Dynamic leaf energy balance: deriving stomatal conductance from thermal imaging in a dynamic environment

Modern phenomics to empower holistic crop science, agronomy, and breeding research

Crop phenomics enables the collection of diverse plant traits for a large number of samples along different time scales, representing a greater data collection throughput compared with traditional measurements. Most modern crop phenomics use different sensors to collect reflective, emitted, and fluorescence signals, etc., from plant organs at different spatial and temporal resolutions. Such multi-modal, high-dimensional data not only accelerates basic research on crop physiology, genetics, and whole plant systems modeling, but also supports the optimization of field agronomic practices, internal environments of plant factories, and ultimately crop breeding. Major challenges and opportunities facing the current crop phenomics research community include developing community consensus or standards for data collection, management, sharing, and processing, developing capabilities to measure physiological parameters, and enabling farmers and breeders to effectively use phenomics in the field to directly support agricultural production.

Inside-out: Synergising leaf biochemical traits with stomatal-regulated water fluxes to enhance transpiration modelling during abiotic stress

As the global climate continues to change, plants will increasingly experience abiotic stress(es). Stomata on leaf surfaces are the gatekeepers to plant interiors, regulating gaseous exchanges that are crucial for both photosynthesis and outward water release. To optimise future crop productivity, accurate modelling of how stomata govern plant-environment interactions will be crucial. Here, we synergise optical and thermal imaging data to improve modelled transpiration estimates during water and/or nutrient stress (where leaf N is reduced). By utilising hyperspectral data and partial least squares regression analysis of six plant traits and fluxes in wheat (Triticum aestivum), we develop a new spectral vegetation index; the Combined Nitrogen and Drought Index (CNDI), which can be used to detect both water stress and/or nitrogen deficiency. Upon full stomatal closure during drought, CNDI shows a strong relationship with leaf water content (r2 = 0.70), with confounding changes in leaf biochemistry. By incorporating CNDI transformed with a sigmoid function into thermal-based transpiration modelling, we have increased the accuracy of modelling water fluxes during abiotic stress. These findings demonstrate the potential of using combined optical and thermal remote sensing-based modelling approaches to dynamically model water fluxes to improve both agricultural water usage and yields.

Alternative method for determining leaf CO2 assimilation without gas exchange measurements: Performance, comparison and sensitivity analysis

We present an alternative method to determine leaf CO2 assimilation rate (An ), eliminating the need for gas exchange measurements in proximal and remote sensing. This method combines the Farquhar-von Caemmerer-Berry photosynthesis model with mechanistic light reaction (MLR) theory and leaf energy balance (EB) analysis. The MLR theory estimates the actual electron transport rate (J) by leveraging chlorophyll fluorescence via pulse amplitude-modulated fluorometry for proximal sensing or sun-induced chlorophyll fluorescence measurements for remote sensing, along with spectral reflectance. The EB equation is used to directly estimate stomatal conductance from leaf temperature. In wheat and soybean, the MLR-EB model successfully estimated An variations, including midday depression, under various environmental and phenological conditions. Sensitivity analysis revealed that the leaf boundary layer conductance (gb ) played an equal, if not more, crucial role compared to the variables for J. This was primarily caused by the indirect influence of gb through the EB equation rather than its direct impact on convective CO2 exchange on the leaf. Although the MLR-EB model requires an accurate estimation of gb , it can potentially reduce uncertainties and enhance applicability in photosynthesis assessment when gas exchange measurements are unavailable.

Speedy stomata of a C4 plant correlate with enhanced K+ channel gating

Stomata are microscopic pores at the surface of plant leaves that facilitate gaseous diffusion to support photosynthesis. The guard cells around each stoma regulate the pore aperture. Plants that carry out C4 photosynthesis are usually more resilient than C3 plants to stress, and their stomata operate over a lower dynamic range of CO2 within the leaf. What makes guard cells of C4 plants more responsive than those of C3 plants? We used gas exchange and electrophysiology, comparing stomatal kinetics of the C4 plant Gynandropsis gynandra and the phylogenetically related C3 plant Arabidopsis thaliana. We found, with varying CO2 and light, that Gynandropsis showed faster changes in stomata conductance and greater water use efficiency when compared with Arabidopsis. Electrophysiological analysis of the dominant K+ channels showed that the outward-rectifying channels, responsible for K+ loss during stomatal closing, were characterised by a greater maximum conductance and substantial negative shift in the voltage dependence of gating, indicating a reduced inhibition by extracellular K+ and enhanced capacity for K+ flux. These differences correlated with the accelerated stomata kinetics of Gynandropsis, suggesting that subtle changes in the biophysical properties of a key transporter may prove a target for future efforts to engineer C4 stomatal kinetics.

Rapid spatial assessment of leaf-absorbed irradiance

Image-based high-throughput phenotyping promises the rapid determination of functional traits in large plant populations. However, interpretation of some traits - such as those related to photosynthesis or transpiration rates - is only meaningful if the irradiance absorbed by the measured leaves is known, which can differ greatly between different parts of the same plant and within canopies. No feasible method currently exists to rapidly measure absorbed irradiance in three-dimensional plants and canopies. We developed a method and protocols to derive absorbed irradiance at any visible part of a canopy with a thermal camera, by fitting a leaf energy balance model to transient changes in leaf temperature. Leaves were exposed to short light pulses (30 s) that were not long enough to trigger stomatal opening but strong enough to induce transient changes in leaf temperature that was proportional to the absorbed irradiance. The method was successfully validated against point measurements of absorbed irradiance in plant species with relatively simple architecture (sweet pepper, cucumber, tomato, and lettuce). Once calibrated, the model was used to produce absorbed irradiance maps from thermograms. Our method opens new avenues for the interpretation of plant responses derived from imaging techniques and can be adapted to existing high-throughput phenotyping platforms.

