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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.

Proper concentrations of several nutrients, such as iron (Fe), zinc (Zn) and potassium (K) in the soil are needed for plant growth. Thus, farmers sometimes test soils to determine fertiliser application rates. However, measuring soil and plant nutrient concentrations is relatively time-consuming and expensive. Therefore, usually, only a few samples are collected and analysed. This limits the scale of research but also poses some limitations on farming practices, as farmers cannot sample fields at high density in order to customize application rates. Cheap, fast, and high spatial resolution methods to measure soil nutrient concentrations would alleviate some of these limitations. This work aimed to determine the potential of hyperspectral imaging (HI) to predict the concentration of some soil nutrients. Soil samples were scanned by visible and near-infrared imaging systems with a total wavelength range of 450-1700 nm. Fe, Zn, and K were analyzed. Partial least-square regression models (PLSR) were used to correlate the relative reflectance of total Fe, Zn and K in the soil samples. The PLSR models could highly predict Fe concentration (R 0.81, RMSE% 16.6) and performed moderately well for Zn (R 0.30, RMSE% 0.9) and K (R0.47, RMSE% 5.58) concentrations. The overall results indicated that the hyperspectral technique coupled with PLSR could be an accurate and reliable method for determining soil nutrient concentrations.

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.

The central motivation for mechanistic crop growth simulation has remained the same for decades: to reliably predict changes in crop yields and water usage in response to previously unexperienced increases in air temperature and CO2 concentration across different environments, species and genotypes. Over the years, individual process-based model components have become more complex and specialized, increasing their fidelity but posing a challenge for integrating them into powerful multiscale models. Combining models is further complicated by the common strategy of hard-coding intertwined parameter values, equations, solution algorithms and user interfaces, rather than treating these each as separate components. It is clear that a more flexible approach is now required. Here we describe a modular crop growth simulator, BioCro II. At its core, BioCro II is a cross-platform representation of models as sets of equations. This facilitates modularity in model building and allows it to harness modern techniques for numerical integration and data visualization. Several crop models have been implemented using the BioCro II framework, but it is a general purpose tool and can be used to model a wide variety of processes.

Soybean is a major global source of protein and oil. Understanding how soybean crops will respond to the changing climate and identifying the responsible molecular machinery are important for facilitating bioengineering and breeding to meet the growing global food demand. The BioCro family of crop models are semi-mechanistic models scaling from biochemistry to whole crop growth and yield. BioCro was previously parameterized and proved effective for the biomass crops Miscanthus, coppice willow and Brazilian sugarcane. Here, we present Soybean-BioCro, the first food crop to be parameterized for BioCro. Two new module sets were incorporated into the BioCro framework describing the rate of soybean development and carbon partitioning and senescence. The model was parameterized using field measurements collected over the 2002 and 2005 growing seasons at the open air [CO2] enrichment (SoyFACE) facility under ambient atmospheric [CO2]. We demonstrate that Soybean-BioCro successfully predicted how elevated [CO2] impacted field-grown soybean growth without a need for re-parameterization, by predicting soybean growth under elevated atmospheric [CO2] during the 2002 and 2005 growing seasons, and under both ambient and elevated [CO2] for the 2004 and 2006 growing seasons. Soybean-BioCro provides a useful foundational framework for incorporating additional primary and secondary metabolic processes or gene regulatory mechanisms that can further aid our understanding of how future soybean growth will be impacted by climate change.

Circadian rhythms play critical roles in plant physiology, growth, development and survival, and their inclusion in crop growth models is essential for high-fidelity results, especially when considering climate change. Commonly used circadian clock models are often inflexible or result in complex outputs, limiting their use in general simulations. Here we present a new circadian clock model based on mathematical oscillators that easily adapts to different environmental conditions and produces intuitive outputs. We then demonstrate its utility as an input to Glycine max development models. This oscillator clock model has the power to simplify the inclusion of circadian cycles and photoperiodic effects in crop growth models and to unify experimental data from field and controlled environment observations.

