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

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

Solar-induced chlorophyll fluorescence captures the effects of elevated ozone on canopy structure and acceleration of senescence in soybean.

Solar-induced chlorophyll fluorescence (SIF) provides an opportunity to rapidly and non-destructively investigate how plants respond to stress. Here, we explored the potential of SIF to detect the effects of elevated O3 on soybean in the field where soybean was subjected to ambient and elevated O3 throughout the growing season in 2021. Exposure to elevated O3 resulted in a significant decrease in canopy SIF at 760 nm (SIF760), with a larger decrease in the late growing season (36%) compared with the middle growing season (13%). Elevated O3 significantly decreased the fraction of absorbed photosynthetically active radiation by 8-15% in the middle growing season and by 35% in the late growing stage. SIF760 escape ratio (fesc) was significantly increased under elevated O3 by 5-12% in the late growth stage due to a decrease of leaf chlorophyll content and leaf area index. Fluorescence yield of the canopy was reduced by 5-11% in the late growing season depending on the fesc estimation method, during which leaf maximum carboxylation rate and maximum electron transport were significantly reduced by 29% and 20% under elevated O3. These results demonstrated that SIF could capture the elevated O3 effect on canopy structure and acceleration of senescence in soybean and provide empirical support for using SIF for soybean stress detection and phenotyping.

Similar photosynthetic but different yield responses of C3 and C4 crops to elevated O3.

The deleterious effects of ozone (O3) pollution on crop physiology, yield, and productivity are widely acknowledged. It has also been assumed that C4 crops with a carbon concentrating mechanism and greater water use efficiency are less sensitive to O3 pollution than C3 crops. This assumption has not been widely tested. Therefore, we compiled 46 journal articles and unpublished datasets that reported leaf photosynthetic and biochemical traits, plant biomass, and yield in five C3 crops (chickpea, rice, snap bean, soybean, and wheat) and four C4 crops (sorghum, maize, Miscanthus × giganteus, and switchgrass) grown under ambient and elevated O3 concentration ([O3]) in the field at free-air O3 concentration enrichment (O3-FACE) facilities over the past 20 y. When normalized by O3 exposure, C3 and C4 crops showed a similar response of leaf photosynthesis, but the reduction in chlorophyll content, fluorescence, and yield was greater in C3 crops compared with C4 crops. Additionally, inbred and hybrid lines of rice and maize showed different sensitivities to O3 exposure. This study quantitatively demonstrates that C4 crops respond less to elevated [O3] than C3 crops. This understanding could help maintain cropland productivity in an increasingly polluted atmosphere.

Manipulating atmospheric CO2 concentration induces shifts in wheat leaf and spike microbiomes and in Fusarium pathogen communities.

Changing atmospheric composition represents a source of uncertainty in our assessment of future disease risks, particularly in the context of mycotoxin producing fungal pathogens which are predicted to be more problematic with climate change. To address this uncertainty, we profiled microbiomes associated with wheat plants grown under ambient vs. elevated atmospheric carbon dioxide concentration [CO2] in a field setting over 2 years. We also compared the dynamics of naturally infecting versus artificially introduced Fusarium spp. We found that the well-known temporal dynamics of plant-associated microbiomes were affected by [CO2]. The abundances of many amplicon sequence variants significantly differed in response to [CO2], often in an interactive manner with date of sample collection or with tissue type. In addition, we found evidence that two strains within Fusarium - an important group of mycotoxin producing fungal pathogens of plants - responded to changes in [CO2]. The two sequence variants mapped to different phylogenetic subgroups within the genus Fusarium, and had differential [CO2] responses. This work informs our understanding of how plant-associated microbiomes and pathogens may respond to changing atmospheric compositions.

Two decades of fumigation data from the Soybean Free Air Concentration Enrichment facility.