The interaction between titanium dioxide nanoparticles and light can have dualistic effects on the physiological responses of plants

The model plant Arabidopsis thaliana was exposed to combined stress factors, i.e., titanium dioxide nanoparticles (TiNPs) and high light. The concentrations of TiNPs used for irrigation were 250, 500, and 1000 μg/mL. This study shows that TiNPs alter the morphology and nanomechanical properties of chloroplasts in A. thaliana, which leads to a decrease in membrane elasticity. We found that TiNPs contributed to a delay in the thermal response of A. thaliana under dynamic light conditions, as revealed by non-invasive thermal imaging. The thermal time constants of TiNP-treated plants under excessive light are determined, showing a shortening in comparison to control plants. The results indicate that TiNPs may contribute to an alleviation of temperature stress experienced by plants under exposure to high light. In this research, we observed a decline in photosystem II photochemical efficiency accompanied by an increase in energy dissipation upon exposure to TiNPs. Interestingly, concentrations exceeding 250 µg/mL TiNPs appeared to mitigate the effects of high light, as shown by reduced differences in the values of specific OJIP parameters (FV/FM, ABS/RC, DI0/RC, and Pi_Abs) before and after light exposure.

Tools for Measuring Photosynthesis at Different Scales

Measurements of in vivo photosynthesis are powerful tools that probe the largest fluxes of carbon and energy in an illuminated leaf, but often the specific techniques used are so varied and specialized that it is difficult for researchers outside the field to select and perform the most useful assays for their research questions. The goal of this chapter is to provide a broad overview of the current tools available for the study of photosynthesis, both in vivo and in vitro, so as to provide a foundation for selecting appropriate techniques, many of which are presented in detail in subsequent chapters. This chapter will also organize current methods into a comparative framework and provide examples of how they have been applied to research questions of broad agronomical, ecological, or biological importance. This chapter closes with an argument that the future of in vivo measurements of photosynthesis lies in the ability to use multiple methods simultaneously and discusses the benefits of this approach to currently open physiological questions. This chapter, combined with the relevant methods chapters, could serve as a laboratory course in methods in photosynthesis research or as part of a more comprehensive laboratory course in general plant physiology methods.

Using Infrared Thermography for High-Throughput Plant Phenotyping

Infrared thermography offers a rapid, noninvasive method for measuring plant temperature, which provides a proxy for stomatal conductance and plant water status and can therefore be used as an index for plant stress. Thermal imaging can provide an efficient method for high-throughput screening of large numbers of plants. This chapter provides guidelines for using thermal imaging equipment and illustrative methodologies, coupled with essential considerations, to access plant physiological processes.

Monitoring of drought stress and transpiration rate using proximal thermal and hyperspectral imaging in an indoor automated plant phenotyping platform

BACKGROUND

Thermography is a popular tool to assess plant water-use behavior, as plant temperature is influenced by transpiration rate, and is commonly used in field experiments to detect plant water deficit. Its application in indoor automated phenotyping platforms is still limited and mainly focuses on differences in plant temperature between genotypes or treatments, instead of estimating stomatal conductance or transpiration rate. In this study, the transferability of commonly used thermography analysis protocols from the field to greenhouse phenotyping platforms was evaluated. In addition, the added value of combining thermal infrared (TIR) with hyperspectral imaging to monitor drought effects on plant transpiration rate (E) was evaluated.

RESULTS

The sensitivity of commonly used TIR indices to detect drought-induced and genotypic differences in water status was investigated in eight maize inbred lines in the automated phenotyping platform PHENOVISION. Indices that normalized plant temperature for vapor pressure deficit and/or air temperature at the time of imaging were most sensitive to drought and could detect genotypic differences in the plants' water-use behavior. However, these indices were not strongly correlated to stomatal conductance and E. The canopy temperature depression index, the crop water stress index and the simplified stomatal conductance index were more suitable to monitor these traits, and were consequently used to develop empirical E prediction models by combining them with hyperspectral indices and/or environmental variables. Different modeling strategies were evaluated, including single index-based, machine learning and mechanistic models. Model comparison showed that combining multiple TIR indices in a random forest model can improve E prediction accuracy, and that the contribution of the hyperspectral data is limited when multiple indices are used. However, the empirical models trained on one genotype were not transferable to all eight inbred lines.

CONCLUSION

Overall, this study demonstrates that existing TIR indices can be used to monitor drought stress and develop E prediction models in an indoor setup, as long as the indices normalize plant temperature for ambient air temperature or relative humidity.

Detailed in situ leaf energy budget permits the assessment of leaf aerodynamic resistance as a key to enhance non-evaporative cooling under drought

The modulation of the leaf energy budget components to maintain optimal leaf temperature are fundamental aspects of plant functioning and survival. Better understanding these aspects becomes increasingly important under a drying and warming climate when cooling through evapotranspiration (E) is suppressed. Combining novel measurements and theoretical estimates, we obtained unusually comprehensive twig-scale leaf energy budgets under extreme field conditions in droughted (suppressed E) and non-droughted (enhanced E) plots of a semi-arid pine forest. Under the same high mid-summer radiative load, leaf cooling shifted from relying on nearly equal contributions of sensible (H) and latent (LE) energy fluxes in non-droughted trees to relying almost exclusively on H in droughted ones, with no change in leaf temperature. Relying on our detailed leaf energy budget, we could demonstrate that this is due to a 2× reduction in leaf aerodynamic resistance. This capability for LE-to-H shift in leaves of mature Aleppo pine trees under droughted field conditions without increasing leaf temperature is likely a critical factor in the resilience and relatively high productivity of this important Mediterranean tree species under drying conditions.

The impact of growth at elevated [CO2] on stomatal anatomy and behavior differs between wheat species and cultivars

The ability of plants to respond to changes in the environment is crucial to their survival and reproductive success. The impact of increasing the atmospheric CO2 concentration (a[CO2]), mediated by behavioral and developmental responses of stomata, on crop performance remains a concern under all climate change scenarios, with potential impacts on future food security. To identify possible beneficial traits that could be exploited for future breeding, phenotypic variation in morphological traits including stomatal size and density, as well as physiological responses and, critically, the effect of growth [CO2] on these traits, was assessed in six wheat relative accessions (including Aegilops tauschii, Triticum turgidum ssp. Dicoccoides, and T. turgidum ssp. dicoccon) and five elite bread wheat T. aestivum cultivars. Exploiting a range of different species and ploidy, we identified key differences in photosynthetic capacity between elite hexaploid wheat and wheat relatives. We also report differences in the speed of stomatal responses which were found to be faster in wheat relatives than in elite cultivars, a trait that could be useful for enhanced photosynthetic carbon gain and water use efficiency. Furthermore, these traits do not all appear to be influenced by elevated [CO2], and determining the underlying genetics will be critical for future breeding programmes.