Highlight Leaves of two highly productive C4 crops lose photosynthetic efficiency in low light as they become shaded by new leaves forming above, costing the crop up to 10% of potential productivity., The wild progenitors of major C4 crops grew as individuals subjected to little shading. Today they are grown in dense stands where most leaves are shaded. Do they maintain photosynthetic efficiency in these low light conditions produced by modern cultivation? The apparent maximum quantum yield of CO2 assimilation (ΦCO2max,app), a key determinant of light-limited photosynthesis, has not been systematically studied in field stands of C4 crops. ΦCO2max,app was derived from the initial slope of the response of leaf CO2 uptake (A) to photon flux (Q). Leaf fractional light absorptance (α) was measured to determine the absolute maximum quantum yield of CO2 assimilation on an absorbed light basis (ΦCO2max,abs). Light response curves were determined on sun and shade leaves of 49 field plants of Miscanthus × giganteus and Zea mays following canopy closure. ΦCO2max,app and ΦCO2max,abs declined significantly by 15–27% (P

Historical and projected impacts of tropospheric ozone and climate change on California’s most valuable perennial crops indicate that opportunities exist to improve crop yields through pollution mitigation.

High accumulation of heterologous proteins expressed from the plastid genome has sometimes been reported to result in compromised plant phenotypes. Comparisons of transplastomic plants to wild-type (WT) are typically made in environmentally controlled chambers with relatively low light; little is known about the performance of such plants under field conditions. Here, we report on two plastid-engineered tobacco lines expressing the bacterial cellulase Cel6A. Field-grown plants producing Cel6A at ~20% of total soluble protein exhibit no loss in biomass or Rubisco content and only minor reductions in photosynthesis compared to WT. These experiments demonstrate that, when grown in the field, tobacco possesses sufficient metabolic flexibility to accommodate high levels of recombinant protein by increasing total protein synthesis and accumulation and/or by reallocating unneeded endogenous proteins. Based on current tobacco cultivation practices and readily achievable recombinant protein yields, we estimate that specific proteins could be obtained from field-grown transgenic tobacco plants at costs three orders of magnitude less than current cell culture methods.

Significance Although it has long been known that ground-level ozone (O 3 ) damages crops and reduces yield, there has never been an estimate of the total loss attributed to ambient O 3 for field-grown maize and soybean in the United States. Knowing the loss caused by this pollutant would be useful for projecting food supply and setting regulatory standards for pollutant emissions. Here we show that ambient O 3 has reduced maize and soybean yields in rain-fed fields by ∼10% and 5%, respectively, based on historical observations from the past 31 y. Results suggest that air-quality regulations in the United States have been effective in reducing crop production losses to O 3 , and indicate that further reductions in ground-level [O 3 ] would be beneficial in the United States and globally.

Measurements of the response of leaf photosynthesis to CO 2 are vital for understanding the response of our planet to climate change and developing novel strategies for improving food production. The speed of these measurements are often limited by the ability of the leaf gas-exchange analysis instrumentation to reach and maintain a desired set point. This paper develops a biophysical model of a leaf and the measurement instrument that incorporates the plant physiology and the physics of gas flow in the instrument. This model is then parameterized for a commonly-used device for measuring photosynthesis of leaves. A standard feedback controller and a feedback linearization controller are applied to this model to reduce waiting time in these measurements. The model is validated by comparison to real measurement data from the instrument. The controllers are implemented on the actual instrument. The result is control algorithms built from firstorder principles governing the exchange of gas between a leaf and its environment. To the best of our knowledge, this is the first attempt at developing such algorithms for controlling CO 2 in these systems.

Accurate measurements of photosynthesis are vital for understanding the response of our planet to climate change and developing novel strategies for improving food production. Since photosynthesis is sensitive to a myriad of inputs, including temperature, these measurements require precise control to produce meaningful and accurate data. This paper develops a biophysical model of energy balance in a leaf and environmental control system that incorporates plant physiology and the biophysical relationship between a leaf and its environment. This model is then parameterized for a commonly-used device used for measuring leaf photosynthesis. Feedback linearization is applied to this model to design a controller for leaf temperature. The model is validated and the controller is then implemented on actual measurements. The result is a family of more efficient control algorithms built from first-order principles governing the exchange of matter and energy between a leaf and its environment. To the best of our knowledge, this is the first attempt at developing such a control algorithm.

