Quantifying impacts of enhancing photosynthesis on crop yield

A dose-dependent effect of UV-328 on photosynthesis: Exploring light harvesting and UV-B sensing mechanisms

Benzotriazole ultraviolet (UV) stabilizers (BUVs) have emerged as significant environmental contaminants, frequently detected in various ecosystems. While the toxicity of BUVs to aquatic organisms is well-documented, studies on their impact on plant life are scarce. Plants are crucial as they provide the primary source of energy and organic matter in ecosystems through photosynthesis. This study investigated the effects of UV-328 (2-(2-hydroxy-4',6'-di-tert-amylphenyl) benzotriazole) on plant growth indices and photosynthesis processes, employing conventional physiological experiments, RNA sequencing (RNA-seq) analysis, and computational methods. Results demonstrated a biphasic response in plant biomass and the maximum quantum yield of PS II (Fv/Fm), showing improvement at a 50 μM UV-328 treatment but reduction under 150 μM UV-328 exposure. Additionally, disruption in thylakoid morphology was observed at the higher concentration. RNA-seq and qRT-PCR analysis identified key differentially expressed genes (light-harvesting chlorophyll-protein complex Ⅰ subunit A4, light-harvesting chlorophyll b-binding protein 3, UVR8, and curvature thylakoid 1 A) related to photosynthetic light harvesting, UV-B sensing, and chloroplast structure pathways, suggesting they may contribute to the observed alterations in photosynthesis activity induced by UV-328 exposure. Molecular docking analyses further supported the binding affinity between these proteins and UV-328. Overall, this study provided comprehensive physiological and molecular insights, contributing valuable information to the evaluation of the potential risks posed by UV-328 to critical plant physiological processes.

Atmospheric drought dominates changes in global water use efficiency

Water use efficiency (defined as the ratio of gross primary productivity to plant transpiration, WUET) describes the tradeoff between ecosystem carbon uptake and water loss. However, a comprehensive understanding of the impact of soil and atmospheric moisture deficits on WUET across large regions remains incomplete. Solar-induced chlorophyll fluorescence (SIF) serves as an effective signal for measuring both terrestrial vegetation photosynthesis and transpiration, thereby enabling a rapid response to changes in the physiological status of plants under water stress. The objectives of this study were to: 1) mechanistically calculate WUET using top-of-canopy SIF data and meteorological information by using the revised mechanistic light response model and the Penman-Monteith equation; 2) analyze the effects of atmospheric and soil water deficits on SIF-based WUET by using decoupled soil water content (SWC) and vapor pressure deficit (VPD); 3) evaluate estimated SIF-based WUET against data from 28 eddy covariance (EC) flux sites representing eight different vegetation types. Results indicated that the model performed well in ecosystems with dense canopies, explaining 56 % of the daily variability in EC tower-based WUET. For the years 2019-2020, the global average WUET derived from SIF was 3.49 g C/kg H2O. Notably, this value exceeded 4 g C/kg H2O in tropical rainforest regions near the equator and went beyond 5 g C/kg H2O in the high-latitude regions of the Northern Hemisphere. We found that SIF-based WUET was primarily influenced by VPD rather than SWC in over 90 % of the global vegetated area. The model used in this study increased our ability to mechanistically estimate WUET with SIF at the global scale, thereby highlighting the significance of the global response of SIF-based WUET to water stress, and also enhancing our understanding of the water‑carbon cycle in terrestrial ecosystems.

Modulation of Photosystem II Function in Celery via Foliar-Applied Salicylic Acid during Gradual Water Deficit Stress

Water deficit is the major stress factor magnified by climate change that causes the most reductions in plant productivity. Knowledge of photosystem II (PSII) response mechanisms underlying crop vulnerability to drought is critical to better understanding the consequences of climate change on crop plants. Salicylic acid (SA) application under drought stress may stimulate PSII function, although the exact mechanism remains essentially unclear. To reveal the PSII response mechanism of celery plants sprayed with water (WA) or SA, we employed chlorophyll fluorescence imaging analysis at 48 h, 96 h, and 192 h after watering. The results showed that up to 96 h after watering, the stroma lamellae of SA-sprayed leaves appeared dilated, and the efficiency of PSII declined, compared to WA-sprayed plants, which displayed a better PSII function. However, 192 h after watering, the stroma lamellae of SA-sprayed leaves was restored, while SA boosted chlorophyll synthesis, and by ameliorating the osmotic potential of celery plants, it resulted in higher relative leaf water content compared to WA-sprayed plants. SA, by acting as an antioxidant under drought stress, suppressed phototoxicity, thereby offering PSII photoprotection, together with enhanced effective quantum yield of PSII photochemistry (ΦPSII) and decreased quantity of singlet oxygen (1O2) generation compared to WA-sprayed plants. The PSII photoprotection mechanism induced by SA under drought stress was triggered by non-photochemical quenching (NPQ), which is a strategy to protect the chloroplast from photo-oxidative damage by dissipating the excess light energy as heat. This photoprotective mechanism, triggered by NPQ under drought stress, was adequate in keeping, especially in high-light conditions, an equal fraction of open PSII reaction centers (qp) as of non-stress conditions. Thus, under water deficit stress, SA activates a regulatory network of stress and light energy partitioning signaling that can mitigate, to an extent, the water deficit stress on PSII functioning.

Transcriptome analysis reveals the key role of overdominant expression of photosynthetic and respiration-related genes in the formation of tobacco(Nicotiana tabacum L.) biomass heterosis

BACKGROUND

Leaves are the nutritional and economic organs of tobacco, and their biomass directly affects tobacco yield and the economic benefits of farmers. In the early stage, our research found that tobacco hybrids have more leaves and larger leaf areas, but the performance and formation reasons of biomass heterosis are not yet clear.

RESULTS

This study selected 5 parents with significant differences in tobacco biomass and paired them with hybrid varieties. It was found that tobacco hybrid varieties have a common biomass heterosis, and 45 days after transplantation is the key period for the formation of tobacco biomass heterosis; By analyzing the biomass heterosis of hybrids, Va116×GDH94 and its parents were selected for transcriptome analysis. 76.69% of the differentially expressed genes between Va116×GDH94 and its parents showed overdominant expression pattern, and these overdominant expression genes were significantly enriched in the biological processes of photosynthesis and TCA cycle; During the process of photosynthesis, the overdominant up-regulation of genes such as Lhc, Psa, and rbcl promotes the progress of photosynthesis, thereby increasing the accumulation of tobacco biomass; During the respiratory process, genes such as MDH, ACO, and OGDH are overedominantly down-regulated, inhibiting the TCA cycle and reducing substrate consumption in hybrid offspring; The photosynthetic characteristics of the hybrid and its parents were measured, and the net photosynthetic capacity of the hybrid was significantly higher than that of the parents.

CONCLUSION

These results indicate that the overdominant expression effect of differentially expressed genes in Va116×GDH94 and its parents plays a crucial role in the formation of tobacco biomass heterosis. The overdominant expression of genes related to photosynthesis and respiration enhances the photosynthetic ability of Va116×GDH94, reduces respiratory consumption, promotes the increase of biomass, and exhibits obvious heterosis.

Estimation of Photosynthetic Induction Is Significantly Affected by Light Environments of Local Leaves and Whole Plants in Oryza Genus

Photosynthetic induction and stomatal kinetics are acknowledged as pivotal factors in regulating both plant growth and water use efficiency under fluctuating light conditions. However, the considerable variability in methodologies and light regimes used to assess the dynamics of photosynthesis (A) and stomatal conductance (gs) during light induction across studies poses challenges for comparison across species. Moreover, the influence of stomatal morphology on both steady-state and non-steady-state gs remains poorly understood. In this study, we show the strong impact of IRGA Chamber Illumination and Whole Plant Illumination on the photosynthetic induction of two rice species. Our findings reveal that these illuminations significantly enhance photosynthetic induction by modulating both stomatal and biochemical processes. Moreover, we observed that a higher density of smaller stomata plays a critical role in enhancing the stomatal opening and photosynthetic induction to fluctuating light conditions, although it exerts minimal influence on steady-state gs and A under constant light conditions. Therefore, future studies aiming to estimate photosynthetic induction and stomatal kinetics should consider the light environments at both the leaf and whole plant levels.