A simple system for phenotyping of plant transpiration and stomatal conductance response to drought

Plant breeding for increased crop water use efficiency or drought stress resistance requires methods to quickly assess the transpiration rate (E) and stomatal conductance (g_s) of a large number of individual plants. Several methods to measure E and g_s exist, each of which has its own advantages and shortcomings. To add to this toolbox, we developed a method that uses whole-plant thermal imaging in a controlled environment, where aerial humidity is changed rapidly to induce changes in E that are reflected in changes in leaf temperature. This approach is based on a simplified energy balance equation, without the need for a reference material or complicated calculations. To test this concept, we built a double-sided, perforated, open-top plexiglass chamber that was supplied with air at a high flow rate (35 L min^-1) and whose relative humidity (RH) could be switched rapidly. Measurements included air and leaf temperature as well as RH. Using several well-watered and drought stressed genotypes of Arabidopsis thaliana that were exposed to multiple cycles in RH (30-50 % and back), we showed that leaf temperature as measured in our system correlated well with E and g_s measured in a commercial gas exchange system. Our results demonstrate that, at least within a given species, the differences in leaf temperature under several RH can be used as a proxy for E and g_s. Given that this method is fairly quick, noninvasive and remote, we envision that it could be upscaled for work within rapid plant phenotyping systems.

Use of thermal imaging and the photochemical reflectance index (PRI) to detect wheat response to elevated CO2 and drought

The spectral-based photochemical reflectance index (PRI) and leaf surface temperature (Tleaf ) derived from thermal imaging are two indicative metrics of plant functioning. The relationship of PRI with radiation-use efficiency (RUE) and Tleaf with leaf transpiration could be leveraged to monitor crop photosynthesis and water use from space. Yet, it is unclear how such relationships will change under future high carbon dioxide concentrations ([CO2 ]) and drought. Here we established an [CO2 ] enrichment experiment in which three wheat genotypes were grown at ambient (400 ppm) and elevated (550 ppm) [CO2 ] and exposed to well-watered and drought conditions in two glasshouse rooms in two replicates. Leaf transpiration (Tr ) and latent heat flux (LE) were derived to assess evaporative cooling, and RUE was calculated from assimilation and radiation measurements on several dates along the season. Simultaneous hyperspectral and thermal images were taken at~ $\unicode{x0007E}$ 1.5 m from the plants to derive PRI and the temperature difference between the leaf and its surrounding air (∆ $\unicode{x02206}$ Tleaf-air ). We found significant PRI and RUE and∆ $\unicode{x02206}$ Tleaf-air and Tr correlations, with no significant differences among the genotypes. A PRI-RUE decoupling was observed under drought at ambient [CO2 ] but not at elevated [CO2 ], likely due to changes in photorespiration. For a LE range of 350 W m-2 , the ΔTleaf-air range was~ $\unicode{x0007E}$ 10°C at ambient [CO2 ] and only~ $\unicode{x0007E}$ 4°C at elevated [CO2 ]. Thicker leaves in plants grown at elevated [CO2 ] suggest higher leaf water content and consequently more efficient thermoregulation at high [CO2 ] conditions. In general, Tleaf was maintained closer to the ambient temperature at elevated [CO2 ], even under drought. PRI, RUE, ΔTleaf -air , and Tr decreased linearly with canopy depth, displaying a single PRI-RUE and ΔTleaf -air  Tr model through the canopy layers. Our study shows the utility of these sensing metrics in detecting wheat responses to future environmental changes.

Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives

Plant phenomics (PP) has been recognized as a bottleneck in studying the interactions of genomics and environment on plants, limiting the progress of smart breeding and precise cultivation. High-throughput plant phenotyping is challenging owing to the spatio-temporal dynamics of traits. Proximal and remote sensing (PRS) techniques are increasingly used for plant phenotyping because of their advantages in multi-dimensional data acquisition and analysis. Substantial progress of PRS applications in PP has been observed over the last two decades and is analyzed here from an interdisciplinary perspective based on 2972 publications. This progress covers most aspects of PRS application in PP, including patterns of global spatial distribution and temporal dynamics, specific PRS technologies, phenotypic research fields, working environments, species, and traits. Subsequently, we demonstrate how to link PRS to multi-omics studies, including how to achieve multi-dimensional PRS data acquisition and processing, how to systematically integrate all kinds of phenotypic information and derive phenotypic knowledge with biological significance, and how to link PP to multi-omics association analysis. Finally, we identify three future perspectives for PRS-based PP: (1) strengthening the spatial and temporal consistency of PRS data, (2) exploring novel phenotypic traits, and (3) facilitating multi-omics communication.

Physiological and Molecular Approaches for Developing Thermotolerance in Vegetable Crops: A Growth, Yield and Sustenance Perspective