Experimental elevation of [CO2] around C3 crops in the field has been shown to increase yields by suppressing the Rubisco oxygenase reaction and, in turn, photorespiration. Bioengineering a cyanobacterial carbon-concentrating mechanism (CCM) into C3 crop species provides a potential means of elevating [CO2] at Rubisco, thereby decreasing photorespiration and increasing photosynthetic efficiency and yield. The cyanobacterial CCM is an attractive alternative relative to other CCMs, because its features do not require anatomical changes to leaf tissue. However, the potential benefits of engineering the entire CCM into a C3 leaf are unexamined. Here, a CO2 and HCO3 − diffusion-reaction model is developed to examine how components of the cyanobacterial CCM affect leaf light-saturated CO2 uptake (A sat) and to determine whether a different Rubisco isoform would perform better in a leaf with a cyanobacterial CCM. The results show that the addition of carboxysomes without other CCM components substantially decreases A sat and that the best first step is the addition of HCO3 − transporters, as a single HCO3 − transporter increased modeled A sat by 9%. Addition of all major CCM components increased A sat from 24 to 38 µmol m−2 s−1. Several Rubisco isoforms were compared in the model, and increasing ribulose bisphosphate regeneration rate will allow for further improvements by using a Rubisco isoform adapted to high [CO2]. Results from field studies that artificially raise [CO2] suggest that this 60% increase in A sat could result in a 36% to 60% increase in yield.

For the C4 perennial grasses, Miscanthus × giganteus and Panicum virgatum (switchgrass) to be successful for bioenergy production they must maintain high yields over the long term. Previous studies under the less conducive climate for productivity in N.W. Europe found little or no yield decline in M. × giganteus in the long term. This study provides the first analysis of whether yield decline occurs in M. × giganteus under United States. Midwest conditions in side-by-side trials with P. virgatum over 8–10 years at seven locations across Illinois. The effect of stand age was determined by using a linear regression model that included effects of weather. Miscanthus × giganteus produced yields more than twice that of P. virgatum averaging 23.4 ± 1.2 Mg ha−1 yr−1 and 10.0 ± 0.9 Mg ha−1 yr−1, respectively, averaged over 8–10 years. Relationships of yield with precipitation and growing degree days were established and used to estimate yields corrected for the stochastic effects of weather. Across all locations and in both species, yield initially increased until it reached a maximum during the fifth growing season and then declined to a stable, but lower level in the eighth. This pattern was more pronounced in M. × giganteus. The mean yields observed over this longer term period of 8–10 years were lower than the yields of the first 5 years. However, this decline was proportionately greater in M. × giganteus than in P. virgatum, suggesting a stronger effect of stand age on M. × giganteus. Based on the average yield over the period of this study, meeting the United States Renewable Fuel Standard mandate of 60 billion liters of cellulosic ethanol by 2022, would require 6.8 Mha of M. × giganteus or 15.8 Mha of P. virgatum. These appear manageable numbers for the United States, given the 16.0 Mha in the farmland Conservation Reserve Program in addition to another 13.0 Mha abandoned from agriculture in the last decade.

Stimulation of C3 crop yield by rising concentrations of atmospheric carbon dioxide ([CO2]) is widely expected to counteract crop losses that are due to greater drought this century. But these expectations come from sparse field trials that have been biased towards mesic growth conditions. This eight-year study used precipitation manipulation and year-to-year variation in weather conditions at a unique open-air field facility to show that the stimulation of soybean yield by elevated [CO2] diminished to zero as drought intensified. Contrary to the prevalent expectation in the literature, rising [CO2] did not counteract the effect of strong drought on photosynthesis and yield because elevated [CO2] interacted with drought to modify stomatal function and canopy energy balance. This new insight from field experimentation under hot and dry conditions, which will become increasingly prevalent in the coming decades, highlights the likelihood of negative impacts from interacting global change factors on a key global commodity crop in its primary region of production.

