Evolution of a biochemical model of steady-state photosynthesis

The Dynamic Assimilation Technique measures photosynthetic CO2 response curves with similar fidelity to steady-state approaches in half the time

The net CO2 assimilation (A) response to intercellular CO2 concentration (Ci) is a fundamental measurement in photosynthesis and plant physiology research. The conventional A/Ci protocols rely on steady-state measurements and take 15-40 min per measurement, limiting data resolution or biological replication. Additionally, there are several CO2 protocols employed across the literature, without clear consensus as to the optimal protocol or systematic biases in their estimations. We compared the non-steady-state Dynamic Assimilation Technique (DAT) protocol and the three most used CO2 protocols in steady-state measurements, and tested whether different CO2 protocols lead to systematic differences in estimations of the biochemical limitations to photosynthesis. The DAT protocol reduced the measurement time by almost half without compromising estimation accuracy or precision. The monotonic protocol was the fastest steady-state method. Estimations of biochemical limitations to photosynthesis were very consistent across all CO2 protocols, with slight differences in Rubisco carboxylation limitation. The A/Ci curves were not affected by the direction of the change of CO2 concentration but rather the time spent under triose phosphate utilization (TPU)-limited conditions. Our results suggest that the maximum rate of Rubisco carboxylation (Vcmax), linear electron flow for NADPH supply (J), and TPU measured using different protocols within the literature are comparable, or at least not systematically different based on the measurement protocol used.

Beyond the visible: Accounting for ultraviolet and far-red radiation in vegetation productivity and surface energy budgets

Photosynthetically active radiation (PAR) is typically defined as light with a wavelength within 400-700 nm. However, ultra-violet (UV) radiation within 280-400 nm and far-red (FR) radiation within 700-750 nm can also excite photosystems, though not as efficiently as PAR. Vegetation and land surface models (LSMs) typically do not explicitly account for UV's contribution to energy budgets or photosynthesis, nor FR's contribution to photosynthesis. However, whether neglecting UV and FR has significant impacts remains unknown. We explored how canopy radiative transfer (RT) and photosynthesis are impacted when explicitly implementing UV in the canopy RT model and accounting for UV and FR in the photosynthesis models within a next-generation LSM that can simulate hyperspectral canopy RT. We validated our improvements using photosynthesis measurements from plants under different light sources and intensities and surface reflection from an eddy-covariance tower. Our model simulations suggested that at the whole plant level, after accounting for UV and FR explicitly, chlorophyll content, leaf area index (LAI), clumping index, and solar radiation all impact the modeling of gross primary productivity (GPP). At the global scale, mean annual GPP within a grid would increase by up to 7.3% and the increase is proportional to LAI; globally integrated GPP increases by 4.6 PgC year-1 (3.8% of the GPP without accounting for UV + FR). Further, using PAR to proxy UV could overestimate surface albedo by more than 0.1, particularly in the boreal forests. Our results highlight the importance of improving UV and FR in canopy RT and photosynthesis modeling and the necessity to implement hyperspectral or multispectral canopy RT schemes in future vegetation and LSMs.

From leaf to multiscale models of photosynthesis: applications and challenges for crop improvement

To keep up with the growth of human population and to circumvent deleterious effects of global climate change, it is essential to enhance crop yield to achieve higher production. Here we review mathematical models of oxygenic photosynthesis that are extensively used, and discuss in depth a subset that accounts for diverse approaches providing solutions to our objective. These include models (1) to study different ways to enhance photosynthesis, such as fine-tuning antenna size, photoprotection and electron transport; (2) to bioengineer carbon metabolism; and (3) to evaluate the interactions between the process of photosynthesis and the seasonal crop dynamics, or those that have included statistical whole-genome prediction methods to quantify the impact of photosynthesis traits on the improvement of crop yield. We conclude by emphasizing that the results obtained in these studies clearly demonstrate that mathematical modelling is a key tool to examine different approaches to improve photosynthesis for better productivity, while effective multiscale crop models, especially those that also include remote sensing data, are indispensable to verify different strategies to obtain maximized crop yields.

