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.

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.

Great concern has long been raised about nitrate leaching in cropland due to its possible environmental side effects in ground water contamination. Here we employed two common techniques to measure nitrate leaching in tea plantation soils in subtropical China. Using drainage lysimeter as a reference method, the adaptability of estimating drainage and nitrate leaching by combining the water balance equation with the suction cup technique was investigated. Results showed that the final cumulative leachate volume for the calculated and measured method was 721.43 mm and 729.92 mm respectively during the study period. However, nitrate concentration exerted great influence in the estimation of nitrate leaching from the suction cup-based method. The cumulative nitrate leaching loss from the lysimeter and suction cup-based method was 47.45 kg ha⁻¹ and 43.58 kg ha⁻¹ under lysimeter nitrate concentrations ranging from 7 mg L⁻¹ to 13 mg L⁻¹, 156.28 kg ha⁻¹ and 79.95 kg ha⁻¹ under lysimeter nitrate concentrations exceeding 13 mg L⁻¹. Therefore, the suction cup-based method could be an alternative way of monitoring nitrate leaching loss within a range of 7–13 mg L⁻¹ of nitrate concentrations in leachate. Besides, lower results occurred in suction cup samplers due to lack of representative samples which mainly leached via preferential flow when in strong leaching events. Thus, it is advisable to increase sampling frequency under such special conditions. The results of this experiment can serve as a reference and guidance for the application of ceramic cups in monitoring nitrogen and other nutrient-ion leaching in tea plantation soils.

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

Selecting and breeding tea plant varieties with low nitrogen tolerance is crucial for reducing the application of nitrogen fertilizer in tea gardens and promoting the green and sustainable production of tea. Thus, a split-plot designed field experiment was conducted in a subtropical tea garden in China, where ten distinct cultivars were planted and exposed to two different levels of nitrogen (N) supply. This study aimed to assess the response of these cultivars to normal (450 kg ha⁻¹) and low (150 kg ha⁻¹) N fertilization treatments and to evaluate their tolerance to low N conditions. The results revealed notable differences in both the growth and biomass responses of the tea cultivars to N supply levels. Under low N supply, tea tree height, pruned litter biomass, and its nitrogen accumulation were all significantly lower than those under the normal N level. There was also a significant interaction effect between the cultivar and N level in the one-hundred-bud weight, new shoot yield, and its nitrogen content, respectively. The amount of total N uptake by harvested new shoots was relatively low, whereas a considerable amount of N was returned to the garden through pruned biomass. The aboveground biomass and its nitrogen accumulation could be considered as critical indicators for identifying nitrogen-tolerant cultivars with a variation coefficient by 20% and 20.57%, respectively. Additionally, cluster analysis showed that BY1 and LJ43 were strong low N-tolerant cultivars, while HJY was the most N-sensitive cultivar, closely followed by the ZN117 tea plants. In conclusion, significant disparities were observed in the adaptability of different tea cultivars to low N fertilization under the ambient field conditions. This study provided valuable theoretical insights and practical references for selecting N-tolerant tea varieties and reducing N fertilizer consumption in tea gardens.