The Soybean Free Air Concentration Enrichment (SoyFACE) facility is the longest running open-air carbon dioxide and ozone enrichment facility in the world. For over two decades, soybean, maize, and other crops have been exposed to the elevated carbon dioxide and ozone concentrations anticipated for late this century. The facility, located in East Central Illinois, USA, exposes crops to different atmospheric concentrations in replicated octagonal ~280 m2 Free Air Concentration Enrichment (FACE) treatment plots. Each FACE plot is paired with an untreated control (ambient) plot. The experiment provides important ground truth data for predicting future crop productivity. Fumigation data from SoyFACE were collected every four seconds throughout each growing season for over two decades. Here, we organize, quality control, and collate 20 years of data to facilitate trend analysis and crop modeling efforts. This paper provides the rationale for and a description of the SoyFACE experiments, along with a summary of the fumigation data and collation process, weather and ambient data collection procedures, and explanations of air pollution metrics and calculations.

Reductions in leaf area index, pod production, seed size, and harvest index drive yield loss to high temperatures in soybean.

Improvements in genetics, technology, and agricultural intensification have increased soybean yields; however, adverse climate conditions may prevent these gains from being fully realized in the future. Higher growing season temperatures reduce soybean yields in key production regions including the US Midwest, and better understanding of the developmental and physiological mechanisms that constrain soybean yield under high temperature conditions is needed. This study tested the response of two soybean cultivars to four elevated temperature treatments (+1.7, +2.6, +3.6, and +4.8 °C) in the field over three growing seasons and identified threshold temperatures for response and linear versus non-linear trait responses to temperature. Yield declined non-linearly to temperature, with decreases apparent when canopy temperature exceeded 20.9 °C for the locally adapted cultivar and 22.7°C for a cultivar adapted to more southern locations. While stem node number increased with increasing temperature, leaf area index decreased substantially. Pod production, seed size, and harvest index significantly decreased with increasing temperature. The seasonal average temperature of even the mildest treatment exceeded the threshold temperatures for yield loss, emphasizing the importance of improving temperature tolerance in soybean germplasm with intensifying climate change.

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.

Anatomical determinants of gas exchange and hydraulics vary with leaf shape in soybean.

BACKGROUND AND AIMS: Leaf shape in crops can impact light distribution and carbon capture at the whole plant and canopy level. Given similar leaf inclination, narrow leaves can allow a greater fraction of incident light to pass through to lower canopy leaves by reducing leaf area index, which can potentially increase canopy-scale photosynthesis. Soybean has natural variation in leaf shape which can be utilized to optimize canopy architecture. However, the anatomical and physiological differences underlying variation in leaf shape remain largely unexplored. METHODS: In this study, we selected 28 diverse soybean lines with leaf length to width ratios (leaf ratio) ranging between 1.1 and 3.2. We made leaf cross-sectional, gas exchange, vein density and hydraulic measurements and studied their interrelationships among these lines. KEY RESULTS: Our study shows that narrow leaves tend to be thicker, with an ~30 µm increase in leaf thickness for every unit increase in leaf ratio. Interestingly, thicker leaves had a greater proportion of spongy mesophyll while the proportions of palisade and paraveinal mesophyll decreased. In addition, narrow and thicker leaves had greater photosynthesis and stomatal conductance per unit area along with greater leaf hydraulic conductance. CONCLUSIONS: Our results suggest that selecting for narrow leaves can improve photosynthetic performance and potentially provide a yield advantage in soybean.

The leaf economics spectrum of triploid and tetraploid C4 grass Miscanthus x giganteus.

The leaf economics spectrum (LES) describes multivariate correlations in leaf structural, physiological and chemical traits, originally based on diverse C3 species grown under natural ecosystems. However, the specific contribution of C4 species to the global LES is studied less widely. C4 species have a CO2 concentrating mechanism which drives high rates of photosynthesis and improves resource use efficiency, thus potentially pushing them towards the edge of the LES. Here, we measured foliage morphology, structure, photosynthesis, and nutrient content for hundreds of genotypes of the C4 grass Miscanthus× giganteus grown in two common gardens over two seasons. We show substantial trait variations across M.× giganteus genotypes and robust genotypic trait relationships. Compared to the global LES, M.× giganteus genotypes had higher photosynthetic rates, lower stomatal conductance, and less nitrogen content, indicating greater water and photosynthetic nitrogen use efficiency in the C4 species. Additionally, tetraploid genotypes produced thicker leaves with greater leaf mass per area and lower leaf density than triploid genotypes. By expanding the LES relationships across C3 species to include C4 crops, these findings highlight that M.× giganteus occupies the boundary of the global LES and suggest the potential for ploidy to alter LES traits.