Simulating short-term light responses of photosynthesis and water use efficiency in sweet sorghum under varying temperature and CO2 conditions

Climate change, characterized by rising atmospheric CO2 levels and temperatures, poses significant challenges to global crop production. Sweet sorghum, a prominent C4 cereal extensively grown in arid areas, emerges as a promising candidate for sustainable bioenergy production. This study investigated the responses of photosynthesis and leaf-scale water use efficiency (WUE) to varying light intensity (I) in sweet sorghum under different temperature and CO2 conditions. Comparative analyses were conducted between the A n-I, g s-I, T r-I, WUEi-I, and WUEinst-I models proposed by Ye et al. and the widely utilized the non-rectangular hyperbolic (NRH) model for fitting light response curves. The Ye's models effectively replicated the light response curves of sweet sorghum, accurately capturing the diminishing intrinsic WUE (WUEi) and instantaneous WUE (WUEinst) trends with increasing I. The fitted maximum values of A n, g s, T r, WUEi, and WUEinst and their saturation light intensities closely matched observations, unlike the NRH model. Despite the NRH model demonstrating high R 2 values for A n-I, g s-I, and T r-I modelling, it returned the maximum values significantly deviating from observed values and failed to generate saturation light intensities. It also inadequately represented WUE responses to I, overestimating WUE. Across different leaf temperatures, A n, g s, and T r of sweet sorghum displayed comparable light response patterns. Elevated temperatures increased maximum A n, g s, and T r but consistently declined maximum WUEi and WUEinst. However, WUEinst declined more sharply due to the disproportionate transpiration increase over carbon assimilation. Critically, sweet sorghum A n saturated at current atmospheric CO2 levels, with no significant gains under 550 μmol mol-1. Instead, stomatal closure enhanced WUE under elevated CO2 by coordinated g s and T r reductions rather than improved carbon assimilation. Nonetheless, this response diminished under simultaneously high temperature, suggesting intricate interplay between CO2 and temperature in modulating plant responses. These findings provide valuable insights into photosynthetic dynamics of sweet sorghum, aiding predictions of yield and optimization of cultivation practices. Moreover, our methodology serves as a valuable reference for evaluating leaf photosynthesis and WUE dynamics in diverse plant species.

The role of metabolomics in informing strategies for improving photosynthesis

Photosynthesis plays a vital role in acclimating to and mitigating climate change, providing food and energy security for a population that is constantly growing, and achieving an economy with zero carbon emissions. A thorough comprehension of the dynamics of photosynthesis, including its molecular regulatory network and limitations, is essential for utilizing it as a tool to boost plant growth, enhance crop yields, and support the production of plant biomass for carbon storage. Photorespiration constrains photosynthetic efficiency and contributes significantly to carbon loss. Therefore, modulating or circumventing photorespiration presents opportunities to enhance photosynthetic efficiency. Over the past eight decades, substantial progress has been made in elucidating the molecular basis of photosynthesis, photorespiration, and the key regulatory mechanisms involved, beginning with the discovery of the canonical Calvin-Benson-Bassham cycle. Advanced chromatographic and mass spectrometric technologies have allowed a comprehensive analysis of the metabolite patterns associated with photosynthesis, contributing to a deeper understanding of its regulation. In this review, we summarize the results of metabolomics studies that shed light on the molecular intricacies of photosynthetic metabolism. We also discuss the methodological requirements essential for effective analysis of photosynthetic metabolism, highlighting the value of this technology in supporting strategies aimed at enhancing photosynthesis.

Addressing the long-standing limitations of double exponential and non-rectangular hyperbolic models in quantifying light-response of electron transport rates in different photosynthetic organisms under various 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 fit J-I curves, and determine the values of J max and I 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 fit J-I curves and estimate J max and I sat. Here, we apply these three models to a series of previously collected Chl a fluorescence data from seven photosynthetic organisms, grown under different conditions. Our results show that the mechanistic model performed well in describing the J-I curves, regardless of whether photoinhibition/dynamic down-regulation of photosystem II (PSII) occurs. Moreover, both J max and I sat estimated by this model are in very good agreement with the measured data. On the contrary, although the DE model simulates quite well the J-I curve for the species studied, it significantly overestimates both the J max of Amaranthus hypochondriacus and the I sat of Microcystis aeruginosa grown under NH4 +-N supply. More importantly, the light intensity required to achieve the potential maximum of J (J s) estimated by this model exceeds the unexpected high value of 105 μmol photons m-2 s-1 for Triticum aestivum and A. hypochondriacus. The NRH model fails to characterize the J-I curves with dynamic down-regulation/photoinhibition for Abies alba, Oryza sativa and M. aeruginosa. In addition, this model also significantly overestimates the values of J max for T. aestivum at 21% O2 and A. hypochondriacus grown under normal condition, and significantly underestimates the values of J max for M. aeruginosa grown 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 the J-I curves and in estimating the photosynthetic parameters. This is a powerful tool for studying light harvesting properties and the dynamic down-regulation of PSII/photoinhibition.

