Short- and long-term warming events on photosynthetic physiology, growth, and yields of field grown crops.

Global temperatures are rising from increasing concentrations of greenhouse gases in the atmosphere associated with anthropogenic activities. Global warming includes a warmer shift in mean temperatures as well as increases in the probability of extreme heating events, termed heat waves. Despite the ability of plants to cope with temporal variations in temperature, global warming is increasingly presenting challenges to agroecosystems. The impact of warming on crop species has direct consequences on food security, therefore understanding impacts and opportunities to adapt crops to global warming necessitates experimentation that allows for modification of growth environments to represent global warming scenarios. Published studies addressing crop responses to warming are extensive, however, in-field studies where growth temperature is manipulated to mimic global warming are limited. Here, we provide an overview of in-field heating techniques employed to understand crop responses to warmer growth environments. We then focus on key results associated with season-long warming, as expected with rising global mean temperatures, and with heat waves, as a consequence of increasing temperature variability and rising global mean temperatures. We then discuss the role of rising temperatures on atmospheric water vapor pressure deficit and potential implications for crop photosynthesis and productivity. Finally, we review strategies by which crop photosynthetic processes might be optimized to adapt crops to the increasing temperatures and frequencies of heat waves. Key findings from this review are that higher temperatures consistently reduce photosynthesis and yields of crops even as atmospheric carbon dioxide increases, yet potential strategies to minimize losses from high-temperature exist.

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.

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.

Emerging approaches to measure photosynthesis from the leaf to the ecosystem.

Measuring photosynthesis is critical for quantifying and modeling leaf to regional scale productivity of managed and natural ecosystems. This review explores existing and novel advances in photosynthesis measurements that are certain to provide innovative directions in plant science research. First, we address gas exchange approaches from leaf to ecosystem scales. Leaf level gas exchange is a mature method but recent improvements to the user interface and environmental controls of commercial systems have resulted in faster and higher quality data collection. Canopy chamber and micrometeorological methods have also become more standardized tools and have an advanced understanding of ecosystem functioning under a changing environment and through long time series data coupled with community data sharing. Second, we review proximal and remote sensing approaches to measure photosynthesis, including hyperspectral reflectance- and fluorescence-based techniques. These techniques have long been used with aircraft and orbiting satellites, but lower-cost sensors and improved statistical analyses are allowing these techniques to become applicable at smaller scales to quantify changes in the underlying biochemistry of photosynthesis. Within the past decade measurements of chlorophyll fluorescence from earth-orbiting satellites have measured Solar Induced Fluorescence (SIF) enabling estimates of global ecosystem productivity. Finally, we highlight that stronger interactions of scientists across disciplines will benefit our capacity to accurately estimate productivity at regional and global scales. Applying the multiple techniques outlined in this review at scales from the leaf to the globe are likely to advance understanding of plant functioning from the organelle to the ecosystem.

The inverse relationship between solar-induced fluorescence yield and photosynthetic capacity: benefits for field phenotyping.

Improving photosynthesis is considered a promising way to increase crop yield to feed a growing population. Realizing this goal requires non-destructive techniques to quantify photosynthetic variation among crop cultivars. Despite existing remote sensing-based approaches, it remains a question whether solar-induced fluorescence (SIF) can facilitate screening crop cultivars of improved photosynthetic capacity in plant breeding trials. Here we tested a hypothesis that SIF yield rather than SIF had a better relationship with the maximum electron transport rate (Jmax). Time-synchronized hyperspectral images and irradiance spectra of sunlight under clear-sky conditions were combined to estimate SIF and SIF yield, which were then correlated with ground-truth Vcmax and Jmax. With observations binned over time (i.e. group 1: 6, 7, and 12 July 2017; group 2: 31 July and 18 August 2017; and group 3: 24 and 25 July 2018), SIF yield showed a stronger negative relationship, compared with SIF, with photosynthetic variables. Using SIF yield for Jmax (Vcmax) predictions, the regression analysis exhibited an R2 of 0.62 (0.71) and root mean square error (RMSE) of 11.88 (46.86) µmol m-2 s-1 for group 1, an R2 of 0.85 (0.72) and RMSE of 13.51 (49.32) µmol m-2 s-1 for group 2, and an R2 of 0.92 (0.87) and RMSE of 15.23 (30.29) µmol m-2 s-1 for group 3. The combined use of hyperspectral images and irradiance measurements provides an alternative yet promising approach to characterization of photosynthetic parameters at plot level.

