European soybean to benefit people and the environment.

Europe imports large amounts of soybean that are predominantly used for livestock feed, mainly sourced from Brazil, USA and Argentina. In addition, the demand for GM-free soybean for human consumption is project to increase. Soybean has higher protein quality and digestibility than other legumes, along with high concentrations of isoflavones, phytosterols and minerals that enhance the nutritional value as a human food ingredient. Here, we examine the potential to increase soybean production across Europe for livestock feed and direct human consumption, and review possible effects on the environment and human health. Simulations and field data indicate rainfed soybean yields of 3.1 ± 1.2 t ha-1 from southern UK through to southern Europe (compared to a 3.5 t ha-1 average from North America). Drought-prone southern regions and cooler northern regions require breeding to incorporate stress-tolerance traits. Literature synthesized in this work evidenced soybean properties important to human nutrition, health, and traits related to food processing compared to alternative protein sources. While acknowledging the uncertainties inherent in any modelling exercise, our findings suggest that further integrating soybean into European agriculture could reduce GHG emissions by 37-291 Mt CO2e year-1 and fertiliser N use by 0.6-1.2 Mt year-1, concurrently improving human health and nutrition.

Stomatal conductance reduction tradeoffs in maize leaves: A theoretical study.

As the leading global grain crop, maize significantly impacts agricultural water usage. Presently, photosynthesis ( A net ${A}_{\text{net}}$ ) in leaves of modern maize crops is saturated with CO 2 ${\text{CO}}_{2}$ , implying that reducing stomatal conductance ( g s ${g}_{{\rm{s}}}$ ) would not affect A net ${A}_{\text{net}}$ but reduce transpiration ( τ $\tau $ ), thereby increasing water use efficiency (WUE). While g s ${g}_{{\rm{s}}}$ reduction benefits upper canopy leaves under optimal conditions, the tradeoffs in low light and nitrogen-deficient leaves under nonoptimal microenvironments remain unexplored. Moreover, g s ${g}_{{\rm{s}}}$ reduction increases leaf temperature ( T leaf ${T}_{\text{leaf}}$ ) and water vapor pressure deficit, partially counteracting transpiratory water savings. Therefore, the overall impact of g s ${g}_{{\rm{s}}}$ reduction on water savings remains unclear. Here, we use a process-based leaf model to investigate the benefits of reduced g s ${g}_{{\rm{s}}}$ in maize leaves under different microenvironments. Our findings show that increases in T leaf ${T}_{\text{leaf}}$ due to g s ${g}_{{\rm{s}}}$ reduction can diminish WUE gains by up to 20%. However, g s ${g}_{{\rm{s}}}$ reduction still results in beneficial WUE tradeoffs, where a 29% decrease in g s ${g}_{{\rm{s}}}$ in upper canopy leaves results in a 28% WUE gain without loss in A net ${A}_{\text{net}}$ . Lower canopy leaves exhibit superior tradeoffs in g s ${g}_{{\rm{s}}}$ reduction with 178% gains in WUE without loss in A net ${A}_{\text{net}}$ . Our simulations show that these WUE benefits are resilient to climate change.

Impact of genotype-calling methodologies on genome-wide association and genomic prediction in polyploids.

Discovery and analysis of genetic variants underlying agriculturally important traits are key to molecular breeding of crops. Reduced representation approaches have provided cost-efficient genotyping using next-generation sequencing. However, accurate genotype calling from next-generation sequencing data is challenging, particularly in polyploid species due to their genome complexity. Recently developed Bayesian statistical methods implemented in available software packages, polyRAD, EBG, and updog, incorporate error rates and population parameters to accurately estimate allelic dosage across any ploidy. We used empirical and simulated data to evaluate the three Bayesian algorithms and demonstrated their impact on the power of genome-wide association study (GWAS) analysis and the accuracy of genomic prediction. We further incorporated uncertainty in allelic dosage estimation by testing continuous genotype calls and comparing their performance to discrete genotypes in GWAS and genomic prediction. We tested the genotype-calling methods using data from two autotetraploid species, Miscanthus sacchariflorus and Vaccinium corymbosum, and performed GWAS and genomic prediction. In the empirical study, the tested Bayesian genotype-calling algorithms differed in their downstream effects on GWAS and genomic prediction, with some showing advantages over others. Through subsequent simulation studies, we observed that at low read depth, polyRAD was advantageous in its effect on GWAS power and limit of false positives. Additionally, we found that continuous genotypes increased the accuracy of genomic prediction, by reducing genotyping error, particularly at low sequencing depth. Our results indicate that by using the Bayesian algorithm implemented in polyRAD and continuous genotypes, we can accurately and cost-efficiently implement GWAS and genomic prediction in polyploid crops.