A guide to photosynthetic gas exchange measurements: Fundamental principles, best practice and potential pitfalls

Gas exchange measurements enable mechanistic insights into the processes that underpin carbon and water fluxes in plant leaves which in turn inform understanding of related processes at a range of scales from individual cells to entire ecosytems. Given the importance of photosynthesis for the global climate discussion it is important to (a) foster a basic understanding of the fundamental principles underpinning the experimental methods used by the broad community, and (b) ensure best practice and correct data interpretation within the research community. In this review, we outline the biochemical and biophysical parameters of photosynthesis that can be investigated with gas exchange measurements and we provide step-by-step guidance on how to reliably measure them. We advise on best practices for using gas exchange equipment and highlight potential pitfalls in experimental design and data interpretation. The Supporting Information contains exemplary data sets, experimental protocols and data-modelling routines. This review is a community effort to equip both the experimental researcher and the data modeller with a solid understanding of the theoretical basis of gas-exchange measurements, the rationale behind different experimental protocols and the approaches to data interpretation.

Estimating leaf day respiration from conventional gas exchange measurements

Leaf day respiration (Rd ) strongly influences carbon-use efficiencies of whole plants and the global terrestrial biosphere. It has long been thought that Rd is slower than respiration in the dark at a given temperature, but measuring Rd by gas exchange remains a challenge because leaves in the light are also photosynthesizing. The Kok method and the Laisk method are widely used to estimate Rd . We highlight theoretical limitations of these popular methods, and recent progress toward their improvement by using additional information from chlorophyll fluorescence and by accounting for the photosynthetic reassimilation of respired CO2 . The latest evidence for daytime CO2 and energy release from the oxidative pentose phosphate pathway in chloroplasts appears to be important to understanding Rd .

Triose phosphate utilization in leaves is modulated by whole-plant sink-source ratios and nitrogen budgets in rice

Triose phosphate utilization (TPU) is a biochemical process indicating carbon sink-source (im)balance within leaves. When TPU limits leaf photosynthesis, photorespiration-associated amino acid exports probably provide an additional carbon outlet and increase leaf CO2 uptake. However, whether TPU is modulated by whole-plant sink-source relations and nitrogen (N) budgets remains unclear. We address this question by model analyses of gas-exchange data measured on leaves at three growth stages of rice plants grown at two N levels. Sink-source ratio was manipulated by panicle pruning, by using yellower-leaf variant genotypes, and by measuring photosynthesis on adaxial and abaxial leaf sides. Across all these treatments, higher leaf N content resulted in the occurrence of TPU limitation at lower intercellular CO2 concentrations. Photorespiration-associated amino acid export was greater in high-N leaves, but was smaller in yellower-leaf genotypes, panicle-pruned plants, and for abaxial measurement. The feedback inhibition of panicle pruning on rates of TPU was not always observed, presumably because panicle pruning blocked N remobilization from leaves to grains and the increased leaf N content masked feedback inhibition. The leaf-level TPU limitation was thus modulated by whole-plant sink-source relations and N budgets during rice grain filling, suggesting a close link between within-leaf and whole-plant sink limitations.

Crop/Plant Modeling Supports Plant Breeding: II. Guidance of Functional Plant Phenotyping for Trait Discovery

Observable morphological traits are widely employed in plant phenotyping for breeding use, which are often the external phenotypes driven by a chain of functional actions in plants. Identifying and phenotyping inherently functional traits for crop improvement toward high yields or adaptation to harsh environments remains a major challenge. Prediction of whole-plant performance in functional-structural plant models (FSPMs) is driven by plant growth algorithms based on organ scale wrapped up with micro-environments. In particular, the models are flexible for scaling down or up through specific functions at the organ nexus, allowing the prediction of crop system behaviors from the genome to the field. As such, by virtue of FSPMs, model parameters that determine organogenesis, development, biomass production, allocation, and morphogenesis from a molecular to the whole plant level can be profiled systematically and made readily available for phenotyping. FSPMs can provide rich functional traits representing biological regulatory mechanisms at various scales in a dynamic system, e.g., Rubisco carboxylation rate, mesophyll conductance, specific leaf nitrogen, radiation use efficiency, and source-sink ratio apart from morphological traits. High-throughput phenotyping such traits is also discussed, which provides an unprecedented opportunity to evolve FSPMs. This will accelerate the co-evolution of FSPMs and plant phenomics, and thus improving breeding efficiency. To expand the great promise of FSPMs in crop science, FSPMs still need more effort in multiscale, mechanistic, reproductive organ, and root system modeling. In summary, this study demonstrates that FSPMs are invaluable tools in guiding functional trait phenotyping at various scales and can thus provide abundant functional targets for phenotyping toward crop improvement.