The long and tortuous path towards improving photosynthesis by engineering elevated mesophyll conductance

The growing demand for global food production is likely to be a defining issue facing humanity over the next 50 years. To tackle this challenge, there is a desire to bioengineer crops with higher photosynthetic efficiencies, to increase yields. Recently, there has been a growing interest in engineering leaves with higher mesophyll conductance (gm), which would allow CO2 to move more efficiently from the substomatal cavities to the chloroplast stroma. However, if crop yield gains are to be realised through this approach, it is essential that the methodological limitations associated with estimating gm are fully appreciated. In this review, we summarise these limitations, and outline the uncertainties and assumptions that can affect the final estimation of gm. Furthermore, we critically assess the predicted quantitative effect that elevating gm will have on assimilation rates in crop species. We highlight the need for more theoretical modelling to determine whether altering gm is truly a viable route to improve crop performance. Finally, we offer suggestions to guide future research on gm, which will help mitigate the uncertainty inherently associated with estimating this parameter.

Mechanistic Insights on Salicylic Acid-Induced Enhancement of Photosystem II Function in Basil Plants under Non-Stress or Mild Drought Stress

Photosystem II (PSII) functions were investigated in basil (Ocimum basilicum L.) plants sprayed with 1 mM salicylic acid (SA) under non-stress (NS) or mild drought-stress (MiDS) conditions. Under MiDS, SA-sprayed leaves retained significantly higher (+36%) chlorophyll content compared to NS, SA-sprayed leaves. PSII efficiency in SA-sprayed leaves under NS conditions, evaluated at both low light (LL, 200 μmol photons m-2 s-1) and high light (HL, 900 μmol photons m-2 s-1), increased significantly with a parallel significant decrease in the excitation pressure at PSII (1-qL) and the excess excitation energy (EXC). This enhancement of PSII efficiency under NS conditions was induced by the mechanism of non-photochemical quenching (NPQ) that reduced singlet oxygen (1O2) production, as indicated by the reduced quantum yield of non-regulated energy loss in PSII (ΦNO). Under MiDS, the thylakoid structure of water-sprayed leaves appeared slightly dilated, and the efficiency of PSII declined, compared to NS conditions. In contrast, the thylakoid structure of SA-sprayed leaves did not change under MiDS, while PSII functionality was retained, similar to NS plants at HL. This was due to the photoprotective heat dissipation by NPQ, which was sufficient to retain the same percentage of open PSII reaction centers (qp), as in NS conditions and HL. We suggest that the redox status of the plastoquinone pool (qp) under MiDS and HL initiated the acclimation response to MiDS in SA-sprayed leaves, which retained the same electron transport rate (ETR) with control plants. Foliar spray of SA could be considered as a method to improve PSII efficiency in basil plants under NS conditions, at both LL and HL, while under MiDS and HL conditions, basil plants could retain PSII efficiency similar to control plants.

The importance of species-specific and temperature-sensitive parameterisation of A/Ci models: A case study using cotton (Gossypium hirsutum L.) and the automated 'OptiFitACi' R-package

Leaf gas exchange measurements are an important tool for inferring a plant's photosynthetic biochemistry. In most cases, the responses of photosynthetic CO2 assimilation to variable intercellular CO2 concentrations (A/Ci response curves) are used to model the maximum (potential) rate of carboxylation by ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco, Vcmax) and the rate of photosynthetic electron transport at a given incident photosynthetically active radiation flux density (PAR; JPAR). The standard Farquhar-von Caemmerer-Berry model is often used with default parameters of Rubisco kinetic values and mesophyll conductance to CO2 (gm) derived from tobacco that may be inapplicable across species. To study the significance of using such parameters for other species, here we measured the temperature responses of key in vitro Rubisco catalytic properties and gm in cotton (Gossypium hirsutum cv. Sicot 71) and derived Vcmax and J2000 (JPAR at 2000 µmol m-2 s-1 PAR) from cotton A/Ci curves incrementally measured at 15°C-40°C using cotton and other species-specific sets of input parameters with our new automated fitting R package 'OptiFitACi'. Notably, parameterisation by a set of tobacco parameters produced unrealistic J2000:Vcmax ratio of <1 at 25°C, two- to three-fold higher estimates of Vcmax above 15°C, up to 2.3-fold higher estimates of J2000 and more variable estimates of Vcmax and J2000, for our cotton data compared to model parameterisation with cotton-derived values. We determined that errors arise when using a gm,25 of 2.3 mol m-2 s-1 MPa-1 or less and Rubisco CO2-affinities in 21% O2 (KC 21%O2) at 25°C outside the range of 46-63 Pa to model A/Ci responses in cotton. We show how the A/Ci modelling capabilities of 'OptiFitACi' serves as a robust, user-friendly, and flexible extension of 'plantecophys' by providing simplified temperature-sensitivity and species-specificity parameterisation capabilities to reduce variability when modelling Vcmax and J2000.

Deep learning-based association analysis of root image data and cucumber yield

The root system is important for the absorption of water and nutrients by plants. Cultivating and selecting a root system architecture (RSA) with good adaptability and ultrahigh productivity have become the primary goals of agricultural improvement. Exploring the correlation between the RSA and crop yield is important for cultivating crop varieties with high-stress resistance and productivity. In this study, 277 cucumber varieties were collected for root system image analysis and yield using germination plates and greenhouse cultivation. Deep learning tools were used to train ResNet50 and U-Net models for image classification and segmentation of seedlings and to perform quality inspection and productivity prediction of cucumber seedling root system images. The results showed that U-Net can automatically extract cucumber root systems with high quality (F1_score ≥ 0.95), and the trained ResNet50 can predict cucumber yield grade through seedling root system image, with the highest F1_score reaching 0.86 using 10-day-old seedlings. The root angle had the strongest correlation with yield, and the shallow- and steep-angle frequencies had significant positive and negative correlations with yield, respectively. RSA and nutrient absorption jointly affected the production capacity of cucumber plants. The germination plate planting method and automated root system segmentation model used in this study are convenient for high-throughput phenotypic (HTP) research on root systems. Moreover, using seedling root system images to predict yield grade provides a new method for rapidly breeding high-yield RSA in crops such as cucumbers.

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.

Contrasting leaf-scale photosynthetic low-light response and its temperature dependency are key to differences in crop-scale radiation use efficiency

Radiation use efficiency (RUE) is a key crop adaptation trait that quantifies the potential amount of aboveground biomass produced by the crop per unit of solar energy intercepted. But it is unclear why elite maize and grain sorghum hybrids differ in their RUE at the crop level. Here, we used a non-traditional top-down approach via canopy photosynthesis modelling to identify leaf-level photosynthetic traits that are key to differences in crop-level RUE. A novel photosynthetic response measurement was developed and coupled with use of a Bayesian model fitting procedure, incorporating a C4 leaf photosynthesis model, to infer cohesive sets of photosynthetic parameters by simultaneously fitting responses to CO2 , light, and temperature. Statistically significant differences between leaf photosynthetic parameters of elite maize and grain sorghum hybrids were found across a range of leaf temperatures, in particular for effects on the quantum yield of photosynthesis, but also for the maximum enzymatic activity of Rubisco and PEPc. Simulation of diurnal canopy photosynthesis predicted that the leaf-level photosynthetic low-light response and its temperature dependency are key drivers of the performance of crop-level RUE, generating testable hypotheses for further physiological analysis and bioengineering applications.

Flexible and Stretchable Light-Emitting Diodes and Photodetectors for Human-Centric Optoelectronics

Optoelectronic devices with unconventional form factors, such as flexible and stretchable light-emitting or photoresponsive devices, are core elements for the next-generation human-centric optoelectronics. For instance, these deformable devices can be utilized as closely fitted wearable sensors to acquire precise biosignals that are subsequently uploaded to the cloud for immediate examination and diagnosis, and also can be used for vision systems for human-interactive robotics. Their inception was propelled by breakthroughs in novel optoelectronic material technologies and device blueprinting methodologies, endowing flexibility and mechanical resilience to conventional rigid optoelectronic devices. This paper reviews the advancements in such soft optoelectronic device technologies, honing in on various materials, manufacturing techniques, and device design strategies. We will first highlight the general approaches for flexible and stretchable device fabrication, including the appropriate material selection for the substrate, electrodes, and insulation layers. We will then focus on the materials for flexible and stretchable light-emitting diodes, their device integration strategies, and representative application examples. Next, we will move on to the materials for flexible and stretchable photodetectors, highlighting the state-of-the-art materials and device fabrication methods, followed by their representative application examples. At the end, a brief summary will be given, and the potential challenges for further development of functional devices will be discussed as a conclusion.