Vegetables are a distinct collection of plant-based foods that vary in nutritional diversity and form an important part of the healthy diet of the human being. Besides providing basic nutrition, they have great potential for boosting human health. The balanced consumption of vegetables is highly recommended for supplementing the human body with better nutrition density, dietary fiber, minerals, vitamins, and bioactive compounds. However, the production and quality of fresh vegetables are influenced directly or indirectly by exposure to high temperatures or heat stress (HS). A decline in quality traits and harvestable yield are the most common effects of HS among vegetable crops. Heat-induced morphological damage, such as poor vegetative growth, leaf tip burning, and rib discoloration in leafy vegetables and sunburn, decreased fruit size, fruit/pod abortion, and unfilled fruit/pods in beans, are common, often rendering vegetable cultivation unprofitable. Further studies to trace down the possible physiological and biochemical effects associated with crop failure reveal that the key factors include membrane damage, photosynthetic inhibition, oxidative stress, and damage to reproductive tissues, which may be the key factors governing heat-induced crop failure. The reproductive stage of plants has extensively been studied for HS-induced abnormalities. Plant reproduction is more sensitive to HS than the vegetative stages, and affects various reproductive processes like pollen germination, pollen load, pollen tube growth, stigma receptivity, ovule fertility and, seed filling, resulting in poorer yields. Hence, sound and robust adaptation and mitigation strategies are needed to overcome the adverse impacts of HS at the morphological, physiological, and biochemical levels to ensure the productivity and quality of vegetable crops. Physiological traits such as the stay-green trait, canopy temperature depression, cell membrane thermostability, chlorophyll fluorescence, relative water content, increased reproductive fertility, fruit numbers, and fruit size are important for developing better yielding heat-tolerant varieties/cultivars. Moreover, various molecular approaches such as omics, molecular breeding, and transgenics, have been proved to be useful in enhancing/incorporating tolerance and can be potential tools for developing heat-tolerant varieties/cultivars. Further, these approaches will provide insights into the physiological and molecular mechanisms that govern thermotolerance and pave the way for engineering "designer" vegetable crops for better health and nutritional security. Besides these approaches, agronomic methods are also important for adaptation, escape and mitigation of HS protect and improve yields.

Lack of coordination between stomatal and vein traits provides functional benefits to the dioecious tropical tree Myrsine coriacea

Climate change will affect the distribution of many tropical plant species. However, the understanding of how dioecious tropical species cope with different environmental conditions is still limited. To address this issue, we investigated how secondary trait attributes in populations of the dioecious tropical tree Myrsine coriacea change along an altitudinal gradient. Eighty individual plants (40 male and 40 female) were selected among seven natural populations. Leaf variation in morphological and stomatal traits, and carbon and nitrogen isotopic compositions were analyzed. Female plants had greater isotopic leaf carbon composition (δ¹³ C) and nitrogen content than male plants, increasing their carboxylation capacity. Plants of both sexes had smaller stomata, greater water-use efficiency (greater δ¹³ C), and greater nitrogen isotopic composition (δ¹⁵ N) at higher altitudes. They also showed lower δ¹⁵ N and had greater carbon: nitrogen ratios at lower altitudes. There was a lack of coordination between stomatal and vein traits, which was compensated for by variation in specific leaf areas. This mechanism was essential for increasing plant performance under the limiting conditions found by the species at higher altitudes.

Phenotyping stomatal closure by thermal imaging for GWAS and TWAS of water use efficiency-related genes

Stomata allow CO2 uptake by leaves for photosynthetic assimilation at the cost of water vapor loss to the atmosphere. The opening and closing of stomata in response to fluctuations in light intensity regulate CO2 and water fluxes and are essential for maintaining water-use efficiency (WUE). However, a little is known about the genetic basis for natural variation in stomatal movement, especially in C4 crops. This is partly because the stomatal response to a change in light intensity is difficult to measure at the scale required for association studies. Here, we used high-throughput thermal imaging to bypass the phenotyping bottleneck and assess 10 traits describing stomatal conductance (gs) before, during and after a stepwise decrease in light intensity for a diversity panel of 659 sorghum (Sorghum bicolor) accessions. Results from thermal imaging significantly correlated with photosynthetic gas exchange measurements. gs traits varied substantially across the population and were moderately heritable (h2 up to 0.72). An integrated genome-wide and transcriptome-wide association study identified candidate genes putatively driving variation in stomatal conductance traits. Of the 239 unique candidate genes identified with the greatest confidence, 77 were putative orthologs of Arabidopsis (Arabidopsis thaliana) genes related to functions implicated in WUE, including stomatal opening/closing (24 genes), stomatal/epidermal cell development (35 genes), leaf/vasculature development (12 genes), or chlorophyll metabolism/photosynthesis (8 genes). These findings demonstrate an approach to finding genotype-to-phenotype relationships for a challenging trait as well as candidate genes for further investigation of the genetic basis of WUE in a model C4 grass for bioenergy, food, and forage production.

Current status and future challenges in implementing and upscaling vertical farming systems

Vertical farming can produce food in a climate-resilient manner, potentially emitting zero pesticides and fertilizers, and with lower land and water use than conventional agriculture. Vertical farming systems (VFS) can meet daily consumer demands for nutritious fresh products, forming a part of resilient food systems-particularly in and around densely populated areas. VFS currently produce a limited range of crops including fruits, vegetables and herbs, but successful implementation of vertical farming as part of mainstream agriculture will require improvements in profitability, energy efficiency, public policy and consumer acceptance. Here we discuss VFS as multi-layer indoor crop cultivation systems, exploring state-of-the-art vertical farming and future challenges in the fields of plant growth, product quality, automation, robotics, system control and environmental sustainability and how research and development, socio-economic and policy-related institutions must work together to ensure successful upscaling of VFS to future food systems.

Explainable machine learning models of major crop traits from satellite-monitored continent-wide field trial data

Four species of grass generate half of all human-consumed calories. However, abundant biological data on species that produce our food remain largely inaccessible, imposing direct barriers to understanding crop yield and fitness traits. Here, we assemble and analyse a continent-wide database of field experiments spanning 10 years and hundreds of thousands of machine-phenotyped populations of ten major crop species. Training an ensemble of machine learning models, using thousands of variables capturing weather, ground sensor, soil, chemical and fertilizer dosage, management and satellite data, produces robust cross-continent yield models exceeding R² = 0.8 prediction accuracy. In contrast to 'black box' analytics, detailed interrogation of these models reveals drivers of crop behaviour and complex interactions predicting yield and agronomic traits. These results demonstrate the capacity of machine learning models to interrogate large datasets, generate new and testable outputs and predict crop behaviour, highlighting the powerful role of data in the future of food.