Antioxidant metabolism is responsive to environmental conditions, and is proposed to be a key component of ozone (O(3)) tolerance in plants. Tropospheric O(3) concentration ([O(3)]) has doubled since the Industrial Revolution and will increase further if precursor emissions rise as expected over this century. Additionally, atmospheric CO(2) concentration ([CO(2)]) is increasing at an unprecedented rate and will surpass 550 ppm by 2050. This study investigated the molecular, biochemical and physiological changes in soybean exposed to elevated [O(3) ] in a background of ambient [CO(2)] and elevated [CO(2)] in the field. Previously, it has been difficult to demonstrate any link between antioxidant defences and O(3) stress under field conditions. However, this study used principle components analysis to separate variability in [O(3)] from variability in other environmental conditions (temperature, light and relative humidity). Subsequent analysis of covariance determined that soybean antioxidant metabolism increased with increasing [O(3)], in both ambient and elevated [CO(2)]. The transcriptional response was dampened at elevated [CO(2)], consistent with lower stomatal conductance and lower O(3) flux into leaves. Energetically expensive increases in antioxidant metabolism and tetrapyrrole synthesis at elevated [O(3)] were associated with greater transcript levels of enzymes involved in respiratory metabolism.

Accurate estimates of the fertilization effect that elevated carbon dioxide [CO2] has on crop yields are valuable for estimation of future crop production, yet there is still some controversy over these estimates due to possible CO2-by-water-status interactions in chamber studies and the difficulty of conducting field experiments with elevated [CO2]. This study presents a new method to estimate the CO2 fertilization effect (CFE) in dry conditions (CFEdry), based on a combination of historical yield and climatic data and field experiments that do not require elevated [CO2]. It was estimated that approximately 50 years of increasing [CO2] (i.e., a 73 ppm increase) resulted in a 9% and 14% improvement of yield in dry conditions for maize and soybean, respectively, which are similar to estimates derived from free air CO2 enrichment (FACE) studies. The main source of uncertainty in this approach relates to differential effects of technology trends such as new cultivars in wet vs. dry years. Estimates of this technology–water interaction can be refined by further experimentation under ambient [CO2], offering a cost-effective path for improving CFE estimates. The results should prove useful for modeling future yield impacts of climate change, and the approach could be used to derive estimates for other species using relatively simple yield trials.

Early spring leaf out is important to the success of deciduous trees competing for light and space in dense forest plantation canopies. In this study, we investigated spring leaf flush and how long-term growth at elevated carbon dioxide concentration ([CO(2)]) and elevated ozone concentration ([O(3)]) altered leaf area index development in a closed Populus tremuloides (aspen) canopy. This work was done at the Aspen FACE experiment where aspen clones have been grown since 1997 in conditions simulating the [CO(2)] and [O(3)] predicted for approximately 2050. The responses of two clones were compared during the first month of spring leaf out when CO(2) fumigation had begun, but O(3) fumigation had not. Trees in elevated [CO(2)] plots showed a stimulation of leaf area index (36%), while trees in elevated [O(3)] plots had lower leaf area index (-20%). While individual leaf area was not significantly affected by elevated [CO(2)], the photosynthetic operating efficiency of aspen leaves was significantly improved (51%). There were no significant differences in the way that the two aspen clones responded to elevated [CO(2)]; however, the two clones responded differently to long-term growth at elevated [O(3)]. The O(3)-sensitive clone, 42E, had reduced individual leaf area when grown at elevated [O(3)] (-32%), while the tolerant clone, 216, had larger mature leaf area at elevated [O(3)] (46%). These results indicate a clear difference between the two clones in their long-term response to elevated [O(3)], which could affect competition between the clones, and result in altered genotypic composition in future atmospheric conditions.