Hyperspectral Proximal Sensing for Estimating Photosynthetic Capacities at Leaf and Canopy Scales

Agronomists, plant breeders, and plant biologists have been promoting the need to develop high-throughput methods to measure plant traits of interest for decades. Measuring these plant traits or phenotypes is often a bottleneck since skilled personnel, resources, and ample time are required. Additionally, plant phenotypic traits from only a select number of breeding lines or varieties can be quantified because the "gold standard" measurement of a desired trait cannot be completed in a timely manner. As such, numerous approaches have been developed and implemented to better understand the biology and production of crops and ecosystems. In this chapter, we explain one of the recent approaches leveraging hyperspectral measurements to estimate different aspects of photosynthesis. Notably, we outline the use of hyperspectral radiometer and imaging to rapidly estimate two of the rate-limiting steps of photosynthesis: the maximum rate of the carboxylation of Rubisco (Vcmax) and the maximum rate of electron transfer or regeneration of RuBP (Jmax).

Physiological and Proteomic Changes in Camellia semiserrata in Response to Aluminum Stress

Camellia semiserrata is an important woody edible oil tree species in southern China that is characterized by large fruits and seed kernels with high oil contents. Increasing soil acidification due to increased use of fossil fuels, misuse of acidic fertilizers, and irrational farming practices has led to leaching of aluminum (Al) in the form of free Al3+, Al(OH)2+, and Al(OH)2+, which inhibits the growth and development of C. semiserrata in South China. To investigate the mechanism underlying C. semiserrata responses to Al stress, we determined the changes in photosynthetic parameters, antioxidant enzyme activities, and osmoregulatory substance contents of C. semiserrata leaves under different concentrations of Al stress treatments (0, 1, 2, 3, and 4 mmol/L Alcl3) using a combination of physiological and proteomics approaches. In addition, we identified the differentially expressed proteins (DEPs) under 0 (CK or GNR0), 2 mmol/L (GNR2), and 4 mmol/L (GNR4) Al stress using a 4D-label-free technique. With increasing stress concentration, the photosynthetic indexes of C. semiserrata leaves, peroxidase (POD), superoxide dismutase (SOD), catalase (CAT), soluble protein (SP), and soluble sugar (SS) showed an overall trend of increasing and then decreasing, and proline (Pro) and malondialdehyde (MDA) contents tended to continuously increase overall. Compared with the control group, we identified 124 and 192 DEPs in GNR2 and GNR4, respectively, which were mainly involved in metabolic processes such as photosynthesis, flavonoid metabolism, oxidative stress response, energy and carbohydrate metabolism, and signal transduction. At 2 mmol/L Al stress, carbon metabolism, amino sugar and nucleotide sugar metabolism, and flavonoid metabolism-related proteins were significantly changed, and when the stress was increased to 4 mmol/L Al, the cells accumulated reactive oxygen species (ROS) at a rate exceeding the antioxidant system scavenging capacity. To deal with this change, C. semiserrata leaves enhanced their glutathione metabolism, drug metabolism-cytochrome P450, metabolism of xenobiotics by cytochrome P450, and other metabolic processes to counteract peroxidative damage to the cytoplasmic membrane caused by stress. In addition, we found that C. semiserrata resisted aluminum toxicity mainly by synthesizing anthocyanidins under 2 mmol/L stress, whereas proanthocyanidins were alleviated by the generation of proanthocyanidins under 4 mmol/L stress, which may be a special mechanism by which C. semiserrata responds to different concentrations of aluminum stress.

Dynamics of organic acid exudation and rhizobacteria in maize rhizosphere respond to N-CDs

To sustainably feed the growing global population, it is essential to increase crop yields on limited land while reducing the use of fertilizers and agrochemicals. The rhizosphere regulation shows significant potential to address this challenge. Here, foliar applied doping of nitrogen in carbon dots (N-CDs) entered maize leaves, and were transported to the stems and roots. The internalized N-CDs significantly increased the biomass (26.4-93.8%) and photosynthesis (17.0-20.3 %) of maize seedling during the three-week application of N-CDs, providing the substrate for tricarboxylic acid cycle (TCA) in shoots and roots. Correspondingly, more organic acids involved in TCA cycle, such as citric acid (14.0-fold), succinic acid (4.4-fold) and malic acid (3.4-fold), were synthesized and then secreted into rhizosphere after exposed to N-CDs for one day. As the exposure time increased, greater secretion of above organic acids by the roots was induced. However, no significant change was observed in the relative abundance of rhizobacteria after foliar application with N-CDs for one day. After one week, the relative abundances of Azotobacter, Bacillus, Lysobacter, Mucilaginibacter, and Sphingomonas increased by 0.8-3.8 folds. The relative abundance of more beneficial rhizobacteria (Sphingomonas, Lysobacter, Rhizobium, Azotobacter, Pseudomonas, Mucilaginibacter and Bacillus) enriched by 0.3-6.0 folds after two weeks, and Sphingomonas, Flavisolibacter and Bacillus improved by 0.6-3.2 folds after three weeks. These dynamic changes suggested that N-CDs initiate the synthesis and secretion of organic acids and then recruited beneficial rhizobacteria. The hierarchical partitioning analysis further indicated that N-CDs-induced secretion of organic acids from the roots was the main drivers of rhizobacteria community dynamics. The differential microbes altered by N-CDs were mainly involved in nitrogen (N) and phosphorus (P) cycles, which are beneficial for N and P uptake, and maize growth. These results provide insights into understanding the rhizosphere regulation of nanomaterials to improve plant productivity and nutrient-use efficiency.

Robotized indoor phenotyping allows genomic prediction of adaptive traits in the field

Breeding for resilience to climate change requires considering adaptive traits such as plant architecture, stomatal conductance and growth, beyond the current selection for yield. Robotized indoor phenotyping allows measuring such traits at high throughput for speed breeding, but is often considered as non-relevant for field conditions. Here, we show that maize adaptive traits can be inferred in different fields, based on genotypic values obtained indoor and on environmental conditions in each considered field. The modelling of environmental effects allows translation from indoor to fields, but also from one field to another field. Furthermore, genotypic values of considered traits match between indoor and field conditions. Genomic prediction results in adequate ranking of genotypes for the tested traits, although with lesser precision for elite varieties presenting reduced phenotypic variability. Hence, it distinguishes genotypes with high or low values for adaptive traits, conferring either spender or conservative strategies for water use under future climates.

Serendipita indica mitigates drought-triggered oxidative burst in trifoliate orange by stimulating antioxidant defense systems

Soil drought is detrimental to plant growth worldwide, particularly by triggering reactive oxygen species (ROS) burst. Serendipita indica (Si), a culturable root-associated endophytic fungus, can assist host plants in dealing with abiotic stresses; however, it is unknown whether and how Si impacts the drought tolerance of citrus plants. To unravel the effects and roles of Si on drought-stressed plants, trifoliate orange (Poncirus trifoliata L. Raf.; a citrus rootstock) seedlings were inoculated with Si and exposed to soil drought, and growth, gas exchange, ROS levels, antioxidant defense systems, and expression of genes encoding antioxidant enzymes and fatty acid desaturases in leaves were measured. Soil drought suppressed plant biomass, whereas Si inoculation significantly increased plant biomass (10.29%-22.47%) and shoot/root ratio (21.78%-24.68%) under ample water and drought conditions, accompanied by improved net photosynthetic rate (105.71%), water use efficiency (115.29%), chlorophyll index (55.34%), and nitrogen balance index (63.84%) by Si inoculation under soil drought. Soil drought triggered an increase in leaf hydrogen peroxide and superoxide anion levels, while Si inoculation significantly reduced these ROS levels under soil drought, resulting in lower membrane lipid peroxidation with respect to malondialdehyde changes. Furthermore, Si-inoculated seedlings under soil drought had distinctly higher levels of ascorbate and glutathione, as well as catalase, peroxidase, and glutathione peroxidase activities, compared with no-Si-inoculated seedlings. Si inoculation increased the expression of leaf PtFAD2, PtFAD6, PtΔ9, PtΔ15, PtFe-SOD, PtCu/Zn-SOD, PtPOD, and PtCAT1 genes under both ample water and soil drought conditions. Overall, Si-inoculated trifoliate orange plants maintained a low oxidative burst in leaves under drought, which was associated with stimulation of antioxidant defense systems. Therefore, Si has great potential as a biostimulant in enhancing drought tolerance in plants, particularly citrus.