Towards a dynamic photosynthesis model to guide yield improvement in C4 crops

The most productive C4 food and biofuel crops, such as Saccharum officinarum (sugarcane), Sorghum bicolor (sorghum) and Zea mays (maize), all use NADP-ME-type C4 photosynthesis. Despite high productivities, these crops fall well short of the theoretical maximum solar conversion efficiency of 6%. Understanding the basis of these inefficiencies is key for bioengineering and breeding strategies to increase the sustainable productivity of these major C4 crops. Photosynthesis is studied predominantly at steady state in saturating light. In field stands of these crops light is continually changing, and often with rapid fluctuations. Although light may change in a second, the adjustment of photosynthesis may take many minutes, leading to inefficiencies. We measured the rates of CO₂ uptake and stomatal conductance of maize, sorghum and sugarcane under fluctuating light regimes. The gas exchange results were combined with a new dynamic photosynthesis model to infer the limiting factors under non-steady-state conditions. The dynamic photosynthesis model was developed from an existing C4 metabolic model for maize and extended to include: (i) post-translational regulation of key photosynthetic enzymes and their temperature responses; (ii) dynamic stomatal conductance; and (iii) leaf energy balance. Testing the model outputs against measured rates of leaf CO₂ uptake and stomatal conductance in the three C4 crops indicated that Rubisco activase, the pyruvate phosphate dikinase regulatory protein and stomatal conductance are the major limitations to the efficiency of NADP-ME-type C4 photosynthesis during dark-to-high light transitions. We propose that the level of influence of these limiting factors make them targets for bioengineering the improved photosynthetic efficiency of these key crops.

Correlation and co-localization of QTL for stomatal density, canopy temperature, and productivity with and without drought stress in Setaria

Mechanistic modeling indicates that stomatal conductance could be reduced to improve water use efficiency (WUE) in C4 crops. Genetic variation in stomatal density and canopy temperature was evaluated in the model C4 genus, Setaria. Recombinant inbred lines (RILs) derived from a Setaria italica×Setaria viridis cross were grown with ample or limiting water supply under field conditions in Illinois. An optical profilometer was used to rapidly assess stomatal patterning, and canopy temperature was measured using infrared imaging. Stomatal density and canopy temperature were positively correlated but both were negatively correlated with total above-ground biomass. These trait relationships suggest a likely interaction between stomatal density and the other drivers of water use such as stomatal size and aperture. Multiple quantitative trait loci (QTL) were identified for stomatal density and canopy temperature, including co-located QTL on chromosomes 5 and 9. The direction of the additive effect of these QTL on chromosome 5 and 9 was in accordance with the positive phenotypic relationship between these two traits. This, along with prior experiments, suggests a common genetic architecture between stomatal patterning and WUE in controlled environments with canopy transpiration and productivity in the field, while highlighting the potential of Setaria as a model to understand the physiology and genetics of WUE in C4 species.

Thermal Analysis of Stomatal Response under Salinity and High Light

A non-destructive thermal imaging method was used to study the stomatal response of salt-treated Arabidopsis thaliana plants to excessive light. The plants were exposed to different levels of salt concentrations (0, 75, 150, and 220 mM NaCl). Time-dependent thermograms showed the changes in the temperature distribution over the lamina and provided new insights into the acute light-induced temporary response of Arabidopsis under short-term salinity. The initial response of plants, which was associated with stomatal aperture, revealed an exponential growth in temperature kinetics. Using a single-exponential function, we estimated the time constants of thermal courses of plants exposed to acute high light. The saline-induced impairment in stomatal movement caused the reduced stomatal conductance and transpiration rate. Limited transpiration of NaCl-treated plants resulted in an increased rosette temperature and decreased thermal time constants as compared to the controls. The net CO₂ assimilation rate decreased for plants exposed to 220 mM NaCl; in the case of 75 mM NaCl treatment, an increase was observed. A significant decline in the maximal quantum yield of photosystem II under excessive light was noticeable for the control and NaCl-treated plants. This study provides evidence that thermal imaging as a highly sensitive technique may be useful for analyzing the stomatal aperture and movement under dynamic environmental conditions.

LED and HPS Supplementary Light Differentially Affect Gas Exchange in Tomato Leaves

Using light emitting diodes (LED) instead of conventionally used high pressure sodium (HPS) lamps as a supplemental light source in greenhouses results in a higher efficacy (µmol light per J electricity) and makes it possible to customize the light spectrum. To explore the effects of LED and HPS on gas exchange, thermal relations, photosynthesis, and water status of young tomato plants, seven genotypes were grown in a greenhouse under LED (95% red, 5% blue) or HPS lamps in four experiments differing in the fraction of lamp light over natural light. HPS lights emit a broader spectrum of red (40%), green–yellow (50%), blue (5%), and far-red (5%) and a substantial amount of infrared radiation (heat). Young tomato plants grown under LED showed lower leaf temperature and higher stomatal density, stomatal conductance (g_s) and transpiration rate (E) than plants grown under HPS; this may be due to the different supplemental light spectrum. The young plants grown under LED tended to have increased photosynthetic capacity. Furthermore, the water stress indices CWSI and I_G, which were obtained using thermal imaging, were positively correlated with gas exchange-derived g_s and E, putting forward the use of thermal imaging for the phenotyping of transpiration. Under LED light, photosynthetic gas exchange was generally increased, which agreed with the water stress indices. The extent of this increase was genotype-dependent. All differences between LED and HPS were smaller in the experiments where the fraction of lamp light over natural light was smaller.

Dynamic thermal imaging confirms local but not fast systemic ABA responses

Abscisic acid (ABA) signals regulating stomatal aperture and water loss are usually studied in detached leaves or isolated epidermal peels and at infrequent timepoints. Measuring stomatal ABA responses in attached leaves across a time course enables the study of stomatal behaviour in the physiological context of the plant. Infrared thermal imaging is often used to characterize steady-state stomatal conductance via comparisons of leaf surface temperature but is rarely used to capture stomatal responses over time or across different leaf surfaces. We used dynamic thermal imaging as a robust, but sensitive, tool to observe stomatal ABA responses in a whole plant context. We detected stomatal responses to low levels of ABA in both monocots and dicots and identified differences between the responses of different leaves. Using whole plant thermal imaging, stomata did not always behave as described previously for detached samples: in Arabidopsis, we found no evidence for fast systemic ABA-induced stomatal closure, and in barley, we observed no requirement for exogenous nitrate during ABA-induced stomatal closure. Thus, we recommend dynamic thermal imaging as a useful approach to complement detached sample assays for the study of local and systemic stomatal responses and molecular mechanisms underlying stomatal responses to ABA in the whole plant context.