It is anticipated that enrichment of the atmosphere with CO 2 will increase photosynthetic carbon assimilation in C3 plants. Analysis of controlled environment studies con- ducted to date indicates that plant growth at concentrations of carbon dioxide ((CO 2 )) anticipated for 2050 ( ~ 550 m mol mol - 1 ) will stimulate leaf photosynthetic carbon assimila- tion ( A ) by 20 to 40%. Simultaneously, concentrations of tropospheric ozone ((O 3 )) are expected to increase by 2050, and growth in controlled environments at elevated (O 3 ) significantly reduces A. However, the simultaneous effects of both increases on a major crop under open-air condi- tions have never been tested. Over three consecutive growing seasons > 4700 individual measurements of A , photosynthetic electron transport ( J PSII ) and stomatal con- ductance ( g s ) were measured on Glycine max (L.) Merr. (soybean). Experimental treatments used free-air gas con- centration enrichment (FACE) technology in a fully repli- cated, factorial complete block design. The mean A in the control plots was 14.5 m mol m - 2 s - 1 . At elevated (CO 2 ), mean A was 24% higher and the treatment effect was sta- tistically significant on 80% of days. There was a strong positive correlation between daytime maximum tempera- tures and mean daily integrated A at elevated (CO 2 ), which accounted for much of the variation in CO 2 effect among days. The effect of elevated (CO 2 ) on photosynthesis also tended to be greater under water stress conditions. The elevated (O 3 ) treatment had no statistically significant effect on mean A , g s or J PSII on newly expanded leaves. Combined elevation of (CO 2 ) and (O 3 ) resulted in a slightly smaller increase in average A than when (CO 2 ) alone was elevated, and was significantly greater than the control on 67% of days. Thus, the change in atmospheric composition predicted for the middle of this century will, based on the results of a 3 year open-air field experiment, have smaller effects on photosynthesis, g s and whole chain electron transport through photosystem II than predicted by the substantial literature on relevant controlled environment studies on soybean and likely most other C3 plants.

Plants grown in elevated [CO(2) ] have lower protein and mineral concentrations compared with plants grown in ambient [CO(2) ]. Dilution by enhanced production of carbohydrates is a likely cause, but it cannot explain all of the reductions. Two proposed, but untested, hypotheses are that (1) reduced canopy transpiration reduces mass flow of nutrients to the roots thus reducing nutrient uptake and (2) changes in metabolite or enzyme concentrations caused by physiological changes alter requirements for minerals as protein cofactors or in other organic complexes, shifting allocation between tissues and possibly altering uptake. Here, we use the meta-analysis of previous studies in crops to test these hypotheses. Nutrients acquired mostly by mass flow were decreased significantly more by elevated [CO(2) ] than nutrients acquired by diffusion to the roots through the soil, supporting the first hypothesis. Similarly, Mg showed large concentration declines in leaves and wheat stems, but smaller decreases in other tissues. Because chlorophyll requires a large fraction of total plant Mg, and chlorophyll concentration is reduced by growth in elevated [CO(2) ], this supports the second hypothesis. Understanding these mechanisms may guide efforts to improve nutrient content, and allow modeling of nutrient changes and health impacts under future climate change scenarios.

Antioxidant metabolism is responsive to environmental conditions, and is proposed to be a key component of ozone (O(3)) tolerance in plants. Tropospheric O(3) concentration ([O(3)]) has doubled since the Industrial Revolution and will increase further if precursor emissions rise as expected over this century. Additionally, atmospheric CO(2) concentration ([CO(2)]) is increasing at an unprecedented rate and will surpass 550 ppm by 2050. This study investigated the molecular, biochemical and physiological changes in soybean exposed to elevated [O(3) ] in a background of ambient [CO(2)] and elevated [CO(2)] in the field. Previously, it has been difficult to demonstrate any link between antioxidant defences and O(3) stress under field conditions. However, this study used principle components analysis to separate variability in [O(3)] from variability in other environmental conditions (temperature, light and relative humidity). Subsequent analysis of covariance determined that soybean antioxidant metabolism increased with increasing [O(3)], in both ambient and elevated [CO(2)]. The transcriptional response was dampened at elevated [CO(2)], consistent with lower stomatal conductance and lower O(3) flux into leaves. Energetically expensive increases in antioxidant metabolism and tetrapyrrole synthesis at elevated [O(3)] were associated with greater transcript levels of enzymes involved in respiratory metabolism.