Physiological trait networks enhance understanding of crop growth and water use in contrasting environments.

Plant function arises from a complex network of structural and physiological traits. Explicit representation of these traits, as well as their connections with other biophysical processes, is required to advance our understanding of plant-soil-climate interactions. We used the Terrestrial Regional Ecosystem Exchange Simulator (TREES) to evaluate physiological trait networks in maize. Net primary productivity (NPP) and grain yield were simulated across five contrasting climate scenarios. Simulations achieving high NPP and grain yield in high precipitation environments featured trait networks conferring high water use strategies: deep roots, high stomatal conductance at low water potential ("risky" stomatal regulation), high xylem hydraulic conductivity and high maximal leaf area index. In contrast, high NPP and grain yield was achieved in dry environments with low late-season precipitation via water conserving trait networks: deep roots, high embolism resistance and low stomatal conductance at low leaf water potential ("conservative" stomatal regulation). We suggest that our approach, which allows for the simultaneous evaluation of physiological traits, soil characteristics and their interactions (i.e., networks), has potential to improve our understanding of crop performance in different environments. In contrast, evaluating single traits in isolation of other coordinated traits does not appear to be an effective strategy for predicting plant performance.

Variation in leaf transcriptome responses to elevated ozone corresponds with physiological sensitivity to ozone across maize inbred lines.

We examine the impact of sustained elevated ozone concentration on the leaf transcriptome of 5 diverse maize inbred genotypes, which vary in physiological sensitivity to ozone (B73, Mo17, Hp301, C123, and NC338), using long reads to assemble transcripts and short reads to quantify expression of these transcripts. More than 99% of the long reads, 99% of the assembled transcripts, and 97% of the short reads map to both B73 and Mo17 reference genomes. Approximately 95% of the genes with assembled transcripts belong to known B73-Mo17 syntenic loci and 94% of genes with assembled transcripts are present in all temperate lines in the nested association mapping pan-genome. While there is limited evidence for alternative splicing in response to ozone stress, there is a difference in the magnitude of differential expression among the 5 genotypes. The transcriptional response to sustained ozone stress in the ozone resistant B73 genotype (151 genes) was modest, while more than 3,300 genes were significantly differentially expressed in the more sensitive NC338 genotype. There is the potential for tandem duplication in 30% of genes with assembled transcripts, but there is no obvious association between potential tandem duplication and differential expression. Genes with a common response across the 5 genotypes (83 genes) were associated with photosynthesis, in particular photosystem I. The functional annotation of genes not differentially expressed in B73 but responsive in the other 4 genotypes (789) identifies reactive oxygen species. This suggests that B73 has a different response to long-term ozone exposure than the other 4 genotypes. The relative magnitude of the genotypic response to ozone, and the enrichment analyses are consistent regardless of whether aligning short reads to: long read assembled transcripts; the B73 reference; the Mo17 reference. We find that prolonged ozone exposure directly impacts the photosynthetic machinery of the leaf.

High-throughput characterization, correlation, and mapping of leaf photosynthetic and functional traits in the soybean (Glycine max) nested association mapping population.

