An in situ approach to characterizing photosynthetic gas exchange of rice panicle

Water stress changes the relationship between photosynthesis and stomatal conductance

Understanding the relationship between stomatal conductance (gs) and photosynthesis (An) under water stress conditions can improve the accuracy of land surface models for estimating the gas exchange of crop canopies with the atmosphere. However, little is known about the effect of water stress on this relationship in crops. A glasshouse experiment was, therefore, conducted to investigate changes in the linear relationship between gs and An owing to water stress in rice and the association with soil moisture content. Severe (SWS), mild (MWS), and no water stress (NWS) conditions were applied from flowering onwards and the gas exchange in fully developed flag leaves was assessed weekly. The Ball-Woodrow-Berry linear model was used to assess the relationship between gs and An under different treatments. SWS had a significant effect and reduced the slope of the linear relationship between gs and An by 30 % compared with NWS. Only in SWS were An and gs strongly correlated with soil water content. Our study revealed that changes in the linear relationship through a reduction in the slope imply a conservative water-use strategy for rice under intense water stress. We propose that crop models that use the linear relationship should consider the impact of water stress conditions when simulating yields and estimating CO2 and H2O fluxes from crop canopies.

MADS1-regulated lemma and awn development benefits barley yield

Floral organ shape and size in cereal crops can affect grain size and yield, so genes that regulate their development are promising breeding targets. The lemma, which protects inner floral organs, can physically constrain grain growth; while the awn, a needle-like extension of the lemma, creates photosynthate to developing grain. Although several genes and modules controlling grain size and awn/lemma growth in rice have been characterized, these processes, and the relationships between them, are not well understood for barley and wheat. Here, we demonstrate that the barley E-class gene HvMADS1 positively regulates awn length and lemma width, affecting grain size and weight. Cytological data indicates that HvMADS1 promotes awn and lemma growth by promoting cell proliferation, while multi-omics data reveals that HvMADS1 target genes are associated with cell cycle, phytohormone signaling, and developmental processes. We define two potential targets of HvMADS1 regulation, HvSHI and HvDL, whose knockout mutants mimic awn and/or lemma phenotypes of mads1 mutants. Additionally, we demonstrate that HvMADS1 interacts with APETALA2 (A-class) to synergistically activate downstream genes in awn/lemma development in barley. Notably, we find that MADS1 function remains conserved in wheat, promoting cell proliferation to increase awn length. These findings extend our understanding of MADS1 function in floral organ development and provide insights for Triticeae crop improvement strategies.

Measuring Nonfoliar Photosynthesis

Nonfoliar gas exchange provides a noninvasive way to measure photosynthesis and other gas exchange parameters, enabling the assessment of their potential contribution to yield. Photosynthesis in nonfoliar material has been gaining increasing attention due to its contribution to yield, especially under conditions when leaf photosynthesis is compromised. Here, we provide methods and approaches along with examples of measuring gas exchange in nonfoliar material using a specialized chamber.

Quinoa panicles contribute to carbon assimilation and are more tolerant to salt stress than leaves

Contribution of inflorescences to seed filling have attracted great attention given the resilience of this photosynthetic organ to stressful conditions. However, studies have been almost exclusively focused to small grain cereals. In this study, we aimed to explore these responses in quinoa, as a climate resilient seed crop of elevated economic and nutritious potential. We compared the physiological and metabolic performance of panicles and leaves of two quinoa cultivars growing under contrasting salinity levels. Plant growth, photosynthetic and transpiratory gas exchange and chlorophyll fluorescence were monitored in inflorescences and leaves throughout the experiment. At flowering stage, young and mature leaves and panicles were sampled for key metabolic markers related to carbon, nitrogen and secondary metabolisms. When subjected to salt stress, panicles showed attenuated declines on photosynthesis, water use, pigments, amino acids, and protein levels as compared to leaves. In fact, the assimilation rates, together with a high hexose content evidenced an active photosynthetic role of the panicle under optimal and salt stress conditions. Moreover, we also found significant genotypic variability for physiological and metabolic traits of panicles and leaves, which emphasizes the study of genotype-dependent stress responses at the whole plant level. We conclude that quinoa panicles are less affected by salt stress than leaves, which encourages further research and exploitation of this organ for crop improvement and stress resilience considering the high natural diversity.