Crops losses to tropospheric ozone (O(3)) in the United States are estimated to cost $1-3 billion annually. This challenge is expected to increase as O(3) concentrations ([O(3)]) rise over the next half century. This study tested the hypothesis that there is cultivar variation in the antioxidant, photosynthetic and yield response of soybean to growth at elevated [O(3)]. Ten cultivars of soybean were grown at elevated [O(3)] from germination through maturity at the Soybean Free Air Concentration Enrichment facility in 2007 and six were grown in 2008. Photosynthetic gas exchange, leaf area index, chlorophyll content, fluorescence and antioxidant capacity were monitored during the growing seasons in order to determine if changes in these parameters could be used to predict the sensitivity of seed yield to elevated [O(3)]. Doubling background [O(3)] decreased soybean yields by 17%, but the variation in response among cultivars and years ranged from 8 to 37%. Chlorophyll content and photosynthetic parameters were positively correlated with seed yield, while antioxidant capacity was negatively correlated with photosynthesis and seed yield, suggesting a trade-off between antioxidant metabolism and carbon gain. Exposure response curves indicate that there has not been a significant improvement in soybean tolerance to [O(3)] in the past 30 years.

Crops losses to tropospheric ozone (O3) in the United States are estimated to cost $1-3 billion annually. This chal- lenge is expected to increase as O3 concentrations ((O3)) rise over the next half century. This study tested the hypoth- esis that there is cultivar variation in the antioxidant, photosynthetic and yield response of soybean to growth at elevated (O3). Ten cultivars of soybean were grown at elevated (O3) from germination through maturity at the Soybean Free Air Concentration Enrichment facility in 2007 and six were grown in 2008. Photosynthetic gas exchange, leaf area index, chlorophyll content, fluorescence and antioxidant capacity were monitored during the growing seasons in order to determine if changes in these parameters could be used to predict the sensitivity of seed yield to elevated (O3). Doubling background (O3) decreased soybean yields by 17%, but the variation in response among cultivars and years ranged from 8 to 37%. Chlorophyll content and photosynthetic parameters were positively correlated with seed yield, while antioxidant capacity was negatively correlated with photosynthesis and seed yield, suggesting a trade-off between antioxidant metabolism and carbon gain. Exposure response curves indicate that there has not been a significant improvement in soybean tolerance to (O3) in the past 30 years.

Previous studies of elevated carbon dioxide concentration ([CO(2)]) on crop canopies have found that radiation-use efficiency is increased more than radiation-interception efficiency. It is assumed that increased radiation-use efficiency is due to changes in leaf-level physiology; however, canopy structure can affect radiation-use efficiency if leaves are displayed in a manner that optimizes their physiological capacity, even though the canopy intercepts the same amount of light. In order to determine the contributions of physiology and canopy structure to radiation-use and radiation-interception efficiency, this study relates leaf-level physiology and leaf display to photosynthetic rate of the outer canopy. We used a new imaging approach that delivers three-dimensional maps of the outer canopy during the growing season. The 3D data were used to model leaf orientation and mean photosynthetic electron transport of the outer canopy to show that leaf orientation changes did not contribute to increased radiation-use; i.e. leaves of the outer canopy showed similar diurnal leaf movements and leaf orientation in both treatments. Elevated [CO(2)] resulted in an increased maximum electron transport rate (ETR(max)) of light reactions of photosynthesis. Modeling of canopy light interception showed that stimulated leaf-level electron transport at elevated [CO(2)], and not alterations in leaf orientation, was associated with stimulated radiation-use efficiency and biomass production in elevated [CO(2)]. This study provides proof of concept of methodology to quantify structure-function relationships in combination, allowing a quantitative estimate of the contribution of both effects to canopy energy conversion under elevated [CO(2)].