Machine learning applications to improve flavor and nutritional content of horticultural crops through breeding and genetics

Over the last decades, significant strides were made in understanding the biochemical factors influencing the nutritional content and flavor profile of fruits and vegetables. Product differentiation in the produce aisle is the natural consequence of increasing consumer power in the food industry. Cotton-candy grapes, specialty tomatoes, and pineapple-flavored white strawberries provide a few examples. Given the increased demand for flavorful varieties, and pressing need to reduce micronutrient malnutrition, we expect breeding to increase its prioritization toward these traits. Reaching this goal will, in part, necessitate knowledge of the genetic architecture controlling these traits, as well as the development of breeding methods that maximize their genetic gain. Can artificial intelligence (AI) help predict flavor preferences, and can such insights be leveraged by breeding programs? In this Perspective, we outline both the opportunities and challenges for the development of more flavorful and nutritious crops, and how AI can support these breeding initiatives.

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.

Relationship between Photosynthetic CO2 Assimilation and Chlorophyll Fluorescence for Winter Wheat under Water Stress

Solar-induced chlorophyll fluorescence (SIF) has a high correlation with Gross Primary Production (GPP). However, studies focusing on the impact of drought on the SIF-GPP relationship have had mixed results at various scales, and the mechanisms controlling the dynamics between photosynthesis and fluorescence emission under water stress are not well understood. We developed a leaf-scale measurement system to perform concurrent measurements of active and passive fluorescence, and gas-exchange rates for winter wheat experiencing a one-month progressive drought. Our results confirmed that: (1) shifts in light energy allocation towards decreasing photochemistry (the quantum yields of photochemical quenching in PSII decreased from 0.42 to 0.21 under intermediate light conditions) and increasing fluorescence emissions (the quantum yields of fluorescence increased to 0.062 from 0.024) as drought progressed enhance the degree of nonlinearity of the SIF-GPP relationship, and (2) SIF alone has a limited capacity to track changes in the photosynthetic status of plants under drought conditions. However, by incorporating the water stress factor into a SIF-based mechanistic photosynthesis model, we show that drought-induced variations in a variety of key photosynthetic parameters, including stomatal conductance and photosynthetic CO2 assimilation, can be accurately estimated using measurements of SIF, photosynthetically active radiation, air temperature, and soil moisture as inputs. Our findings provide the experimental and theoretical foundations necessary for employing SIF mechanistically to estimate plant photosynthetic activity during periods of drought stress.

Coordination of carbon assimilation, allocation, and utilization for systemic improvement of cereal yield

The growth of yield outputs is dwindling after the first green revolution, which cannot meet the demand for the projected population increase by the mid-century, especially with the constant threat from extreme climates. Cereal yield requires carbon (C) assimilation in the source for subsequent allocation and utilization in the sink. However, whether the source or sink limits yield improvement, a crucial question for strategic orientation in future breeding and cultivation, is still under debate. To narrow the knowledge gap and capture the progress, we focus on maize, rice, and wheat by briefly reviewing recent advances in yield improvement by modulation of i) leaf photosynthesis; ii) primary C allocation, phloem loading, and unloading; iii) C utilization and grain storage; and iv) systemic sugar signals (e.g., trehalose 6-phosphate). We highlight strategies for optimizing C allocation and utilization to coordinate the source-sink relationships and promote yields. Finally, based on the understanding of these physiological mechanisms, we envisage a future scenery of "smart crop" consisting of flexible coordination of plant C economy, with the goal of yield improvement and resilience in the field population of cereals crops.

Two decades of harnessing standing genetic variation for physiological traits to improve drought tolerance in maize

We review approaches to maize breeding for improved drought tolerance during flowering and grain filling in the central and western US corn belt and place our findings in the context of results from public breeding. Here we show that after two decades of dedicated breeding efforts, the rate of crop improvement under drought increased from 6.2 g m-2 year-1 to 7.5 g m-2 year-1, closing the genetic gain gap with respect to the 8.6 g m-2 year-1 observed under water-sufficient conditions. The improvement relative to the long-term genetic gain was possible by harnessing favourable alleles for physiological traits available in the reference population of genotypes. Experimentation in managed stress environments that maximized the genetic correlation with target environments was key for breeders to identify and select for these alleles. We also show that the embedding of physiological understanding within genomic selection methods via crop growth models can hasten genetic gain under drought. We estimate a prediction accuracy differential (Δr) above current prediction approaches of ~30% (Δr=0.11, r=0.38), which increases with increasing complexity of the trait environment system as estimated by Shannon information theory. We propose this framework to inform breeding strategies for drought stress across geographies and crops.

Increase in cotton yield through improved leaf physiological functioning under the soil condition of reduced chemical fertilization compensated by the enhanced organic liquid fertilization

Introduction

Low agricultural nutrient input efficiency remains a significant impediment for crop production globally. To address this issue in cotton agroecosystems, there is a need to develop sustainable crop nutrient management strategies to achieve high crop yields. We hypothesized that organic liquid fertilizer (OF) combined with reduced chemical fertilizer (CF) would enhance cotton yield by improving leaf functioning and soil properties. However, the underlying mechanism and its related process is poorly understood.

Methods

This study explored the effects of OF combined with reduced CF on cotton yield, physiology and soil properties. Treatments included a single application of CF (CF: N, P2O5 and K2O applied at 228, 131 and 95 kg ha-1) and combined applications of OF and CF (OF0.6-OF1.4) in the following ratios: OF0.6, OF+60% CF; OF0.8, OF+80% CF; OF1.0, OF+100% CF; OF1.2, OF+120% CF; OF1.4, OF+140% CF.

Results and discussion

The result showed that compared with CF, OF0.8, OF1.0 and OF1.2 increased soil organic matter (SOM) content by 9.9%, 16.3% and 23.7%, respectively. Compared with CF, the OF0.6, OF0.8, OF1.0, and OF1.2 treatments increased leaf area (LA) by 10.6-26.1%, chlorophyll content (Chl content) by 6.8-39.6%, and the efficiency of photosystem II (PSII) light energy (Y(II)), electron transfer rate of PSII (ETR) and photochemical quenching (qP) by 3.6-26.3%, 4.7-15.3% and 4.3-9.8%, respectively. The OF0.8 treatment increased net photosynthetic rate (P n), stomatal conductance (G s) and transpiration rate (E) by 22.0%, 27.4% and 26.8%, respectively, resulting in higher seed cotton yield. The seed cotton yield and economic coefficient were positively correlated with P n, E, G s and Y(II) from the full boll stage to the boll opening stage. In summary, the OF0.8 treatment can maintain a high SOM content and photosynthetic performance with reduced chemical fertilizer input without sacrificing yield. The integration of OF+80% CF (OF0.8) is a promising nutrient management strategy for highly efficient cotton production under mulch drip irrigation systems.

Faster induction of photosynthesis increases biomass and grain yield in glasshouse-grown transgenic Sorghum bicolor overexpressing Rieske FeS

Sorghum is one of the most important crops providing food and feed in many of the world's harsher environments. Sorghum utilizes the C₄ pathway of photosynthesis in which a biochemical carbon-concentrating mechanism results in high CO₂ assimilation rates. Overexpressing the Rieske FeS subunit of the Cytochrome b₆ f complex was previously shown to increase the rate of photosynthetic electron transport and stimulate CO₂ assimilation in the model C₄ plant Setaria viridis. To test whether productivity of C₄ crops could be improved by Rieske overexpression, we created transgenic Sorghum bicolor Tx430 plants with increased Rieske content. The transgenic plants showed no marked changes in abundances of other photosynthetic proteins or chlorophyll content. The steady-state rates of electron transport and CO₂ assimilation did not differ between the plants with increased Rieske abundance and control plants, suggesting that Cytochrome b₆ f is not the only factor limiting electron transport in sorghum at high light and high CO₂ . However, faster responses of non-photochemical quenching as well as an elevated quantum yield of Photosystem II and an increased CO₂ assimilation rate were observed from the plants overexpressing Rieske during the photosynthetic induction, a process of activation of photosynthesis upon the dark-light transition. As a consequence, sorghum with increased Rieske content produced more biomass and grain when grown in glasshouse conditions. Our results indicate that increasing Rieske content has potential to boost productivity of sorghum and other C₄ crops by improving the efficiency of light utilization and conversion to biomass through the faster induction of photosynthesis.