Photosynthesis - beyond the leaf

Although leaves are considered the main site for photosynthesis, other green nonfoliar tissues can carry out considerable amounts of photosynthetic carbon assimilation. With photosynthesis, a potential target for improving crop productivity, physiology and contribution of nonfoliar tissues to overall plant carbon acquisition is gaining increasing attention. This review will provide an overview of nonfoliar photosynthesis, the role of stomata in these tissues and methodologies for quantification and the contribution to overall carbon gain.

Novel Insights into the Contribution of Cyclic Electron Flow to Cotton Bracts in Response to High Light

Cyclic electron flow around photosystem I (CEF-PSI) is shown to be an important protective mechanism to photosynthesis in cotton leaves. However, it is still unclear how CEF-PSI is regulated in non-foliar green photosynthetic tissues such as bracts. In order to learn more about the regulatory function of photoprotection in bracts, we investigated the CEF-PSI attributes in Yunnan 1 cotton genotypes (Gossypium bar-badense L.) between leaves and bracts. Our findings demonstrated that cotton bracts possessed PROTON GRADIENT REGULATION5 (PGR5)-mediated and the choroplastic NAD(P)H dehydrogenase (NDH)-mediated CEF-PSI by the same mechanism as leaves, albeit at a lower rate than in leaves. The ATP synthase activity of bracts was also lower, while the proton gradient across thylakoid membrane (ΔpH), rate of synthesis of zeaxanthin, and heat dissipation were higher than those of the leaves. These results imply that cotton leaves under high light conditions primarily depend on CEF to activate ATP synthase and optimize ATP/NADPH. In contrast, bracts mainly protect photosynthesis by establishing a ΔpH through CEF to stimulate the heat dissipation process.

Fusarium head blight monitoring in wheat ears using machine learning and multimodal data from asymptomatic to symptomatic periods

The growth of the fusarium head blight (FHB) pathogen at the grain formation stage is a deadly threat to wheat production through disruption of the photosynthetic processes of wheat spikes. Real-time nondestructive and frequent proxy detection approaches are necessary to control pathogen propagation and targeted fungicide application. Therefore, this study examined the ch\lorophyll-related phenotypes or features from spectral and chlorophyll fluorescence for FHB monitoring. A methodology is developed using features extracted from hyperspectral reflectance (HR), chlorophyll fluorescence imaging (CFI), and high-throughput phenotyping (HTP) for asymptomatic to symptomatic disease detection from two consecutive years of experiments. The disease-sensitive features were selected using the Boruta feature-selection algorithm, and subjected to machine learning-sequential floating forward selection (ML-SFFS) for optimum feature combination. The results demonstrated that the biochemical parameters, HR, CFI, and HTP showed consistent alterations during the spike-pathogen interaction. Among the selected disease sensitive features, reciprocal reflectance (RR=1/700) demonstrated the highest coefficient of determination (R ²) of 0.81, with root mean square error (RMSE) of 11.1. The multivariate k-nearest neighbor model outperformed the competing multivariate and univariate models with an overall accuracy of R ² = 0.92 and RMSE = 10.21. A combination of two to three kinds of features was found optimum for asymptomatic disease detection using ML-SFFS with an average classification accuracy of 87.04% that gradually improved to 95% for a disease severity level of 20%. The study demonstrated the fusion of chlorophyll-related phenotypes with the ML-SFFS might be a good choice for crop disease detection.

A non-destructive approach for measuring rice panicle-level photosynthetic responses using 3D-image reconstruction

BACKGROUND

Our understanding of the physiological responses of rice inflorescence (panicle) to environmental stresses is limited by the challenge of accurately determining panicle photosynthetic parameters and their impact on grain yield. This is primarily due to the lack of a suitable gas exchange methodology for panicles and non-destructive methods to accurately determine panicle surface area.