Past and Future of Plant Stress Detection: An Overview From Remote Sensing to Positron Emission Tomography

Plant stress detection is considered one of the most critical areas for the improvement of crop yield in the compelling worldwide scenario, dictated by both the climate change and the geopolitical consequences of the Covid-19 epidemics. A complicated interconnection of biotic and abiotic stressors affect plant growth, including water, salt, temperature, light exposure, nutrients availability, agrochemicals, air and soil pollutants, pests and diseases. In facing this extended panorama, the technology choice is manifold. On the one hand, quantitative methods, such as metabolomics, provide very sensitive indicators of most of the stressors, with the drawback of a disruptive approach, which prevents follow up and dynamical studies. On the other hand qualitative methods, such as fluorescence, thermography and VIS/NIR reflectance, provide a non-disruptive view of the action of the stressors in plants, even across large fields, with the drawback of a poor accuracy. When looking at the spatial scale, the effect of stress may imply modifications from DNA level (nanometers) up to cell (micrometers), full plant (millimeters to meters), and entire field (kilometers). While quantitative techniques are sensitive to the smallest scales, only qualitative approaches can be used for the larger ones. Emerging technologies from nuclear and medical physics, such as computed tomography, magnetic resonance imaging and positron emission tomography, are expected to bridge the gap of quantitative non-disruptive morphologic and functional measurements at larger scale. In this review we analyze the landscape of the different technologies nowadays available, showing the benefits of each approach in plant stress detection, with a particular focus on the gaps, which will be filled in the nearby future by the emerging nuclear physics approaches to agriculture.

An Integrated Method for Tracking and Monitoring Stomata Dynamics from Microscope Videos

Patchy stomata are a common and characteristic phenomenon in plants. Understanding and studying the regulation mechanism of patchy stomata are of great significance to further supplement and improve the stomatal theory. Currently, the common methods for stomatal behavior observation are based on static images, which makes it difficult to reflect dynamic changes of stomata. With the rapid development of portable microscopes and computer vision algorithms, it brings new chances for stomatal movement observation. In this study, a stomatal behavior observation system (SBOS) was proposed for real-time observation and automatic analysis of each single stoma in wheat leaf using object tracking and semantic segmentation methods. The SBOS includes two modules: the real-time observation module and the automatic analysis module. The real-time observation module can shoot videos of stomatal dynamic changes. In the automatic analysis module, object tracking locates every single stoma accurately to obtain stomatal pictures arranged in time-series; semantic segmentation can precisely quantify the stomatal opening area (SOA), with a mean pixel accuracy (MPA) of 0.8305 and a mean intersection over union (MIoU) of 0.5590 in the testing set. Moreover, we designed a graphical user interface (GUI) so that researchers could use this automatic analysis module smoothly. To verify the performance of the SBOS, the dynamic changes of stomata were observed and analyzed under chilling. Finally, we analyzed the correlation between gas exchange and SOA under drought stress, and the correlation coefficients between mean SOA and net photosynthetic rate (Pn), intercellular CO₂ concentration (Ci), stomatal conductance (Gs), and transpiration rate (Tr) are 0.93, 0.96, 0.96, and 0.97.

Thermal Imaging for Plant Stress Detection and Phenotyping

In the last few years, large efforts have been made to develop new methods to optimize stress detection in crop fields. Thus, plant phenotyping based on imaging techniques has become an essential tool in agriculture. In particular, leaf temperature is a valuable indicator of the physiological status of plants, responding to both biotic and abiotic stressors. Often combined with other imaging sensors and data-mining techniques, thermography is crucial in the implementation of a more automatized, precise and sustainable agriculture. However, thermal data need some corrections related to the environmental and measuring conditions in order to achieve a correct interpretation of the data. This review focuses on the state of the art of thermography applied to the detection of biotic stress. The work will also revise the most important abiotic stress factors affecting the measurements as well as practical issues that need to be considered in order to implement this technique, particularly at the field scale.

The dichotomy of yield and drought resistance: Translation challenges from basic research to crop adaptation to climate change

Global climate change and the increasing human population require crop varieties with higher yield and draught resistance. But meeting both goals is not an easy task for breeders and plant science.

Toward "Smart Canopy" Sorghum: Discovery of the Genetic Control of Leaf Angle Across Layers

A "smart canopy" ideotype has been proposed with leaves being upright at the top and more horizontal toward the bottom of the plant to maximize light interception and conversion efficiencies, and thus increasing yield. The genetic control of leaf angle has, to date, been studied on one or two leaves, or data have been merged from multiple leaves to generate average values. This approach has limited our understanding of the diversity of leaf angles across layers and their genetic control. Genome-wide association studies and quantitative trait loci mapping studies in sorghum (Sorghum bicolor) were performed using layer-specific angle data collected manually and via high-throughput phenotyping strategies. The observed distribution of angles in indoor and field settings is opposite to the ideotype. Several genomic regions were associated with leaf angle within layers or across the canopy. The expression of the brassinosteroid-related transcription factor BZR1/BES1 and the auxin-transporter Dwarf3 were found to be highly correlated with the distribution of angles at different layers. The application of a brassinosteroid biosynthesis inhibitor could not revert the undesirable overall angle distribution. These discoveries demonstrate that the exploitation of layer-specific quantitative trait loci/genes will be instrumental to reversing the natural angle distribution in sorghum according to the "smart canopy" ideotype.