A genome-scale metabolic reconstruction of soybean and Bradyrhizobium diazoefficiens reveals the cost-benefit of nitrogen fixation.

Nitrogen-fixing symbioses allow legumes to thrive in nitrogen-poor soils at the cost of diverting some photoassimilate to their microsymbionts. Effort is being made to bioengineer nitrogen fixation into nonleguminous crops. This requires a quantitative understanding of its energetic costs and the links between metabolic variations and symbiotic efficiency. A whole-plant metabolic model for soybean (Glycine max) with its associated microsymbiont Bradyrhizobium diazoefficiens was developed and applied to predict the cost-benefit of nitrogen fixation with varying soil nitrogen availability. The model predicted a nitrogen-fixation cost of c. 4.13 g C g-1 N, which when implemented into a crop scale model, translated to a grain yield reduction of 27% compared with a non-nodulating plant receiving its nitrogen from the soil. Considering the lower nitrogen content of cereals, the yield cost to a hypothetical N-fixing cereal is predicted to be less than half that of soybean. Soybean growth was predicted to be c. 5% greater when the nodule nitrogen export products were amides versus ureides. This is the first metabolic reconstruction in a tropical crop species that simulates the entire plant and nodule metabolism. Going forward, this model will serve as a tool to investigate carbon use efficiency and key mechanisms within N-fixing symbiosis in a tropical species forming determinate nodules.

Rethinking the potential productivity of crassulacean acid metabolism by integrating metabolic dynamics with shoot architecture, using the example of Agave tequilana.

Terrestrial CAM plants typically occur in hot semiarid regions, yet can show high crop productivity under favorable conditions. To achieve a more mechanistic understanding of CAM plant productivity, a biochemical model of diel metabolism was developed and integrated with 3-D shoot morphology to predict the energetics of light interception and photosynthetic carbon assimilation. Using Agave tequilana as an example, this biochemical model faithfully simulated the four diel phases of CO2 and metabolite dynamics during the CAM rhythm. After capturing the 3-D form over an 8-yr production cycle, a ray-tracing method allowed the prediction of the light microclimate across all photosynthetic surfaces. Integration with the biochemical model thereby enabled the simulation of plant and stand carbon uptake over daily and annual courses. The theoretical maximum energy conversion efficiency of Agave spp. is calculated at 0.045-0.049, up to 7% higher than for C3 photosynthesis. Actual light interception, and biochemical and anatomical limitations, reduced this to 0.0069, or 15.6 Mg ha-1 yr-1 dry mass annualized over an 8-yr cropping cycle, consistent with observation. This is comparable to the productivity of many C3 crops, demonstrating the potential of CAM plants in climates where little else may be grown while indicating strategies that could raise their productivity.

Is chloroplast size optimal for photosynthetic efficiency?

Improving photosynthetic efficiency has recently emerged as a promising way to increase crop production in a sustainable manner. While chloroplast size may affect photosynthetic efficiency in several ways, we aimed to explore whether chloroplast size manipulation can be a viable approach to improving photosynthetic performance. Several tobacco (Nicotiana tabacum) lines with contrasting chloroplast sizes were generated via manipulation of chloroplast division genes to assess photosynthetic performance under steady-state and fluctuating light. A selection of lines was included in a field trial to explore productivity. Lines with enlarged chloroplasts underperformed in most of the measured traits. Lines with smaller and more numerous chloroplasts showed a similar efficiency compared with wild-type (WT) tobacco. Chloroplast size only weakly affected light absorptance and light profiles within the leaf. Increasing chloroplast size decreased mesophyll conductance (gm ) but decreased chloroplast size did not increase gm . Increasing chloroplast size reduced chloroplast movements and enhanced non-photochemical quenching. The chloroplast smaller than WT appeared to be no better than WT for photosynthetic efficiency and productivity under field conditions. The results indicate that chloroplast size manipulations are therefore unlikely to lead to higher photosynthetic efficiency or growth.