Modelling plants across scales of biological organisation for guiding crop improvement

Grain yield improvement in globally important staple crops is critical in the coming decades if production is to keep pace with growing demand; so there is increasing interest in understanding and manipulating plant growth and developmental traits for better crop productivity. However, this is confounded by complex cross-scale feedback regulations and a limited ability to evaluate the consequences of manipulation on crop production. Plant/crop modelling could hold the key to deepening our understanding of dynamic trait-crop-environment interactions and predictive capabilities for supporting genetic manipulation. Using photosynthesis and crop growth as an example, this review summarises past and present experimental and modelling work, bringing about a model-guided crop improvement thrust, encompassing research into: (1) advancing cross-scale plant/crop modelling that connects across biological scales of organisation using a trait dissection-integration modelling principle; (2) improving the reliability of predicted molecular-trait-crop-environment system dynamics with experimental validation; and (3) innovative model application in synergy with cross-scale experimentation to evaluate G×M×E and predict yield outcomes of genetic intervention (or lack of it) for strategising further molecular and breeding efforts. The possible future roles of cross-scale plant/crop modelling in maximising crop improvement are discussed.

Seasonal climate conditions impact the effectiveness of improving photosynthesis to increase soybean yield

Context

Photosynthetic stimulations have shown promising outcomes in improving crop photosynthesis, including soybean. However, it is still unclear to what extent these changes can impact photosynthetic assimilation and yield under long-term field climate conditions.

Objective

In this paper, we present a systematic evaluation of the response of canopy photosynthesis and yield to two critical parameters in leaf photosynthesis: the maximum carboxylation rate of ribulose-1,5-bisphosphate carboxylase/oxygenase (Vcmax) and the maximum electron transport of the ribulose-1,5-bisphosphate regeneration rate (Jmax).

Methods

Using the field-scale crop model Soybean-BioCro and ten years of observed climate data in Urbana, Illinois, U.S., we conducted sensitivity experiments to estimate the changes in canopy photosynthesis, leaf area index, and biomass due to the changes in Vcmax and Jmax.

Results

The results show that 1) Both the canopy photosynthetic assimilation (An) and pod biomass yields were more sensitive to the changes in Jmax, particularly at high atmospheric carbon-dioxide concentrations ([CO2]); 2) Higher [CO2] undermined the effectiveness of increasing the two parameters to improve An and yield; 3) Under the same [CO2], canopy light interception and canopy respiration were key factors that undermined improvements in An and yield; 4) A canopy with smaller leaf area index tended to have a higher yield improvement, and 5) Increases in assimilations and yields were highly dependent on growing-season climatic conditions. The solar radiation, temperature, and relative humidity were the main climate drivers that impacted the yield improvement, and they had opposite correlations with improved yield during the vegetative phase compared to the reproductive phase.

Conclusions

In a world with elevated [CO2], genetic engineering crop photosynthesis should focus more on improving Jmax. Further, long-term climate conditions and seasonal variations must be considered to determine the improvements in soybean canopy photosynthesis and yield at the field scale.

Implications

Quantifying the effectiveness of changing Vcmax and Jmax helps understand their individual and combined contributions to potential improvements in assimilation and yield. This work provides a framework for evaluating how altering the photosynthetic rate parameters impacts soybean yield and assimilation under different seasonal climate scenarios at the field scale.

China can be self-sufficient in maize production by 2030 with optimal crop management

Population growth and economic development in China has increased the demand for food and animal feed, raising questions regarding China's future maize production self-sufficiency. Here, we address this challenge by combining data-driven projections with a machine learning method on data from 402 stations, with data from 87 field experiments across China. Current maize yield would be roughly doubled with the implementation of optimal planting density and management. In the 2030 s, we estimate a 52% yield improvement through dense planting and soil improvement under a high-end climate forcing Shared Socio-Economic Pathway (SSP585), compared with a historical climate trend. Based on our results, yield gains from soil improvement outweigh the adverse effects of climate change. This implies that China can be self-sufficient in maize by using current cropping areas. Our results challenge the view of yield stagnation in most global areas and provide an example of how food security can be achieved with optimal crop-soil management under future climate change scenarios.

Feeding the world: impacts of elevated [CO2] on nutrient content of greenhouse grown fruit crops and options for future yield gains

Several long-term studies have provided strong support demonstrating that growing crops under elevated [CO2] can increase photosynthesis and result in an increase in yield, flavour and nutritional content (including but not limited to Vitamins C, E and pro-vitamin A). In the case of tomato, increases in yield by as much as 80% are observed when plants are cultivated at 1000 ppm [CO2], which is consistent with current commercial greenhouse production methods in the tomato fruit industry. These results provide a clear demonstration of the potential for elevating [CO2] for improving yield and quality in greenhouse crops. The major focus of this review is to bring together 50 years of observations evaluating the impact of elevated [CO2] on fruit yield and fruit nutritional quality. In the final section, we consider the need to engineer improvements to photosynthesis and nitrogen assimilation to allow plants to take greater advantage of elevated CO2 growth conditions.

ASYMMETRIC LEAVES 2 and ASYMMETRIC LEAVES 2-LIKE are partially redundant genes and essential for fruit development in tomato

Fruit size and shape are controlled by genes expressed during the early developmental stages of fruit. Although the function of ASYMMETRIC LEAVES 2 (AS2) in promoting leaf adaxial cell fates has been well characterized in Arabidopsis thaliana, the molecular mechanisms conferring freshy fruit development as a spatial-temporal expression gene in tomato pericarp remain unclear. In the present study, we verified the transcription of SlAS2 and SlAS2L, two homologs of AS2, in the pericarp during early fruit development. Disruption of SlAS2 or SlAS2L caused a significant decrease in pericarp thickness as a result of a reduction in the number of pericarp cell layers and cell area, leading to smaller tomato fruit size, which revealed their critical roles in tomato fruit development. In addition, leaves and stamens exhibited severe morphological defects in slas2 and slas2l single mutants, as well as in the double mutants. These results demonstrated the redundant and pleiotropic functions of SlAS2 and SlAS2L in tomato fruit development. Yeast two-hybrid and split-luciferase complementation assays showed that both SlAS2 and SlAS2L physically interact with SlAS1. Molecular analyses further indicated that SlAS2 and SlAS2L regulate various downstream genes in leaf and fruit development, and that some genes participating in the regulation of cell division and cell differentiation in the tomato pericarp are affected by these genes. Our findings demonstrate that SlAS2 and SlAS2L are vital transcription factors required for tomato fruit development.

More than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters: a computational study on wheat crop

Using in silico experiment in crop model, we identified different physiological regulations of yield and yield stability, as well as quantify the genotype and environment numbers required for analysing yield stability convincingly. Identifying target traits for breeding stable and high-yielded cultivars simultaneously is difficult due to limited knowledge of physiological mechanisms behind yield stability. Besides, there is no consensus about the adequacy of a stability index (SI) and the minimal number of environments and genotypes required for evaluating yield stability. We studied this question using the crop model APSIM-Wheat to simulate 9100 virtual genotypes grown under 9000 environments. By analysing the simulated data, we showed that the shape of phenotype distributions affected the correlation between SI and mean yield and the genotypic superiority measure (P_i) was least affected among 11 SI. P_i was used as index to demonstrate that more than 150 environments were required to estimate yield stability of a genotype convincingly and more than 1000 genotypes were necessary to evaluate the contribution of a physiological parameter to yield stability. Network analyses suggested that a physiological parameter contributed preferentially to yield or P_i. For example, soil water absorption efficiency and potential grain filling rate explained better the variations in yield than in P_i; while light extinction coefficient and radiation use efficiency were more correlated with P_i than with yield. The high number of genotypes and environments required for studying P_i highlight the necessity and potential of in silico experiments to better understand the mechanisms behind yield stability.

Disentangling the Heterosis in Biomass Production and Radiation Use Efficiency in Maize: A Phytomer-Based 3D Modelling Approach

Maize (Zea mays L.) benefits from heterosis in-yield formation and photosynthetic efficiency through optimizing canopy structure and improving leaf photosynthesis. However, the role of canopy structure and photosynthetic capacity in determining heterosis in biomass production and radiation use efficiency has not been separately clarified. We developed a quantitative framework based on a phytomer-based three-dimensional canopy photosynthesis model and simulated light capture and canopy photosynthetic production in scenarios with and without heterosis in either canopy structure or leaf photosynthetic capacity. The accumulated above-ground biomass of Jingnongke728 was 39% and 31% higher than its male parent, Jing2416, and female parent, JingMC01, while accumulated photosynthetically active radiation was 23% and 14% higher, correspondingly, leading to an increase of 13% and 17% in radiation use efficiency. The increasing post-silking radiation use efficiency was mainly attributed to leaf photosynthetic improvement, while the dominant contributing factor differs for male and female parents for heterosis in post-silking yield formation. This quantitative framework illustrates the potential to identify the key traits related to yield and radiation use efficiency and helps breeders to make selections for higher yield and photosynthetic efficiency.