Development of Modified Farquhar-von Caemmerer-Berry Model Describing Photodamage of Photosynthetic Electron Transport in C3 Plants under Different Temperatures

Photodamage of photosynthetic electron transport is a key mechanism of disruption of photosynthesis in plants under action of stressors. This means that investigation of photodamage is an important task for basic and applied investigations. However, its complex mechanisms restrict using experimental methods of investigation for this process; the development of mathematical models of photodamage and model-based analysis can be used for overcoming these restrictions. In the current work, we developed the modified Farquhar-von Caemmerer-Berry model which describes photodamage of photosynthetic electron transport in C3 plants. This model was parameterized on the basis of experimental results (using an example of pea plants). Analysis of the model showed that combined inactivation of linear electron flow and Rubisco could induce both increasing and decreasing photodamage at different magnitudes of inactivation of these processes. Simulation of photodamage under different temperatures and light intensities showed that simulated temperature dependences could be multi-phase; particularly, paradoxical increases in the thermal tolerance of photosynthetic electron transport could be observed under high temperatures (37-42 °C). Finally, it was shown that changes in temperature optimums of linear electron flow and Rubisco could modify temperature dependences of the final activity of photosynthetic electron transport under photodamage induction; however, these changes mainly stimulated its photodamage. Thus, our work provides a new theoretical tool for investigation of photodamage of photosynthetic processes in C3 plants and shows that this photodamage can be intricately dependent on parameters of changes in activities of linear electron flow and Rubisco including changes induced by temperature.

Toward mechanistic modeling and rational engineering of plant respiration

Plant respiration not only provides energy to support all cellular processes, including biomass production, but also plays a major role in the global carbon cycle. Therefore, modulation of plant respiration can be used to both increase the plant yield and mitigate the effects of global climate change. Mechanistic modeling of plant respiration at sufficient biochemical detail can provide key insights for rational engineering of this process. Yet, despite its importance, plant respiration has attracted considerably less modeling effort in comparison to photosynthesis. In this update review, we highlight the advances made in modeling of plant respiration, emphasizing the gradual but important change from phenomenological to models based on first principles. We also provide a detailed account of the existing resources that can contribute to resolving the challenges in modeling plant respiration. These resources point at tangible improvements in the representation of cellular processes that contribute to CO2 evolution and consideration of kinetic properties of underlying enzymes to facilitate mechanistic modeling. The update review emphasizes the need to couple biochemical models of respiration with models of acclimation and adaptation of respiration for their effective usage in guiding breeding efforts and improving terrestrial biosphere models tailored to future climate scenarios.

Characterization of physiological and antioxidant responses in Run1Ren1 Vitis vinifera plants during Erysiphe necator attack

Grapevine is a fruit crop of major significance worldwide. Fungal attacks are one of the most relevant factors affecting grapevine yield and fruit quality, and powdery mildew caused by Erysiphe necator is one of the most harmful fungal diseases for this fruit-bearing species. Incorporating resistance genes such as Run1 and Ren1 in new vine selections offers a sustainable alternative to control the disease. These combined loci produce an immune response that prevents the development of the disease. However, to date studies are lacking concerning whether this response generates alterations in the physiological and antioxidant parameters of resistant plants in the presence of the fungus or if it has an associated energy cost. Therefore, the main goal of our research was to determine if Run1Ren1 plants present alterations in their physiological and biochemical parameters in the presence of the fungus. To achieve this target, a previously characterized resistant Run1Ren1 genotype and the susceptible Carménère cultivar were analyzed. We evaluated photochemical parameters (Fv'/Fm', ΦPSII and ETR), net photosynthesis (Pn), photosynthetic pigments, transpiration (E), stomatal conductance (g_s ), oxidative stress parameters (MDA), antioxidant activity, and phenols. Our results show that the physiological parameters of Run1Ren1 plants were not negatively affected by the fungus at 10 days post-inoculation, contrasting with alterations observed in the susceptible plants. Therefore, we propose that the resistance response triggered by Run1Ren1 is physiologically and biochemically advantageous to grapevines by preventing the development of powdery mildew infection.

