%, 46.63%, and 37.66% lower than those from A_n–C_i curves for L. perenne, and 47.10%, 44.30%, 47.03%, and 37.36% lower for T. aestivum, respectively. These results highlight that the FvCB model yields significantly different V_cmax and R_day values when fitting A_n–C_a versus A_n–C_i curves for these two C₃ plants. In contrast, the novel model demonstrated superior fitting capabilities for both A_n–C_a and A_n–C_i curves under 2% and 21% O₂ conditions, achieving high determination coefficients (R²≥ 0.989). Key parameters such as the maximum net photosynthetic rate (A_max) and the CO₂ compensation point (Γ) in the presence of R_day, showed no significant differences across oxygen concentrations. However, the apparent photorespiratory rate (R_pa0) and photorespiratory rate (R_p0) derived from A_n–C_i curves consistently exceeded those from A_n–C_a curves for both plant species. Furthermore, R_pa0 values derived from A_n–C_a curves closely matched observed values, suggesting that A_n–C_a curves more accurately reflect the physiological state of plants, particularly for estimating photorespiratory rates. This study underscores the importance of selecting appropriate CO₂-response curves to investigate plant photosynthesis and photorespiration under diverse environmental conditions, thereby ensuring a more accurate understanding of plant responses to changing environments

Photosynthetica covers wide range of photosynthesis research or research including photosynthetic parameters of both experimental and theoretical nature.

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.

Leaf day respiratory rate (Rd), a pivotal component of plant carbon metabolism that directly modulates net photosynthetic carbon gain and plant fitness, has long been challenging to accurately quantify due to overlapping CO2 fluxes with photosynthesis and photorespiration (Rp). This study aimed to disentangle Rd from Rp in C3 crops using a high-CO2/low-O2 (>1200 μmol mol–1 CO2 + 2% O2) An/Ca (net photosynthetic rate-ambient CO2 concentration) model. We integrated two datasets: An/Ca curve data of four C3 species (Trifolium pratense, Silphium perfoliatum, Lolium perenne, Triticum aestivum) under ambient O2 (21% O2) from Ye et al. (2025) and newly collected data under low O2 (2% O2) for the same species. A dedicated model (Eqn 1) was developed to extract key parameters [e.g., the maximum net photosynthetic rate (Anmax), CO2 compensation point (Γ) in the presence of Rd, photorespiratory rate at Ca = 0 μmol mol–1 (RC0)] from An/Ca curves, with ANOVA confirming no significant differences between calculated and observed parameter values (p > 0.05). Under 2% O2, Rp was strongly suppressed, making the gross photorespiratory rate (RC = Rp + Rd) a reliable proxy for approximate Rd. Results showed that Rd estimates from the high-CO2/low-O2 approach (0.74–1.12 μmol m–2 s–1) were consistent with literature ranges (0.74–2.89 μmol m–2 s–1) for four C3 crops. Interspecific differences in Rd were observed: L. perenne had the highest Rd, while T. aestivum had the lowest, which correlated with species-specific photosynthetic traits (e.g., carboxylation efficiency). Rd remained stable across O2 levels (21% vs. 2%), indicating independence from short-term photorespiratory flux changes. The RC ≈ Rd assumption is supported by the substantial decrease in Γ (50–67%) and RCO (40–55%) under 2% O2, and by the consistency of Rd estimates with literature ranges, although independent ground-truth measurements remain to be conducted. This study suggests the high-CO2/low-O2 An/Ca model as a new tool for Rd quantification in C3 crops. The findings enhance understanding of non-photosynthetic carbon flux dynamics and provide critical parameters for refining crop carbon cycling models to predict growth and yield under current and future atmospheric conditions.