Variation in key leaf photosynthetic traits across wheat wild relatives is accession dependent not species dependent

The wild relatives of modern wheat represent an underutilized source of genetic and phenotypic diversity and are of interest in breeding owing to their wide adaptation to diverse environments. Leaf photosynthetic traits underpin the rate of production of biomass and yield and have not been systematically explored in the wheat relatives. This paper identifies and quantifies the phenotypic variation in photosynthetic, stomatal, and morphological traits in up to 88 wheat wild relative accessions across five genera. Both steady-state measurements and dynamic responses to step changes in light intensity are assessed. A 2.3-fold variation for flag leaf light and CO₂ -saturated rates of photosynthesis A_max was observed. Many accessions showing higher and more variable A_max , maximum rates of carboxylation, electron transport, and Rubisco activity when compared with modern genotypes. Variation in dynamic traits was also significant; with distinct genus-specific trends in rates of induction of nonphotochemical quenching and rate of stomatal opening. We conclude that utilization of wild relatives for improvement of photosynthesis is supported by the existence of a high degree of natural variation in key traits and should consider not only genus-level properties but variation between individual accessions.

A study of light-induced stomatal response in Arabidopsis using thermal imaging

Thermal imaging was used to study the early stage response to light-induced heating of Arabidopsis thaliana leaves. Time-series thermograms provided a spatial and temporal characterization of temperature changes in Arabidopsis wild type and the ost1-2 mutant rosettes exposed to excessive illumination. The initial response to high light, defined by the exponential increase in leaf temperature of ost1-2 gave an increased thermal time constant compared to wild type plants. The inability to regulate stomata in ost1-2 resulted in enhanced stomatal conductance and transpiration rate. Under strong irradiation, a significant decline in the efficiency of photosystem II was observed. This study evaluates infrared thermography kinetics and determines thermal time constants in particular, as an early and rapid method for diagnosing the prime indicators of light stress in plants under excessive light conditions.

Revisiting the physical mutagenesis for sugarcane improvement: a stomatal prospective

This study was conducted to investigate the influence of gamma rays on stomatal parameters and the interaction of these traits with agronomy of the sugarcane crop. Three genotypes of sugarcane (NIA-0819, NIA-98, and BL4) were exposed to four doses of gamma radiation (10, 20, 30, and 40 Gy) and then subjected to field trials. Stomatal length, width, and density were observed using scanning electron microscopy. Moreover, agronomic and sugar-related characteristics of the crop were determined at maturity. The stomatal parameters augmented at two lower doses of gamma radiation (10 and 20 Gy) and declined under higher doses (30 and 40 Gy). The maximum stomatal length was observed in NIA-0819 at 10 Gy (63.71 µm), whereas NIA-98 and BL4 demonstrated highest stomatal length under 20 Gy (54.11 and 57.40 µm, respectively), indicating a role of genetic factors in varietal response. Similar trend was noticed for stomatal width and density as well. The lowermost treatment (10 Gy) of NIA-0819 produced maximum stomatal density (115.31 stomata mm^-2 on the abaxial surface). Adaxial stomatal density was significantly lower than the abaxial one. Sugar quality attributes revealed a different tendency. Sucrose contents of BL4 increased gradually from 12.33% at control to 14.54% at 40 Gy. Yield and yield-contributing traits of genotypes indicated a strong positive correlation with the stomatal parameters. The present study suggested that gamma radiations cause variations in stomatal characteristics of sugarcane. These changes further influence the photosynthetic activity and instigate a direct impact on the agronomic performance of the crop.

Drying times: plant traits to improve crop water use efficiency and yield

Crop water use efficiency (WUE) has come into sharp focus as population growth and climate change place increasing strain on the water used in cropping. Rainfed crops are being challenged by an upward trend in evaporative demand as average temperatures rise and, in many regions, there is an increased irregularity and a downward trend in rainfall. In addition, irrigated cropping faces declining water availability and increased competition from other users. Crop WUE would be improved by, first, ensuring that as much water as possible is actually transpired by the crop rather than being wasted. Deeper roots and greater early crop vigour are two traits that should help achieve this. Crop WUE would also be improved by achieving greater biomass per unit water transpired. A host of traits has been proposed to address this outcome. Restricting crop transpiration through lower stomatal conductance is assessed as having limited utility compared with traits that improve carbon gain, such as enhancements to photosynthetic biochemistry and responsiveness, or greater mesophyll conductance. Ultimately, the most useful outcomes for improved crop WUE will probably be achieved by combining traits to achieve synergistic benefit. The potential utility of trait combinations is supported by the results of crop simulation modelling.

Role of blue and red light in stomatal dynamic behaviour

Plants experience changes in light intensity and quality due to variations in solar angle and shading from clouds and overlapping leaves. Stomatal opening to increasing irradiance is often an order of magnitude slower than photosynthetic responses, which can result in CO2 diffusional limitations on leaf photosynthesis, as well as unnecessary water loss when stomata continue to open after photosynthesis has reached saturation. Stomatal opening to light is driven by two distinct pathways; the 'red' or photosynthetic response that occurs at high fluence rates and saturates with photosynthesis, and is thought to be the main mechanism that coordinates stomatal behaviour with photosynthesis; and the guard cell-specific 'blue' light response that saturates at low fluence rates, and is often considered independent of photosynthesis, and important for early morning stomatal opening. Here we review the literature on these complicated signal transduction pathways and osmoregulatory processes in guard cells that are influenced by the light environment. We discuss the possibility of tuning the sensitivity and magnitude of stomatal response to blue light which potentially represents a novel target to develop ideotypes with the 'ideal' balance between carbon gain, evaporative cooling, and maintenance of hydraulic status that is crucial for maximizing crop performance and productivity.