Drought exerts a greater influence than growth temperature on the temperature response of leaf day respiration in wheat (Triticum aestivum)

We assessed how the temperature response of leaf day respiration (R_d ) in wheat responded to contrasting water regimes and growth temperatures. In Experiment 1, well-watered and drought-stressed conditions were imposed on two genotypes; in Experiment 2, the two water regimes combined with high (HT), medium (MT) and low (LT) growth temperatures were imposed on one of the genotypes. R_d was estimated from simultaneous gas exchange and chlorophyll fluorescence measurements at six leaf temperatures (T_leaf ) for each treatment, using the Yin method for nonphotorespiratory conditions and the nonrectangular hyperbolic fitting method for photorespiratory conditions. The two genotypes responded similarly to growth and measurement conditions. Estimates of R_d for nonphotorespiratory conditions were generally higher than those for photorespiratory conditions, but their responses to T_leaf were similar. Under well-watered conditions, R_d and its sensitivity to T_leaf slightly acclimated to LT, but did not acclimate to HT. Temperature sensitivities of R_d were considerably suppressed by drought, and the suppression varied among growth temperatures. Thus, it is necessary to quantify interactions between drought and growth temperature for reliably modelling R_d under climate change. Our study also demonstrated that the Kok method, one of the currently popular methods for estimating R_d , underestimated R_d significantly.

A model-guided holistic review of exploiting natural variation of photosynthesis traits in crop improvement

Breeding for improved leaf photosynthesis is considered as a viable approach to increase crop yield. Whether it should be improved in combination with other traits has not been assessed critically. Based on the quantitative crop model GECROS that interconnects various traits to crop productivity, we review natural variation in relevant traits, from biochemical aspects of leaf photosynthesis to morpho-physiological crop characteristics. While large phenotypic variations (sometimes >2-fold) for leaf photosynthesis and its underlying biochemical parameters were reported, few quantitative trait loci (QTL) were identified, accounting for a small percentage of phenotypic variation. More QTL were reported for sink size (that feeds back on photosynthesis) or morpho-physiological traits (that affect canopy productivity and duration), together explaining a much greater percentage of their phenotypic variation. Traits for both photosynthetic rate and sustaining it during grain filling were strongly related to nitrogen-related traits. Much of the molecular basis of known photosynthesis QTL thus resides in genes controlling photosynthesis indirectly. Simulation using GECROS demonstrated the overwhelming importance of electron transport parameters, compared with the maximum Rubisco activity that largely determines the commonly studied light-saturated photosynthetic rate. Exploiting photosynthetic natural variation might significantly improve crop yield if nitrogen uptake, sink capacity, and other morpho-physiological traits are co-selected synergistically.

Inference of photosynthetic capacity parameters from chlorophyll a fluorescence is affected by redox state of PSII reaction centers

Solar-induced chlorophyll fluorescence (SIF) has been used to infer photosynthetic capacity parameters (e.g., the maximum carboxylation rate V_cmax , and the maximum electron transport rate J_max ). However, the precise mechanism and practical utility of such approach under dynamic environments remain unclear. We used the balance between the light and carbon reactions to derive theoretical equations relating chlorophyll a fluorescence (ChlF) emission and photosynthetic capacity parameters, and formulated testable hypotheses regarding the dynamic relationships between the true total ChlF emitted from PSII (SIF_PSII ) and V_cmax and J_max . We employed concurrent measurements of gas exchanges and ChlF parameters for 15 species from six biomes to test the formulated hypotheses across species, temperatures, and limitation state of carboxylation. Our results revealed that SIF_PSII alone is incapable of informing the variations in V_cmax and J_max across species, even when SIF_PSII is determined under the same environmental conditions. In contrast, the product of SIF_PSII and the fraction of open PSII reactions q_L , which indicates the redox state of PSII, is a strong predictor of both V_cmax and J_max , although their precise relationships vary somewhat with environmental conditions. Our findings suggest the redox state of PSII strongly influences the relationship between SIF_PSII and V_cmax and J_max .

Advances in optical phenotyping of cereal crops

Optical sensors and sensing-based phenotyping techniques have become mainstream approaches in high-throughput phenotyping for improving trait selection and genetic gains in crops. We review recent progress and contemporary applications of optical sensing-based phenotyping (OSP) techniques in cereal crops and highlight optical sensing principles for spectral response and sensor specifications. Further, we group phenotypic traits determined by OSP into four categories - morphological, biochemical, physiological, and performance traits - and illustrate appropriate sensors for each extraction. In addition to the current status, we discuss the challenges of OSP and provide possible solutions. We propose that optical sensing-based traits need to be explored further, and that standardization of the language of phenotyping and worldwide collaboration between phenotyping researchers and other fields need to be established.