Identification of photosynthetic parameters for superior yield of two super hybrid rice varieties: A cross-scale study from leaf to canopy

Enhancing photosynthetic capacity is widely accepted as critical to advancing crop yield. Therefore, identifying photosynthetic parameters positively related to biomass accumulation in elite cultivars is the major focus of current rice research. In this work, we assessed leaf photosynthetic performance, canopy photosynthesis, and yield attributes of super hybrid rice cultivars Y-liangyou 3218 (YLY3218) and Y-liangyou 5867 (YLY5867) at tillering stage and flowering stage, using inbred super rice cultivars Zhendao11(ZD11) and Nanjing 9108 (NJ9108) as control. A diurnal canopy photosynthesis model was applied to estimate the influence of key environmental factors, canopy attributes, and canopy nitrogen status on daily aboveground biomass increment (AM_DAY). Results showed that primarily the light-saturated photosynthetic rate at tillering stage contributed to the advancing yield and biomass of super hybrid rice in comparison to inbred super rice, and the light-saturated photosynthetic rate between them was similar at flowering stage. At tillering stage, the higher CO₂ diffusion capacity, together with higher biochemical capacity (i.e., maximum carboxylation rate of Rubisco, maximum electron transport rate (J _max), and triose phosphate utilization rate) favored leaf photosynthesis of super hybrid rice. Similarly, AM_DAY in super hybrid rice was higher than inbred super rice at tillering stage, and comparable at flowering stage partially due to increased canopy nitrogen concentration (SLN_ave) of inbred super rice. At tillering stage, model simulation revealed that replacement of J _max and g _m in inbred super rice by super hybrid rice always had a positive effect on AM_DAY, and the averaged AM_DAY increment was 5.7% and 3.4%, respectively. Simultaneously, the 20% enhancement of total canopy nitrogen concentration through the improvement of SLN_ave (TNC-SLN_ave) resulted in the highest AM_DAY across cultivars, with an average increase of 11.2%. In conclusion, the advancing yield performance of YLY3218 and YLY5867 was due to the higher J _max and g _m at tillering stage, and TCN-SLN_ave is a promising target for future super rice breeding programs.

Plant hormone cytokinin at the crossroads of stress priming and control of photosynthesis

To cope with biotic and abiotic stress conditions, land plants have evolved several levels of protection, including delicate defense mechanisms to respond to changes in the environment. The benefits of inducible defense responses can be further augmented by defense priming, which allows plants to respond to a mild stimulus faster and more robustly than plants in the naïve (non-primed) state. Priming provides a low-cost protection of agriculturally important plants in a relatively safe and effective manner. Many different organic and inorganic compounds have been successfully tested to induce resistance in plants. Among the plethora of commonly used physicochemical techniques, priming by plant growth regulators (phytohormones and their derivatives) appears to be a viable approach with a wide range of applications. While several classes of plant hormones have been exploited in agriculture with promising results, much less attention has been paid to cytokinin, a major plant hormone involved in many biological processes including the regulation of photosynthesis. Cytokinins have been long known to be involved in the regulation of chlorophyll metabolism, among other functions, and are responsible for delaying the onset of senescence. A comprehensive overview of the possible mechanisms of the cytokinin-primed defense or stress-related responses, especially those related to photosynthesis, should provide better insight into some of the less understood aspects of this important group of plant growth regulators.

Escherichia coli expressing chloroplast chaperones as a proxy to test heterologous Rubisco production in leaves

Rubisco is a fundamental enzyme in photosynthesis and therefore for life. Efforts to improve plant Rubisco performance have been hindered by the enzymes' complex chloroplast biogenesis requirements. New Synbio approaches, however, now allow the production of some plant Rubisco isoforms in Escherichia coli. While this enhances opportunities for catalytic improvement, there remain limitations in the utility of the expression system. Here we generate, optimize, and test a robust Golden Gate cloning E. coli expression system incorporating the protein folding machinery of tobacco chloroplasts. By comparing the expression of different plant Rubiscos in both E. coli and plastome-transformed tobacco, we show that the E. coli expression system can accurately predict high level Rubisco production in chloroplasts but poorly forecasts the biogenesis potential of isoforms with impaired production in planta. We reveal that heterologous Rubisco production in E. coli and tobacco plastids poorly correlates with Rubisco large subunit phylogeny. Our findings highlight the need to fully understand the factors governing Rubisco biogenesis if we are to deliver an efficient, low-cost screening tool that can accurately emulate chloroplast expression.

Climate change challenges, plant science solutions

Climate change is a defining challenge of the 21st century, and this decade is a critical time for action to mitigate the worst effects on human populations and ecosystems. Plant science can play an important role in developing crops with enhanced resilience to harsh conditions (e.g. heat, drought, salt stress, flooding, disease outbreaks) and engineering efficient carbon-capturing and carbon-sequestering plants. Here, we present examples of research being conducted in these areas and discuss challenges and open questions as a call to action for the plant science community.

Enhancing the light reactions of photosynthesis: Strategies, controversies, and perspectives

Photosynthesis is central to life on Earth, employing sunlight, water, and carbon dioxide to produce chemical energy and oxygen. It is generally accepted that boosting its efficiency offers one promising way to increase crop yields under agronomically realistic conditions. Since the components, structure, and regulatory mechanisms of the light reactions of photosynthesis are well understood, concepts for enhancing the process have been suggested and partially tested. These approaches vary in complexity, from targeting single components to comprehensive redesign of the whole process on the scales from single cells or tissues to whole canopies. Attempts to enhance light utilization per leaf, by decreasing pigmentation, increasing levels of photosynthetic proteins, prolonging the lifespan of the photosynthetic machinery, or massive reconfiguration of the photosynthetic machinery and the incorporation of nanomaterials, are discussed in this review first. Secondly, strategies intended to optimize the acclimation of photosynthesis to changes in the environment are presented, including redesigning mechanisms to dissipate excess excitation energy (e.g., non-photochemical quenching) or reduction power (e.g., flavodiiron proteins). Moreover, schemes for improving acclimation, inspired by natural or laboratory-induced adaptation, are introduced. However, all these endeavors are still in an early exploratory phase and/or have not resulted in the desired outcome, largely because photosynthesis is embedded within large networks of closely interacting cellular and metabolic processes, which can vary among species and even cultivars. This explains why integrated, systems-wide approaches are required to achieve the breakthroughs required for effectively increasing crop yields.

Potential abiotic stress targets for modern genetic manipulation

Research into crop yield and resilience has underpinned global food security, evident in yields tripling in the past 5 decades. The challenges that global agriculture now faces are not just to feed 10+ billion people within a generation, but to do so under a harsher, more variable, and less predictable climate, and in many cases with less water, more expensive inputs, and declining soil quality. The challenges of climate change are not simply to breed for a "hotter drier climate," but to enable resilience to floods and droughts and frosts and heat waves, possibly even within a single growing season. How well we prepare for the coming decades of climate variability will depend on our ability to modify current practices, innovate with novel breeding methods, and communicate and work with farming communities to ensure viability and profitability. Here we define how future climates will impact farming systems and growing seasons, thereby identifying the traits and practices needed and including exemplars being implemented and developed. Critically, this review will also consider societal perspectives and public engagement about emerging technologies for climate resilience, with participatory approaches presented as the best approach.