RESULTS

To address these challenges, we have developed a custom panicle gas exchange cylinder compatible with the LiCor 6800 Infra-red Gas Analyzer. Accurate surface area measurements were determined using 3D panicle imaging to normalize the panicle-level photosynthetic measurements. We observed differential responses in both panicle and flag leaf for two temperate Japonica rice genotypes (accessions TEJ-1 and TEJ-2) exposed to heat stress during early grain filling. There was a notable divergence in the relative photosynthetic contribution of flag leaf and panicles for the heat-tolerant genotype (TEJ-2) compared to the sensitive genotype (TEJ-1).

CONCLUSION

The novelty of this method is the non-destructive and accurate determination of panicle area and photosynthetic parameters, enabling researchers to monitor temporal changes in panicle physiology during the reproductive development. The method is useful for panicle-level measurements under diverse environmental stresses and is sensitive enough to evaluate genotypic variation for panicle physiology and architecture in cereals with compact inflorescences.

Stomatal Development and Gene Expression in Rice Florets

Stomata play a fundamental role in modulating the exchange of gases between plants and the atmosphere. These microscopic structures form in high numbers on the leaf epidermis and are also present on flowers. Although leaf stomata are well studied, little attention has been paid to the development or function of floral stomata. Here, we characterize in detail the spatial distribution and development of the floral stomata of the indica rice variety IR64. We show that stomatal complexes are present at low density on specific areas of the lemma, palea and anthers and are morphologically different compared to stomata found on leaves. We reveal that in the bract-like organs, stomatal development follows the same cell lineage transitions as in rice leaves and demonstrate that the overexpression of the stomatal development regulators OsEPFL9-1 and OsEPF1 leads to dramatic changes in stomatal density in rice floral organs, producing lemma with approximately twice as many stomata (OsEPFL9-1_oe) or lemma where stomata are practically absent (OsEPF1_oe). Transcriptomic analysis of developing florets also indicates that the cellular transitions during the development of floral stomata are regulated by the same genetic network used in rice leaves. Finally, although we were unable to detect an impact on plant reproduction linked to changes in the density of floral stomata, we report alterations in global gene expression in lines overexpressing OsEPF1 and discuss how our results reflect on the possible role(s) of floral stomata.

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.

Hyperspectral Reflectance Proxies to Diagnose In-Field Fusarium Head Blight in Wheat with Machine Learning

Hyperspectral reflectance (HR) technology as proxy approach to diagnose fusarium head blight (FHB) in wheat crop could be a real-time and non-invasive approach for its in-field management to reduce grain damage. In-field canopy’s non-imaging HR (400–2400 nm using ground-based spectrometer system), photosynthesis rate (Pn) and disease severity (DS) data were simultaneously acquired from artificially inoculated wheat plots over a period of two years (2020 and 2021) in the field. Subsequently, continuous wavelet transform (CWT) was employed to select the consistent spectral bands (CSBs) and to develop the canopy-based difference indices with criterion of variable importance score using random forest—recursive feature elimination. Thereby, different machine learning algorithms were employed for FHB classification and multivariate estimation, and linear regression models to evaluate the newly developed indices against conventional vegetation indices. The results showed that inoculation reduced the Pn rate of spikes, elevated reflectance in visible and short-wave infrared regions and decreased in near infrared region at different days after inoculation (DAI). CWT analysis selected five CSBs (401, 460, 570, 786 and 840 nm) employing datasets from 2020 and 2021. These spectral bands were employed to develop wheat fusarium canopy indices (WFCI1 and WFCI2). Considering the average classification accuracy (ACA) in both years of experiments, WFCI1 manifested a maximum ACA of 75% at 5 DAI with DS of 9.73% which raised to 100% at 10 DAI with a DS of 18%. ACA mentions the averaged results of all machine learning classifiers (MLC). While in the perspective of MLC, random forest (RF) outperformed the rest of the MLC, individually, it revealed 100% classification accuracy through WFCI1 at DS 10.78% on the eight DAI. The univariate estimation of disease based on WFCI1 and WFCI2 with independent data produced R2 and root mean square error (RMSE) values of 0.80 and 14.7, and 0.81 and13.50, respectively. However, Knn regression analysis with both canopy indices (WFCI1 and WFCI2) manifested the maximum accuracy for disease estimation with RMSE of 11.61 and R2 = 0.83. Conclusively, the newly proposed HR indices show great potential as proxy approach for detecting FHB at early stage and understanding the physical state of crops in field conditions for the better management and control of plant diseases.