Thermography methods to assess stomatal behaviour in a dynamic environment

Although thermography allows rapid, non-invasive measurements of large numbers of plants, it has not been used extensively due to the difficulty in deriving biologically relevant information such as leaf transpiration (E) and stomatal conductance (gsw) from thermograms. Methods normalizing leaf temperature using temperatures from reference materials (e.g. with and without evaporative flux) to generate stress indices are generally preferred due to their ease of use to assess plant water status. Here, a simplified method to solve dynamic energy balance equations is presented, which enables the calculation of 'wet' and 'dry' leaf temperatures in order to derive stress indices, whilst providing accurate estimates of E and gsw. Comparing stress indices and gas exchange parameters highlights the limitation of stress indices in a dynamic environment and how this problem can be overcome using artificial leaf references with known conductance. Additionally, applying the equations for each pixel of a thermogram to derive the rapidity of stomatal response over the leaf lamina in wheat revealed the spatial heterogeneity of stomatal behaviour. Rapidity of stomatal movements is an important determinant of water use efficiency, and our results showed 'patchy' responses that were linked to both the spatial and temporal response of gsw.

Natural genetic variation in photosynthesis: an untapped resource to increase crop yield potential?

Raising crop yield potential is a major goal to ensure food security for the growing global population. Photosynthesis is the primary determinant of crop productivity and any gain in photosynthetic CO2 assimilation per unit of leaf area (A) has the potential to increase yield. Significant intraspecific variation in A is known to exist in various autotrophic organs that represent an unexploited target for crop improvement. However, the large number of factors that influence photosynthetic rates often makes it difficult to measure or estimate A under dynamic field conditions (i.e. fluctuating light intensities or temperatures). This complexity often results in photosynthetic capacity, rather than realized photosynthetic rates being used to assess natural variation in photosynthesis. Here we review the work on natural variation in A, the different factors determining A and their interaction in yield formation. A series of drawbacks and perspectives are presented for the most common analyses generally used to estimate A. The different yield components and their determination based on different photosynthetic organs are discussed with a major focus on potential exploitation of various traits for crop improvement. To conclude, an example of different possibilities to increase yield in wheat through enhancing A is illustrated.

All roads lead to growth: imaging-based and biochemical methods to measure plant growth

Plant growth is a highly complex biological process that involves innumerable interconnected biochemical and signalling pathways. Many different techniques have been developed to measure growth, unravel the various processes that contribute to plant growth, and understand how a complex interaction between genotype and environment determines the growth phenotype. Despite this complexity, the term 'growth' is often simplified by researchers; depending on the method used for quantification, growth is viewed as an increase in plant or organ size, a change in cell architecture, or an increase in structural biomass. In this review, we summarise the cellular and molecular mechanisms underlying plant growth, highlight state-of-the-art imaging and non-imaging-based techniques to quantitatively measure growth, including a discussion of their advantages and drawbacks, and suggest a terminology for growth rates depending on the type of technique used.

tealeaves: an R package for modelling leaf temperature using energy budgets

Plants must regulate leaf temperature to optimize photosynthesis, control water loss and prevent damage caused by overheating or freezing. Physical models of leaf energy budgets calculate the energy fluxes and leaf temperatures for a given set leaf and environmental parameters. These models can provide deep insight into the variation in leaf form and function, but there are few computational tools available to use these models. Here I introduce a new R package called tealeaves to make complex leaf energy budget models accessible to a broader array of plant scientists. This package enables novice users to start modelling leaf energy budgets quickly while allowing experts to customize their parameter settings. The code is open source, freely available and readily integrates with other R tools for scientific computing. This paper describes the current functionality of tealeaves, but new features will be added in future releases. This software tool will advance new research on leaf thermal physiology to advance our understanding of basic and applied plant science.

Natural genetic variation of the photosynthetic induction response to fluctuating light environment

Field-grown plants experience fluctuating light intensity for periods extending from seconds to hours because of cloud movements and self-shading. When full light intensity returns after shading, the net CO₂ assimilation rate in leaves does not reach its maximum value immediately, but rises gradually over several minutes to approach a new steady state. This phenomenon has been termed photosynthetic induction, which substantially affects the efficiency of carbon fixation, and thus crop production. The significant natural variation of the speed of induction response exists among not only interspecies but also intraspecies. Recent advances in molecular analysis and high-throughput measurement techniques have revealed the genetic and eco-physiological basis of observed genetic variations in photosynthetic induction response. Here, we review the current understanding of the physiological and genetic mechanisms behind photosynthetic induction, and discusses routes to further advances.

Genotypic, Developmental and Environmental Effects on the Rapidity of gs in Wheat: Impacts on Carbon Gain and Water-Use Efficiency

Stomata are the primary gatekeepers for CO2 uptake for photosynthesis and water loss via transpiration and therefore play a central role in crop performance. Although stomatal conductance (gs ) and assimilation rate (A) are often highly correlated, studies have demonstrated an uncoupling between A and gs that can result in sub-optimal physiological processes in dynamic light environments. Wheat (Triticum aestivum L.) is exposed to changes in irradiance due to leaf self-shading, moving clouds and shifting sun angle to which both A and gs respond. However, stomatal responses are generally an order of magnitude slower than photosynthetic responses, leading to non-synchronized A and gs responses that impact CO2 uptake and water use efficiency ( iWUE). Here we phenotyped a panel of eight wheat cultivars (estimated to capture 80% of the single nucleotide polymorphism variation in North-West European bread wheat) for differences in the speed of stomatal responses (to changes in light intensity) and photosynthetic performance at different stages of development. The impact of water stress and elevated [CO2] on stomatal kinetics was also examined in a selected cultivar. Significant genotypic variation was reported for the time constant for stomatal opening (Ki, P = 0.038) and the time to reach 95% steady state A (P = 0.045). Slow gs opening responses limited A by ∼10% and slow closure reduced iWUE, with these impacts found to be greatest in cultivars Soissons, Alchemy and Xi19. A decrease in stomatal rapidity (and thus an increase in the limitation of photosynthesis) (P < 0.001) was found during the post-anthesis stage compared to the early booting stage. Reduced water availability triggered stomatal closure and asymmetric stomatal opening and closing responses, while elevated atmospheric [CO2] conditions reduced the time for stomatal opening during a low to high light transition, thus suggesting a major environmental effect on dynamic stomatal kinetics. We discuss these findings in terms of exploiting various traits to develop ideotypes for specific environments, and suggest that intraspecific variation in the rapidity of stomatal responses could provide a potential unexploited breeding target to optimize the physiological responses of wheat to dynamic field conditions.