Photosynthesis is a key target to improve crop production in many species including soybean [Glycine max (L.) Merr.]. A challenge is that phenotyping photosynthetic traits by traditional approaches is slow and destructive. There is proof-of-concept for leaf hyperspectral reflectance as a rapid method to model photosynthetic traits. However, the crucial step of demonstrating that hyperspectral approaches can be used to advance understanding of the genetic architecture of photosynthetic traits is untested. To address this challenge, we used full-range (500-2,400 nm) leaf reflectance spectroscopy to build partial least squares regression models to estimate leaf traits, including the rate-limiting processes of photosynthesis, maximum Rubisco carboxylation rate, and maximum electron transport. In total, 11 models were produced from a diverse population of soybean sampled over multiple field seasons to estimate photosynthetic parameters, chlorophyll content, leaf carbon and leaf nitrogen percentage, and specific leaf area (with R2 from 0.56 to 0.96 and root mean square error approximately <10% of the range of calibration data). We explore the utility of these models by applying them to the soybean nested association mapping population, which showed variability in photosynthetic and leaf traits. Genetic mapping provided insights into the underlying genetic architecture of photosynthetic traits and potential improvement in soybean. Notably, the maximum Rubisco carboxylation rate mapped to a region of chromosome 19 containing genes encoding multiple small subunits of Rubisco. We also mapped the maximum electron transport rate to a region of chromosome 10 containing a fructose 1,6-bisphosphatase gene, encoding an important enzyme in the regeneration of ribulose 1,5-bisphosphate and the sucrose biosynthetic pathway. The estimated rate-limiting steps of photosynthesis were low or negatively correlated with yield suggesting that these traits are not influenced by the same genetic mechanisms and are not limiting yield in the soybean NAM population. Leaf carbon percentage, leaf nitrogen percentage, and specific leaf area showed strong correlations with yield and may be of interest in breeding programs as a proxy for yield. This work is among the first to use hyperspectral reflectance to model and map the genetic architecture of the rate-limiting steps of photosynthesis.

Advances in field-based high-throughput photosynthetic phenotyping.

Gas exchange techniques revolutionized plant research and advanced understanding, including associated fluxes and efficiencies, of photosynthesis, photorespiration, and respiration of plants from cellular to ecosystem scales. These techniques remain the gold standard for inferring photosynthetic rates and underlying physiology/biochemistry, although their utility for high-throughput phenotyping (HTP) of photosynthesis is limited both by the number of gas exchange systems available and the number of personnel available to operate the equipment. Remote sensing techniques have long been used to assess ecosystem productivity at coarse spatial and temporal resolutions, and advances in sensor technology coupled with advanced statistical techniques are expanding remote sensing tools to finer spatial scales and increasing the number and complexity of phenotypes that can be extracted. In this review, we outline the photosynthetic phenotypes of interest to the plant science community and describe the advances in high-throughput techniques to characterize photosynthesis at spatial scales useful to infer treatment or genotypic variation in field-based experiments or breeding trials. We will accomplish this objective by presenting six lessons learned thus far through the development and application of proximal/remote sensing-based measurements and the accompanying statistical analyses. We will conclude by outlining what we perceive as the current limitations, bottlenecks, and opportunities facing HTP of photosynthesis.

Testing unified theories for ozone response in C4 species.

There is tremendous interspecific variability in O3  sensitivity among C3  species, but variation among C4  species has been less clearly documented. It is also unclear whether stomatal conductance and leaf structure such as leaf mass per area (LMA) determine the variation in sensitivity to O3 across species. In this study, we investigated leaf morphological, chemical, and photosynthetic responses of 22 genotypes of four C4 bioenergy species (switchgrass, sorghum, maize, and miscanthus) to elevated O3 in side-by-side field experiments using free-air O3 concentration enrichment (FACE). The C4  species varied largely in leaf morphology, physiology, and nutrient composition. Elevated O3 did not alter leaf morphology, nutrient content, stomatal conductance, chlorophyll fluorescence, and respiration in most genotypes but reduced net CO2 assimilation in maize and photosynthetic capacity in sorghum and maize. Species with lower LMA and higher stomatal conductance tended to show greater losses in photosynthetic rate and capacity in elevated O3 compared with species with higher LMA and lower stomatal conductance. Stomatal conductance was the strongest determinant of leaf photosynthetic rate and capacity. The response of both area- and mass-based leaf photosynthetic rate and capacity to elevated O3 were not affected by LMA directly but negatively influenced by LMA indirectly through stomatal conductance. These results demonstrate that there is significant variation in O3  sensitivity among C4  species with maize and sorghum showing greater sensitivity of photosynthesis to O3 than switchgrass and miscanthus. Interspecific variation in O3  sensitivity was determined by direct effects of stomatal conductance and indirect effects of LMA. This is the first study to provide a test of unifying theories explaining variation in O3  sensitivity in C4 bioenergy grasses. These findings advance understanding of O3 tolerance in C4  grasses and could aid in optimal placement of diverse C4 bioenergy feedstock across a polluted landscape.