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.

The Importance of Stem Photosynthesis for Two Desert Shrubs Across Different Groundwater Depths

Water availability could alter multiple ecophysiological processes such as water use strategy, photosynthesis, and respiration, thereby modifying plant water use and carbon gain. However, a lack of field observations hinders our understanding of how water availability affects stem photosynthesis at both organ and plant levels of desert shrubs. In this study, we measured gas exchange and oxygen stable isotopes to quantify water sources, stem recycling photosynthesis, and whole-plant carbon balance in two coexisting Haloxylon species (Haloxylon ammodendron and Haloxylon persicum) at different groundwater depths in the Gurbantonggut Desert. The overall aim of the study was to analyze and quantify the important role of stem recycling photosynthesis for desert shrubs (Haloxylon species) under different groundwater depths. The results showed that (1) regardless of changes in groundwater depth, H. ammodendron consistently used groundwater and H. persicum used deep soil water as their main water source, with greater than 75% of xylem water being derived from groundwater and deep soil water for the two species, respectively; (2) stem recycling photosynthesis refixed 72-81% of the stem dark respiration, and its contribution to whole-plant carbon assimilation was 10-21% for the two species; and (3) deepened groundwater increased stem water use efficiency and its contribution to whole-plant carbon assimilation in H. persicum but not in H. ammodendron. Our study provided observational evidence that deepened groundwater depth induced H. persicum to increase stem recycling photosynthetic capacity and a greater contribution to whole-plant carbon assimilation, but this did not occur on H. ammodendron. Our study indicates that stem recycling photosynthesis may play an important role in the survival of desert shrubs in drought conditions.

Limiting factors for panicle photosynthesis at the anthesis and grain filling stages in rice (Oryza sativa L.)

Panicle photosynthesis is crucial for grain yield in cereal crops; however, the limiting factors for panicle photosynthesis are poorly understood, greatly impeding improvement in this trait. In the present study, pot experiments were conducted to investigate the limiting factors for panicle photosynthesis at the anthesis stage in seven rice genotypes and to examine the temporal variations in photosynthesis during the grain filling stage in the Liangyou 287 genotype. At the anthesis stage, leaf and panicle photosynthesis was positively correlated with stomatal conductance and maximum carboxylation rate, which were in turn associated with hydraulic conductance and nitrogen content, respectively. Panicle hydraulic conductance was positively correlated with the area of bundle sheaths in the panicle neck. During grain filling, leaf and panicle photosynthesis remained constant at the early stage but dramatically decreased from 8 to 9 days after anthesis. The trends of variations in panicle photosynthesis were consistent with those in stomatal conductance but not with those in maximum carboxylation rate. At first, the maximum carboxylation rate and respiration rate in the panicle increased, through elevated panicle nitrogen content, but then drastically decreased, as a result of dehydration. The present study systematically investigated the limiting factors for panicle photosynthesis, which are vital for improving photosynthesis and crop yield.

Diurnal and Seasonal Variations of Photosynthetic Energy Conversion Efficiency of Field Grown Wheat

Improving canopy photosynthetic light use efficiency and energy conversion efficiency (ε _c ) is a major option to increase crop yield potential. However, so far, the diurnal and seasonal variations of canopy light use efficiency (LUE) and ε _c are largely unknown due to the lack of an efficient method to estimate ε _c in a high temporal resolution. Here we quantified the dynamic changes of crop canopy LUE and ε _c during a day and a growing season with the canopy gas exchange method. A response curve of whole-plant carbon dioxide (CO₂) flux to incident photosynthetically active radiation (PAR) was further used to calculate ε _c and LUE at a high temporal resolution. Results show that the LUE of two wheat cultivars with different canopy architectures at five stages varies between 0.01 to about 0.05 mol CO₂ mol^-1 photon, with the LUE being higher under medium PAR. Throughout the growing season, the ε _c varies from 0.5 to 3.7% (11-80% of the maximal ε _c for C₃ plants) with incident PAR identified as a major factor controlling variation of ε _c . The estimated average ε _c from tillering to grain filling stages was about 2.17%, i.e., 47.2% of the theoretical maximal. The estimated season-averaged radiation use efficiency (RUE) was 1.5-1.7 g MJ^-1, which was similar to the estimated RUE based on biomass harvesting. The large variations of LUE and ε _c imply a great opportunity to improve canopy photosynthesis for greater wheat biomass and yield potential.