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.

To have value, comparisons of high-throughput phenotyping methods need statistical tests of bias and variance.

The gap between genomics and phenomics is narrowing. The rate at which it is narrowing, however, is being slowed by improper statistical comparison of methods. Quantification using Pearson's correlation coefficient (r) is commonly used to assess method quality, but it is an often misleading statistic for this purpose as it is unable to provide information about the relative quality of two methods. Using r can both erroneously discount methods that are inherently more precise and validate methods that are less accurate. These errors occur because of logical flaws inherent in the use of r when comparing methods, not as a problem of limited sample size or the unavoidable possibility of a type I error. A popular alternative to using r is to measure the limits of agreement (LOA). However both r and LOA fail to identify which instrument is more or less variable than the other and can lead to incorrect conclusions about method quality. An alternative approach, comparing variances of methods, requires repeated measurements of the same subject, but avoids incorrect conclusions. Variance comparison is arguably the most important component of method validation and, thus, when repeated measurements are possible, variance comparison provides considerable value to these studies. Statistical tests to compare variances presented here are well established, easy to interpret and ubiquitously available. The widespread use of r has potentially led to numerous incorrect conclusions about method quality, hampering development, and the approach described here would be useful to advance high throughput phenotyping methods but can also extend into any branch of science. The adoption of the statistical techniques outlined in this paper will help speed the adoption of new high throughput phenotyping techniques by indicating when one should reject a new method, outright replace an old method or conditionally use a new method.

Increased bundle-sheath leakiness of CO2 during photosynthetic induction shows a lack of coordination between the C4 and C3 cycles.

Use of a complete dynamic model of NADP-malic enzyme C4 photosynthesis indicated that, during transitions from dark or shade to high light, induction of the C4 pathway was more rapid than that of C3 , resulting in a predicted transient increase in bundle-sheath CO2 leakiness (ϕ). Previously, ϕ has been measured at steady state; here we developed a new method, coupling a tunable diode laser absorption spectroscope with a gas-exchange system to track ϕ in sorghum and maize through the nonsteady-state condition of photosynthetic induction. In both species, ϕ showed a transient increase to > 0.35 before declining to a steady state of 0.2 by 1500 s after illumination. Average ϕ was 60% higher than at steady state over the first 600 s of induction and 30% higher over the first 1500 s. The transient increase in ϕ, which was consistent with model prediction, indicated that capacity to assimilate CO2 into the C3 cycle in the bundle sheath failed to keep pace with the rate of dicarboxylate delivery by the C4 cycle. Because nonsteady-state light conditions are the norm in field canopies, the results suggest that ϕ in these major crops in the field is significantly higher and energy conversion efficiency lower than previous measured values under steady-state conditions.

Soybean photosynthesis and crop yield are improved by accelerating recovery from photoprotection.

Crop leaves in full sunlight dissipate damaging excess absorbed light energy as heat. This protective dissipation continues after the leaf transitions to shade, reducing crop photosynthesis. A bioengineered acceleration of this adjustment increased photosynthetic efficiency and biomass in tobacco in the field. But could that also translate to increased yield in a food crop? Here we bioengineered the same change into soybean. In replicated field trials, photosynthetic efficiency in fluctuating light was higher and seed yield in five independent transformation events increased by up to 33%. Despite increased seed quantity, seed protein and oil content were unaltered. This validates increasing photosynthetic efficiency as a much needed strategy toward sustainably increasing crop yield in support of future global food security.

Drought imprints on crops can reduce yield loss: Nature's insights for food security.