Predicting biochemical acclimation of leaf photosynthesis in soybean under in-field canopy warming using hyperspectral reflectance.

Traditional gas exchange measurements are cumbersome, which makes it difficult to capture variation in biochemical parameters, namely the maximum rate of carboxylation measured at a reference temperature (Vcmax25 ) and the maximum electron transport at a reference temperature (Jmax25 ), in response to growth temperature over time from days to weeks. Hyperspectral reflectance provides reliable measures of Vcmax25 and Jmax25 ; however, the capability of this method to capture biochemical acclimations of the two parameters to high growth temperature over time has not been demonstrated. In this study, Vcmax25 and Jmax25 were measured over multiple growth stages during two growing seasons for field-grown soybeans using both gas exchange techniques and leaf spectral reflectance under ambient and four elevated canopy temperature treatments (ambient+1.5, +3, +4.5, and +6°C). Spectral vegetation indices and machine learning methods were used to build predictive models for Vcmax25 and Jmax25 , based on the leaf reflectance. Results showed that these models yielded an R2 of 0.57-0.65 and 0.48-0.58 for Vcmax25 and Jmax25 , respectively. Hyperspectral reflectance captured biochemical acclimation of leaf photosynthesis to high temperature in the field, improving spatial and temporal resolution in the ability to assess the impact of future warming on crop productivity.

Approaches to investigate crop responses to ozone pollution: from O3 -FACE to satellite-enabled modeling.

Ozone (O3 ) is a damaging air pollutant to crops. As one of the most reactive oxidants known, O3 rapidly forms other reactive oxygen species (ROS) once it enters leaves through stomata. Those ROS in turn can cause oxidative stress, reduce photosynthesis, accelerate senescence, and decrease crop yield. To improve and adapt our feed, fuel, and food supply to rising O3 pollution, a number of Free Air Concentration Enrichment (O3 -FACE) facilities have been developed around the world and have studied key staple crops. In this review, we provide an overview of the FACE facilities and highlight some of the lessons learned from the last two decades of research. We discuss the differences between C3 and C4 crop responses to elevated O3 , the possible trade-off between productivity and protection, genetic variation in O3 response within and across species, and how we might leverage this observed variation for crop improvement. We also highlight the need to improve understanding of the interaction between rising O3 pollution and other aspects of climate change, notably drought. Finally, we propose the use of globally modeled O3 data that are available at increasing spatial and temporal resolutions to expand upon the research conducted at the limited number of global O3 -FACE facilities.

Historical Trends in Sweet Corn Plant Density Tolerance Using Era Hybrids (1930-2010s).

Over the last six decades, steady improvement in plant density tolerance (PDT) has been one of the largest contributors to genetic yield gain in field corn. While recent research indicates that PDT in modern sweet corn hybrids could be exploited to improve yield, historical changes in PDT in sweet corn are unknown. The objectives of this study were to: (a) quantify the extent to which PDT has changed since introduction of hybrid sweet corn and (b) determine the extent to which changes over time in PDT are associated with plant morpho-physiological and ear traits. An era panel was assembled by recreating 15 sugary1 sweet corn hybrids that were widely used at one time in the United States, representing hybrids since the 1930s. Era hybrids were evaluated in field experiments in a randomized complete block design with a split-plot arrangement of treatments, including hybrid as the main factor and density as the split-plot factor. Plant density treatments included "Low" plant density (9,900 plants/ha) free of crowding stress or "High" plant density (79,000 plants/ha) with crowding stress. On average, per-area marketable ear mass (Mt/ha) increased at a rate of 0.8 Mt/ha/decade at High densities, whereas per-plant yield (i.e., kg/plant) remained unchanged over time regardless of the density level. Crate yield, a fresh market metric, improved for modern hybrids. However, processing sweet corn yield metrics like fresh kernel mass and recovery (amount of kernel mass contributing to the fresh ear mass) showed modest or no improvement over time, respectively. Modern sweet corn hybrids tend to have fewer tillers and lower fresh shoot biomass, potentially allowing the use of higher plant density; however, plant architecture alone does not accurately predict PDT of individual hybrids.