A 'wiring diagram' for source strength traits impacting wheat yield potential

Source traits are currently of great interest for the enhancement of yield potential; for example, much effort is being expended to find ways of modifying photosynthesis. However, photosynthesis is but one component of crop regulation, so sink activities and the coordination of diverse processes throughout the crop must be considered in an integrated, systems approach. A set of 'wiring diagrams' has been devised as a visual tool to integrate the interactions of component processes at different stages of wheat development. They enable the roles of chloroplast, leaf, and whole-canopy processes to be seen in the context of sink development and crop growth as a whole. In this review, we dissect source traits both anatomically (foliar and non-foliar) and temporally (pre- and post-anthesis), and consider the evidence for their regulation at local and whole-plant/crop levels. We consider how the formation of a canopy creates challenges (self-occlusion) and opportunities (dynamic photosynthesis) for components of photosynthesis. Lastly, we discuss the regulation of source activity by feedback regulation. The review is written in the framework of the wiring diagrams which, as integrated descriptors of traits underpinning grain yield, are designed to provide a potential workspace for breeders and other crop scientists that, along with high-throughput and precision phenotyping data, genetics, and bioinformatics, will help build future dynamic models of trait and gene interactions to achieve yield gains in wheat and other field crops.

A cross-scale analysis to understand and quantify the effects of photosynthetic enhancement on crop growth and yield across environments

Photosynthetic manipulation provides new opportunities for enhancing crop yield. However, understanding and quantifying the importance of individual and multiple manipulations on the seasonal biomass growth and yield performance of target crops across variable production environments is limited. Using a state-of-the-art cross-scale model in the APSIM platform we predicted the impact of altering photosynthesis on the enzyme-limited (A_c ) and electron transport-limited (A_j ) rates, seasonal dynamics in canopy photosynthesis, biomass growth, and yield formation via large multiyear-by-location crop growth simulations. A broad list of promising strategies to improve photosynthesis for C₃ wheat and C₄ sorghum were simulated. In the top decile of seasonal outcomes, yield gains were predicted to be modest, ranging between 0% and 8%, depending on the manipulation and crop type. We report how photosynthetic enhancement can affect the timing and severity of water and nitrogen stress on the growing crop, resulting in nonintuitive seasonal crop dynamics and yield outcomes. We predicted that strategies enhancing A_c alone generate more consistent but smaller yield gains across all water and nitrogen environments, A_j enhancement alone generates larger gains but is undesirable in more marginal environments. Large increases in both A_c and A_j generate the highest gains across all environments. Yield outcomes of the tested manipulation strategies were predicted and compared for realistic Australian wheat and sorghum production. This study uniquely unpacks complex cross-scale interactions between photosynthesis and seasonal crop dynamics and improves understanding and quantification of the potential impact of photosynthesis traits (or lack of it) for crop improvement research.

Defining the scope for altering rice leaf anatomy to improve photosynthesis: a modelling approach

Leaf structure plays an important role in photosynthesis. However, the causal relationship and the quantitative importance of any single structural parameter to the overall photosynthetic performance of a leaf remains open to debate. In this paper, we report on a mechanistic model, eLeaf, which successfully captures rice leaf photosynthetic performance under varying environmental conditions of light and CO₂ . We developed a 3D reaction-diffusion model for leaf photosynthesis parameterised using a range of imaging data and biochemical measurements from plants grown under ambient and elevated CO₂ and then interrogated the model to quantify the importance of these elements. The model successfully captured leaf-level photosynthetic performance in rice. Photosynthetic metabolism underpinned the majority of the increased carbon assimilation rate observed under elevated CO₂ levels, with a range of structural elements making positive and negative contributions. Mesophyll porosity could be varied without any major outcome on photosynthetic performance, providing a theoretical underpinning for experimental data. eLeaf allows quantitative analysis of the influence of morphological and biochemical properties on leaf photosynthesis. The analysis highlights a degree of leaf structural plasticity with respect to photosynthesis of significance in the context of attempts to improve crop photosynthesis.

Stomatal CO2/bicarbonate sensor consists of two interacting protein kinases, Raf-like HT1 and non-kinase-activity requiring MPK12/MPK4

The continuing rise in the atmospheric carbon dioxide (CO₂) concentration causes stomatal closing, thus critically affecting transpirational water loss, photosynthesis, and plant growth. However, the primary CO₂ sensor remains unknown. Here, we show that elevated CO₂ triggers interaction of the MAP kinases MPK4/MPK12 with the HT1 protein kinase, thus inhibiting HT1 kinase activity. At low CO₂, HT1 phosphorylates and activates the downstream negatively regulating CBC1 kinase. Physiologically relevant HT1-mediated phosphorylation sites in CBC1 are identified. In a genetic screen, we identify dominant active HT1 mutants that cause insensitivity to elevated CO₂. Dominant HT1 mutants abrogate the CO₂/bicarbonate-induced MPK4/12-HT1 interaction and HT1 inhibition, which may be explained by a structural AlphaFold2- and Gaussian-accelerated dynamics-generated model. Unexpectedly, MAP kinase activity is not required for CO₂ sensor function and CO₂-triggered HT1 inhibition and stomatal closing. The presented findings reveal that MPK4/12 and HT1 together constitute the long-sought primary stomatal CO₂/bicarbonate sensor upstream of the CBC1 kinase in plants.

Genotype-dependent changes of cell wall composition influence physiological traits of a long and a non-long shelf-life tomato genotypes under distinct water regimes

Water shortage strongly affects plants' physiological performance. Since tomato (Solanum lycopersicum) non-long shelf-life (nLSL) and long shelf-life (LSL) genotypes differently face water deprivation, we subjected a nLSL and a LSL genotype to four treatments: control (well watering), short-term water deficit stress at 40% field capacity (FC) (ST 40% FC), short-term water deficit stress at 30% FC (ST 30% FC), and short-term water deficit stress at 30% FC followed by recovery (ST 30% FC-Rec). Treatments promoted genotype-dependent elastic adjustments accompanied by distinct photosynthetic responses. While the nLSL genotype largely modified mesophyll conductance (g_m ) across treatments, it was kept within a narrow range in the LSL genotype. However, similar g_m values were achieved under ST 30% FC conditions. Particularly, modifications in the relative abundance of cell wall components and in sub-cellular anatomic parameters such as the chloroplast surface area exposed to intercellular air space per leaf area (S_c /S) and the cell wall thickness (T_cw ) regulated g_m in the LSL genotype. Instead, only changes in foliar structure at the supra-cellular level influenced g_m in the nLSL genotype. Even though further experiments testing a larger range of genotypes and treatments would be valuable to support our conclusions, we show that even genotypes of the same species can present different elastic, anatomical, and cell wall composition-mediated mechanisms to regulate g_m when subjected to distinct water regimes.

Stomata conductance as a goalkeeper for increased photosynthetic efficiency

100-120 words. References should not be included. Abbreviations should be avoided as far as possible. Low stomatal conductance (g_s) poses a major constraint for improving photosynthetic efficiency for greater yield. Options at the molecular, leaf, canopy, and even the whole plant scales can be developed to enhance g_s for greater light and water use efficiencies. Among these, many genes regulating stomatal development and stomatal movement have been discovered and manipulated to increase light and water use efficiencies under well-watered, drought, or facility agriculture conditions with the manual-controlled growth environmental. Optimization of canopy conductance to increase whole plant photosynthesis with full consideration of the heterogeneities in g_s, microclimates and leaf ontology inside the canopy represents a largely uncharted area to improve crop efficiency.

Insight into the regulatory networks underlying the high lipid perennial ryegrass growth under different irradiances

Under favourable conditions, perennial ryegrass (Lolium perenne) engineered to accumulated high lipid (HL) carbon sink in their leaves was previously shown to also enhance photosynthesis and growth. The greater aboveground biomass was found to be diminished in a dense canopy compared to spaced pots. Besides, the underlying genetic regulatory network linking between leaf lipid sinks and these physiological changes remains unknown. In this study, we demonstrated that the growth advantage was not displayed in HL Lolium grown in spaced pots under low lights. Under standard lights, analysis of differentiating transcripts in HL Lolium reveals that the plants had elevated transcripts involved in lipid metabolism, light capturing, photosynthesis, and sugar signalling while reduced expression of genes participating in sugar biosynthesis and transportation. The plants also had altered several transcripts involved in mitochondrial oxidative respiration and redox potential. Many of the above upregulated or downregulated transcript levels were found to be complemented by growing the plants under low light. Overall, this study emphasizes the importance of carbon and energy homeostatic regulatory mechanisms to overall productivity of the HL Lolium through photosynthesis, most of which are significantly impacted by low irradiances.

Combining QTL mapping and RNA-Seq Unravels candidate genes for Alfalfa (Medicago sativa L.) leaf development

BACKGROUND

Leaf size affects crop canopy morphology and photosynthetic efficiency, which can influence forage yield and quality. It is of great significance to mine the key genes controlling leaf development for breeding new alfalfa varieties. In this study, we mapped leaf length (LL), leaf width (LW), and leaf area (LA) in an F1 mapping population derived from a cultivar named ZhongmuNo.1 with larger leaf area and a landrace named Cangzhou with smaller leaf area.