The Midwestern "Corn-Belt" in the United States is the most productive agricultural region on the planet despite being predominantly rainfed. In this region, global climate change is driving precipitation patterns toward wetter springs and drier mid- to late-summers, a trend that is likely to intensify in the future. The lack of precipitation can lead to crop water limitations that ultimately impact growth and yields. Young plants exposed to water stress will often invest more resources into their root systems, possibly priming the crop for any subsequent mid- or late-season drought. The trend toward wetter springs, however, suggests that opportunities for crop priming may lessen in the future. Here, we test the hypothesis that early season dry conditions lead to drought priming in field-grown crops and this response will protect crops against growth and yield losses from late-season droughts. This hypothesis was tested for the two major Midwestern crop, maize and soybean, using high-resolution daily weather data, satellite-derived phenological metrics, field yield data, and ecosystem-scale model (Agricultural Production System Simulator) simulations. The results from this study showed that priming mitigated yield losses from a late season drought of up to 4.0% and 7.0% for maize and soybean compared with unprimed crops experiencing a late season drought. These results suggest that if the trend toward wet springs with drier summers continues, the relative impact of droughts on crop productivity is likely to worsen. Alternatively, identifying opportunities to breed or genetically modify pre-primed crop species may provide improved resilience to future climate change.

Field-grown ictB tobacco transformants show no difference in photosynthetic efficiency for biomass relative to the wild type.

In this study, four tobacco transformants overexpressing the inorganic carbon transporter B gene (ictB) were screened for photosynthetic performance relative to the wild type (WT) in field-based conditions. The WT and transgenic tobacco plants were evaluated for photosynthetic performance to determine the maximum rate of carboxylation (Vc, max), maximum rate of electron transport (Jmax), the photosynthetic compensation point (Γ*), quantum yield of PSII (ΦPSII), and mesophyll conductance (gm). Additionally, all plants were harvested to compare differences in above-ground biomass. Overall, transformants did not perform better than the WT on photosynthesis-, biomass-, and leaf composition-related traits. This is in contrast to previous studies that have suggested significant increases in photosynthesis and yield with the overexpression of ictB, although not widely evaluated under field conditions. These findings suggest that the benefit of ictB is not universal and may only be seen under certain growth conditions. While there is certainly still potential benefit to utilizing ictB in the future, further effort must be concentrated on understanding the underlying function of the gene and in which environmental conditions it offers the greatest benefit to crop performance. As it stands at present, it is possible that ictB overexpression may be largely favorable in controlled environments, such as greenhouses.

Into the Shadows and Back into Sunlight: Photosynthesis in Fluctuating Light.

Photosynthesis is an important remaining opportunity for further improvement in the genetic yield potential of our major crops. Measurement, analysis, and improvement of leaf CO2 assimilation (A) have focused largely on photosynthetic rates under light-saturated steady-state conditions. However, in modern crop canopies of several leaf layers, light is rarely constant, and the majority of leaves experience marked light fluctuations throughout the day. It takes several minutes for photosynthesis to regain efficiency in both sun-shade and shade-sun transitions, costing a calculated 10-40% of potential crop CO2 assimilation. Transgenic manipulations to accelerate the adjustment in sun-shade transitions have already shown a substantial productivity increase in field trials. Here, we explore means to further accelerate these adjustments and minimize these losses through transgenic manipulation, gene editing, and exploitation of natural variation. Measurement andanalysis of photosynthesis in sun-shade and shade-sun transitions are explained. Factors limiting speeds of adjustment and how they could be modified to effect improved efficiency are reviewed, specifically nonphotochemical quenching (NPQ), Rubisco activation, and stomatal responses.

Guard-cell-targeted overexpression of Arabidopsis Hexokinase 1 can improve water use efficiency in field-grown tobacco plants.

Water deficit currently acts as one of the largest limiting factors for agricultural productivity worldwide. Additionally, limitation by water scarcity is projected to continue in the future with the further onset of effects of global climate change. As a result, it is critical to develop or breed for crops that have increased water use efficiency and that are more capable of coping with water scarce conditions. However, increased intrinsic water use efficiency (iWUE) typically brings a trade-off with CO2 assimilation as all gas exchange is mediated by stomata, through which CO2 enters the leaf while water vapor exits. Previously, promising results were shown using guard-cell-targeted overexpression of hexokinase to increase iWUE without incurring a penalty in photosynthetic rates or biomass production. Here, two homozygous transgenic tobacco (Nicotiana tabacum) lines expressing Arabidopsis Hexokinase 1 (AtHXK1) constitutively (35SHXK2 and 35SHXK5) and a line that had guard-cell-targeted overexpression of AtHXK1 (GCHXK2) were evaluated relative to wild type for traits related to photosynthesis and yield. In this study, iWUE was significantly higher in GCHXK2 compared with wild type without negatively impacting CO2 assimilation, although results were dependent upon leaf age and proximity of precipitation event to gas exchange measurement.