Rising atmospheric carbon dioxide concentration ([CO2]) in this century will alter crop yield quantity and quality. It is important to understand the magnitude of the expected changes and the mechanisms involved in crop responses to elevated [CO2] in order to adapt our food systems to the committed change in atmospheric [CO2] and to accurately model future food supply. Free-Air CO2 Enrichment (FACE) allows for crops to be grown in their production environment, under fully open air conditions, at elevated [CO2]. Current best estimates for the response of the staple crops wheat, soybean and rice from FACE experiments are that grain yield will increase by 13% at 550 ppm CO2. For the C4 species, sorghum and maize, grain yield is not expected to increase at elevated [CO2] if water supply is adequate. Grain quality is adversely affected by elevated [CO2]. On average, protein content decreases by 10–14% in non-leguminous grain crops and concentrations of minerals, such as iron and zinc decrease by 15–30%. While these represent our best estimate of changes in crop yield quantity and quality, most studies have been done in temperate regions, and do not account for possible interactions of rising [CO2] with other aspects of climate change, including increased temperature, drought stress and tropospheric ozone concentration.

Photosynthetic and respiratory exchanges of CO 2 by plants with the atmosphere are significantly larger than anthropogenic CO 2 emissions, and these fluxes will change as growing conditions are altered by climate change. Understanding feedbacks in CO 2 exchange is important to predicting future atmospheric [CO 2 ] and climate change. At the tissue and plant scale, respiration is a key determinant of growth and yield. Although the stimulation of C 3 photosynthesis by growth at elevated [CO 2 ] can be predicted with confidence, the nature of changes in respiration is less certain. This is largely because the mechanism of the respiratory response is insufficiently understood. Molecular, biochemical and physiological changes in the carbon metabolism of soybean in a free-air CO 2 enrichment experiment were investigated over 2 growing seasons. Growth of soybean at elevated [CO 2 ] (550 μmol·mol −1 ) under field conditions stimulated the rate of nighttime respiration by 37%. Greater respiratory capacity was driven by greater abundance of transcripts encoding enzymes throughout the respiratory pathway, which would be needed for the greater number of mitochondria that have been observed in the leaves of plants grown at elevated [CO 2 ]. Greater respiratory quotient and leaf carbohydrate content at elevated [CO 2 ] indicate that stimulated respiration was supported by the additional carbohydrate available from enhanced photosynthesis at elevated [CO 2 ]. If this response is consistent across many species, the future stimulation of net primary productivity could be reduced significantly. Greater foliar respiration at elevated [CO 2 ] will reduce plant carbon balance, but could facilitate greater yields through enhanced photoassimilate export to sink tissues.

Although crop yield generally responds positively to increased atmospheric CO2 concentration ([CO2]), the response depends on the species and environmental conditions. Thus, even though global [CO2] is increasing roughly uniformly, regional yield response to increased [CO2] will vary due to differences in climate and the mixture of crops. Although [CO2] effects have been shown to be important for economic and food security impacts of climate change, regional [CO2] effects are not often considered, and the few studies that have considered them disagree on regional patterns. Here regional yield effects of elevated [CO2] are examined by combining experimentally determined CO2 fertilization effect estimates with grid-level data on climate, crop areas, and yields. Production stimulation varies between regions, mostly driven by differences in climate but also by the mixture of crops. The variability in yield due to the variable response to elevated [CO2] is about 50–70% of the variability in yield due to the variable response to climate. There is, however, little agreement between studies regarding which regions benefit most from elevated [CO2]. This is likely because of interactions of CO2 with temperature, species, water status, and nitrogen availability, but no models currently account for all these interactions. These results suggest that regional differences in CO2 effects are of similar importance as regional differences in climate effects and should be included in models.