Boll-leaf system gas exchange and its application in the analysis of cotton photosynthetic function

Estimating the boll development and boll yield from single-leaf photosynthesis is difficult as the source-sink relationship of cotton (Gossypium hirsutum L.) is complicated. As the boll-leaf system (BLS), which includes the main-stem leaf, sympodial leaf, and non-leaf organs, is the basic unit of the cotton source-sink relationship and yield formation, the concept of "BLS photosynthesis" is introduced in this study. We speculate that the characteristics of BLS gas exchange can more accurately reflect the photosynthetic function of the system, thus revealing the law of photosynthesis in the process of boll development. The results showed that the photosynthetic rate of single leaves measured by a BLS chamber was consistent with that measured by a standard single-leaf chamber. BLSs exhibited typical light response curves, and the shape of the curves was similar to those of single leaves. The light compensation point and respiration rate of BLSs were higher than those of single leaves, while the apparent quantum efficiency of BLSs was lower. Compared with single leaves, the duration of the photosynthetic function of BLSs was longer. Increasing plant density decreased the gas exchange rate per unit BLS more significantly under field conditions. There was a better linear correlation between the net CO₂ assimilation rate, respiration rate of BLSs and boll biomass. Therefore, we think that the gas exchange of BLSs can better reveal the changes in photosynthetic function of BLSs and boll development. This provides a new basis for analyzing the mechanism and regulation of cotton yield formation.

The potential of resilient carbon dynamics for stabilizing crop reproductive development and productivity during heat stress

Impaired carbon metabolism and reproductive development constrain crop productivity during heat stress. Reproductive development is energy intensive, and its requirement for respiratory substrates rises as associated metabolism increases with temperature. Understanding how these processes are integrated and the extent to which they contribute to the maintenance of yield during and following periods of elevated temperatures is important for developing climate-resilient crops. Recent studies are beginning to demonstrate links between processes underlying carbon dynamics and reproduction during heat stress, consequently a summation of research that has been reported thus far and an evaluation of purported associations are needed to guide and stimulate future research. To this end, we review recent studies relating to source-sink dynamics, non-foliar photosynthesis and net carbon gain as pivotal in understanding how to improve reproductive development and crop productivity during heat stress. Rapid and precise phenotyping during narrow phenological windows will be important for understanding mechanisms underlying these processes, thus we discuss the development of relevant high-throughput phenotyping approaches that will allow for more informed decision-making regarding future crop improvement.

Improving crop yield and resilience through optimization of photosynthesis: panacea or pipe dream?

Increasing the speed of breeding to enhance crop productivity and adaptation to abiotic stresses is urgently needed. The perception that a second Green Revolution should be implemented is widely established within the scientific community and among stakeholders. In recent decades, different alternatives have been proposed for increasing crop yield through manipulation of leaf photosynthetic efficiency. However, none of these has delivered practical or relevant outputs. Indeed, the actual increases in photosynthetic rates are not expected to translate into yield increases beyond 10-15%. Furthermore, instantaneous rates of leaf photosynthesis are not necessarily the reference target for research. Yield is the result of canopy photosynthesis, understood as the contribution of laminar and non-laminar organs over time, within which concepts such as canopy architecture, stay-green, or non-laminar photosynthesis need to be taken into account. Moreover, retrospective studies show that photosynthetic improvements have been more common at the canopy level. Nevertheless, it is crucial to place canopy photosynthesis in the context of whole-plant functioning, which includes sink-source balance and transport of photoassimilates, and the availability and uptake of nutrients, such as nitrogen in particular. Overcoming this challenge will only be feasible if a multiscale crop focus combined with a multidisciplinary scientific approach is adopted.