Faster than expected Rubisco deactivation in shade reduces cowpea photosynthetic potential in variable light conditions.

Cowpea is the major source of vegetable protein for rural populations in sub-Saharan Africa and average yields are not keeping pace with population growth. Each day, crop leaves experience many shade events and the speed of photosynthetic adjustment to this dynamic environment strongly affects daily carbon gain. Rubisco activity is particularly important because it depends on the speed and extent of deactivation in shade and recovers slowly on return to sun. Here, direct biochemical measurements showed a much faster rate of Rubisco deactivation in cowpea than prior estimates inferred from dynamics of leaf gas exchange in other species1-3. Shade-induced deactivation was driven by decarbamylation, and half-times for both deactivation in shade and activation in saturating light were shorter than estimates from gas exchange (≤53% and 79%, respectively). Incorporating these half-times into a model of diurnal canopy photosynthesis predicted a 21% diurnal loss of productivity and suggests slowing Rubisco deactivation during shade is an unexploited opportunity for improving crop productivity.

A hybrid kinetic and constraint-based model of leaf metabolism allows predictions of metabolic fluxes in different environments.

While flux balance analysis (FBA) provides a framework for predicting steady-state leaf metabolic network fluxes, it does not readily capture the response to environmental variables without being coupled to other modelling formulations. To address this, we coupled an FBA model of 903 reactions of soybean (Glycine max) leaf metabolism with e-photosynthesis, a dynamic model that captures the kinetics of 126 reactions of photosynthesis and associated chloroplast carbon metabolism. Successful coupling was achieved in an iterative formulation in which fluxes from e-photosynthesis were used to constrain the FBA model and then, in turn, fluxes computed from the FBA model used to update parameters in e-photosynthesis. This process was repeated until common fluxes in the two models converged. Coupling did not hamper the ability of the kinetic module to accurately predict the carbon assimilation rate, photosystem II electron flux, and starch accumulation of field-grown soybean at two CO2 concentrations. The coupled model also allowed accurate predictions of additional parameters such as nocturnal respiration, as well as analysis of the effect of light intensity and elevated CO2 on leaf metabolism. Predictions included an unexpected decrease in the rate of export of sucrose from the leaf at high light, due to altered starch-sucrose partitioning, and altered daytime flux modes in the tricarboxylic acid cycle at elevated CO2 . Mitochondrial fluxes were notably different between growing and mature leaves, with greater anaplerotic, tricarboxylic acid cycle and mitochondrial ATP synthase fluxes predicted in the former, primarily to provide carbon skeletons and energy for protein synthesis.

Dynamics of photosynthetic induction and relaxation within the canopy of rice and two wild relatives.

Wild rice species are a source of genetic material for improving cultivated rice (Oryza sativa) and a means to understand its evolutionary history. Renewed interest in non-steady-state photosynthesis in crops has taken place due its potential in improving sustainable productivity. Variation was characterized for photosynthetic induction and relaxation at two leaf canopy levels in three rice species. The wild rice accessions had 16%-40% higher rates of leaf CO2 uptake (A) during photosynthetic induction relative to the O. sativa accession. However, O. sativa had an overall higher photosynthetic capacity when compared to accessions of its wild progenitors. Additionally, O. sativa had a faster stomatal closing response, resulting in higher intrinsic water-use efficiency during high-to-low light transitions. Leaf position in the canopy had a significant effect on non-steady-state photosynthesis, but not steady-state photosynthesis. The results show potential to utilize wild material to refine plant models and improve non-steady-state photosynthesis in cultivated rice for increased productivity.

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.