RESULTS

This study showed that the larger LW was more conducive to increasing LA. A total of 24 significant quantitative trait loci (QTL) associated with leaf size were identified on both the paternal and maternal linkage maps. Among them, nine QTL explained about 11.50-22.45% phenotypic variation. RNA-seq analysis identified 2,443 leaf-specific genes and 3,770 differentially expressed genes. Combining QTL mapping, RNA-seq alalysis, and qRT-PCR, we identified seven candidate genes associated with leaf development in five major QTL regions.

CONCLUSION

Our study will provide a theoretical basis for marker-assisted breeding and lay a foundation for further revealing molecular mechanism of leaf development in alfalfa.

Wheat traits and the associated loci conferring radiation use efficiency

Wheat (Triticum aestivum L.) radiation use efficiency (RUE) must be raised through crop breeding to further increase the yield potential, as the harvest index is now close to its theoretical limit. Field experiments including 209 wheat cultivars which have been widely cultivated in China since the 1940s were conducted in two growing seasons (2018-2019 and 2019-2020) to evaluate the variations of phenological, physiological, plant architectural, and yield-related traits and their contributions to RUE and to identify limiting factors for wheat yield potential. The average annual genetic gain in grain yield was 0.60% (or 45.32 kg ha^-1  year^-1 ; R²  = 0.44, P < 0.01), mainly attributed to the gain in RUE (r = 0.85, P < 0.01). The net photosynthetic rates were positively and closely correlated with grain RUE and grain yield, suggesting source as a limiting factor to future yield gains. Thirty-four cultivars were identified, exhibiting not only high RUE, but also traits contributing to high RUE and 11 other critical traits - of known genetic basis - as potential parents for breeding to improve yield and RUE. Our findings reveal wheat traits and the associated loci conferring RUE, which are valuable for facilitating marker-assisted breeding to improve wheat RUE and yield potential.

Proper irrigation amount for eggplant cultivation in a solar greenhouse improved plant growth, fruit quality and yield by influencing the soil microbial community and rhizosphere environment

Water scarcity is a worldwide problem, and in order to obtain plenty of production, agricultural irrigation water accounts for a large portion. Many studies have shown that the interaction of root microorganisms and soil can promote crop growth. Developing ways to reduce irrigation to maintain soil fertility and ensure crop yield by regulating the root microenvironment is an important research goal. Here, we developed a reasonable irrigation plan for eggplant cultivation in a solar greenhouse. The maximum theoretical amount of water demand during eggplant planting obtained from a previous study was used as the control (CK), and the irrigation in the treatments was reduced by 10, 20 and 30% relative to this amount. The 10% irrigation reduction treatment (T1) significantly improved soil nutrients and increased soil catalase, urease and alkaline phosphatase activities (p < 0.05). Further analysis of rhizosphere microorganisms revealed the highest richness and diversity of the microbial community under the T1 treatment, with Bacilli as the most abundant bacteria and Aspergillaceae as the most abundant fungi and lower relative abundances of Chloroflexi and Acidobacteria (p < 0.05). Changes in microbial community structure under the influence of different irrigation treatments resulted in improvements in rhizosphere N cycling and nutrient catabolism. The plant–microbe interactions led to significant increases in eggplant plant height, root vigour, root surface area, leaf chlorophyll a, leaf net photosynthetic rate, water use efficiency, transpiration rate, and stomatal conductance under the T1 treatment compared to the CK treatment; soluble sugar, soluble protein and free amino acid contents in eggplant fruit increased by 10.8, 12.3 and 6.7%, respectively; and yield increased by 3.9%. Our research proved that the 10% irrigation reduction treatment (T1) could improve microbial community richness and fruit yield, which would improve irrigation efficiency and cost reduction in agriculture.

Carbon assimilation and distribution in cotton photosynthetic organs is a limiting factor affecting boll weight formation under drought

Previous studies have documented cotton boll weight reductions under drought, but the relative importance of the subtending leaf, bracts and capsule wall in driving drought-induced reductions in boll mass has received limited attention. To investigate the role of carbon metabolism in driving organ-specific differences in contribution to boll weight formation, under drought conditions. Controlled experiments were carried out under soil relative water content (SRWC) (75 ± 5)% (well-watered conditions, control), (60 ± 5)% (moderate drought) and (45 ± 5)% (severe drought) in 2018 and 2019 with two cultivars Yuzaomian 9110 and Dexiamian 1. Under severe drought, the decreases of photosynthetic rate (Pn) and carbon isotope composition (δ¹³C) were observed in the subtending leaf, bract and capsule wall, suggesting that carbon assimilation of three organs was restricted and the limitation was most pronounced in the subtending leaf. Changes in the activities of sucrose phosphate synthase (SPS), sucrose synthase (SuSy), invertases as well as the reduction in expression of sucrose transporter (GhSUT1) led to variabilities in the sucrose content of three organs. Moreover, photosynthate distribution from subtending leaf to seeds plus fibers (the components of boll weight) was significantly restricted and the photosynthetic contribution rate of subtending leaf to boll weight was decreased, while contributions of bracts and capsule wall were increased by drought. This, in conjunction with the observed decreases in boll weight, indicated that the subtending leaf was the most sensitive photosynthetic organ to drought and was a dominant driver of boll weight loss under drought. Therefore, the subtending leaf governs boll weight loss under drought due to limitations in carbon assimilation, perturbations in sucrose metabolism and inhibition of sucrose transport.

Regulation of photosynthetic light reaction proteins via reversible phosphorylation

The regulation of photosynthesis occurs at different levels including the control of nuclear and plastid genes transcription, RNA processing and translation, protein translocation, assemblies and their post translational modifications. Out of all these, post translational modification enables rapid response of plants towards changing environmental conditions. Among all post-translational modifications, reversible phosphorylation is known to play a crucial role in the regulation of light reaction of photosynthesis. Although, phosphorylation of PS II subunits has been extensively studied but not much attention is given to other photosynthetic complexes such as PS I, Cytochrome b6f complex and ATP synthase. Phosphorylation reaction is known to protect photosynthetic apparatus in challenging environment conditions such as high light, elevated temperature, high salinity and drought. Recent studies have explored the role of photosynthetic protein phosphorylation in conferring plant immunity against the rice blast disease. The evolution of phosphorylation of different subunits of photosynthetic proteins occurred along with the evolution of plant lineage for their better adaptation to the changing environment conditions. In this review, we summarize the progress made in the research field of phosphorylation of photosynthetic proteins and highlights the missing links that need immediate attention.

3dCAP-Wheat: An Open-Source Comprehensive Computational Framework Precisely Quantifies Wheat Foliar, Nonfoliar, and Canopy Photosynthesis

Canopy photosynthesis is the sum of photosynthesis of all above-ground photosynthetic tissues. Quantitative roles of nonfoliar tissues in canopy photosynthesis remain elusive due to methodology limitations. Here, we develop the first complete canopy photosynthesis model incorporating all above-ground photosynthetic tissues and validate this model on wheat with state-of-the-art gas exchange measurement facilities. The new model precisely predicts wheat canopy gas exchange rates at different growth stages, weather conditions, and canopy architectural perturbations. Using the model, we systematically study (1) the contribution of both foliar and nonfoliar tissues to wheat canopy photosynthesis and (2) the responses of wheat canopy photosynthesis to plant physiological and architectural changes. We found that (1) at tillering, heading, and milking stages, nonfoliar tissues can contribute ~4, ~32, and ~50% of daily gross canopy photosynthesis (A_cgross; ~2, ~15, and ~-13% of daily net canopy photosynthesis, A_cnet) and absorb ~6, ~42, and ~60% of total light, respectively; (2) under favorable condition, increasing spike photosynthetic activity, rather than enlarging spike size or awn size, can enhance canopy photosynthesis; (3) covariation in tissue respiratory rate and photosynthetic rate may be a major factor responsible for less than expected increase in daily A_cnet; and (4) in general, erect leaves, lower spike position, shorter plant height, and proper plant densities can benefit daily A_cnet. Overall, the model, together with the facilities for quantifying plant architecture and tissue gas exchange, provides an integrated platform to study canopy photosynthesis and support rational design of photosynthetically efficient wheat crops.