Plant biochemistry influences tropospheric ozone formation, destruction, deposition, and response.

Tropospheric ozone (O3) is among the most damaging air pollutant to plants. Plants alter the atmospheric O3 concentration in two distinct ways: (i) by the emission of volatile organic compounds (VOCs) that are precursors of O3; and (ii) by dry deposition, which includes diffusion of O3 into vegetation through stomata and destruction by nonstomatal pathways. Isoprene, monoterpenes, and higher terpenoids are emitted by plants in quantities that alter tropospheric O3. Deposition of O3 into vegetation is related to stomatal conductance, leaf structural traits, and the detoxification capacity of the apoplast. The biochemical fate of O3 once it enters leaves and reacts with aqueous surfaces is largely unknown, but new techniques for the tracking and identification of initial products have the potential to open the black box.

Elevated carbon dioxide reduces a common soybean leaf endophyte.

Free-air CO2 enrichment (FACE) experiments have elucidated how climate change affects plant physiology and production. However, we lack a predictive understanding of how climate change alters interactions between plants and endophytes, critical microbial mediators of plant physiology and ecology. We leveraged the SoyFACE facility to examine how elevated [CO2 ] affected soybean (Glycine max) leaf endophyte communities in the field. Endophyte community composition changed under elevated [CO2 ], including a decrease in the abundance of a common endophyte, Methylobacterium sp. Moreover, Methylobacterium abundance was negatively correlated with co-occurring fungal endophytes. We then assessed how Methylobacterium affected the growth of co-occurring endophytic fungi in vitro. Methylobacterium antagonized most co-occurring fungal endophytes in vitro, particularly when it was more established in culture before fungal introduction. Variation in fungal response to Methylobacterium within a single fungal operational taxonomic unit (OTU) was comparable to inter-OTU variation. Finally, fungi isolated from elevated vs. ambient [CO2 ] plots differed in colony growth and response to Methylobacterium, suggesting that increasing [CO2 ] may affect fungal traits and interactions within the microbiome. By combining in situ and in vitro studies, we show that elevated [CO2 ] decreases the abundance of a common bacterial endophyte that interacts strongly with co-occurring fungal endophytes. We suggest that endophyte responses to global climate change will have important but largely unexplored implications for both agricultural and natural systems.

Quantifying high-temperature stress on soybean canopy photosynthesis: The unique role of sun-induced chlorophyll fluorescence.

High temperature and accompanying high vapor pressure deficit often stress plants without causing distinctive changes in plant canopy structure and consequential spectral signatures. Sun-induced chlorophyll fluorescence (SIF), because of its mechanistic link with photosynthesis, may better detect such stress than remote sensing techniques relying on spectral reflectance signatures of canopy structural changes. However, our understanding about physiological mechanisms of SIF and its unique potential for physiological stress detection remains less clear. In this study, we measured SIF at a high-temperature experiment, Temperature Free-Air Controlled Enhancement, to explore the potential of SIF for physiological investigations. The experiment provided a gradient of soybean canopy temperature with 1.5, 3.0, 4.5, and 6.0°C above the ambient canopy temperature in the open field environments. SIF yield, which is normalized by incident radiation and the fraction of absorbed photosynthetically active radiation, showed a high correlation with photosynthetic light use efficiency (r = 0.89) and captured dynamic plant responses to high-temperature conditions. SIF yield was affected by canopy structural and plant physiological changes associated with high-temperature stress (partial correlation r = 0.60 and -0.23). Near-infrared reflectance of vegetation, only affected by canopy structural changes, was used to minimize the canopy structural impact on SIF yield and to retrieve physiological SIF yield (ΦF ) signals. ΦF further excludes the canopy structural impact than SIF yield and indicates plant physiological variability, and we found that ΦF outperformed SIF yield in responding to physiological stress (r = -0.37). Our findings highlight that ΦF sensitively responded to the physiological downregulation of soybean gross primary productivity under high temperature. ΦF , if reliably derived from satellite SIF, can support monitoring regional crop growth and different ecosystems' vegetation productivity under environmental stress and climate change.