Fast Phenomics in Vineyards: Development of GRover, the Grapevine Rover, and LiDAR for Assessing Grapevine Traits in the Field.

This paper introduces GRover (the grapevine rover), an adaptable mobile platform for the deployment and testing of proximal imaging sensors in vineyards for the non-destructive assessment of trunk and cordon volume and pruning weight. A SICK LMS-400 light detection and ranging (LiDAR) radar mounted on GRover was capable of producing precise (±3 mm) 3D point clouds of vine rows. Vineyard scans of the grapevine variety Shiraz grown under different management systems at two separate locations have demonstrated that GRover is able to successfully reproduce a variety of vine structures. Correlations of pruning weight and vine wood (trunk and cordon) volume with LiDAR scans have resulted in high coefficients of determination (R² = 0.91 for pruning weight; 0.76 for wood volume). This is the first time that a LiDAR of this type has been extensively tested in vineyards. Its high scanning rate, eye safe laser and ability to distinguish tissue types make it an appealing option for further development to offer breeders, and potentially growers, quantified measurements of traits that otherwise would be difficult to determine.

Canopy warming accelerates development in soybean and maize, offsetting the delay in soybean reproductive development by elevated CO2 concentrations.

Increases in atmospheric CO2 concentrations ([CO2 ]) and surface temperature are known to individually have effects on crop development and yield, but their interactive effects have not been adequately investigated under field conditions. We evaluated the impacts of elevated [CO2 ] with and without canopy warming as a function of development in soybean and maize using infrared heating arrays nested within free air CO2 enrichment plots over three growing seasons. Vegetative development accelerated in soybean with temperature plus elevated [CO2 ] resulting in higher node number. Reproductive development was delayed in soybean under elevated [CO2 ], but warming mitigated this delay. In maize, both vegetative and reproductive developments were accelerated by warming, whereas elevated [CO2 ] had no apparent effect on development. Treatment-induced changes in the leaf carbohydrates, dark respiration rate, morphological parameters, and environmental conditions accompanied the changes in plant development. We used two thermal models to investigate their ability to predict the observed development under warming and elevated [CO2 ]. Whereas the growing degree day model underestimated the thermal threshold to reach each developmental stage, the alternative process-based model used (ß function) was able to predict crop development under climate change conditions.

Intensifying drought eliminates the expected benefits of elevated carbon dioxide for soybean.

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.

Canopy warming caused photosynthetic acclimation and reduced seed yield in maize grown at ambient and elevated [CO2 ].

Rising atmospheric CO2 concentration ([CO2 ]) and attendant increases in growing season temperature are expected to be the most important global change factors impacting production agriculture. Although maize is the most highly produced crop worldwide, few studies have evaluated the interactive effects of elevated [CO2 ] and temperature on its photosynthetic physiology, agronomic traits or biomass, and seed yield under open field conditions. This study investigates the effects of rising [CO2 ] and warmer temperature, independently and in combination, on maize grown in the field throughout a full growing season. Free-air CO2 enrichment (FACE) technology was used to target atmospheric [CO2 ] to 200 µmol mol(-1) above ambient [CO2 ] and infrared heaters to target a plant canopy increase of 3.5 °C, with actual season mean heating of ~2.7 °C, mimicking conditions predicted by the second half of this century. Photosynthetic gas-exchange parameters, leaf nitrogen and carbon content, leaf water potential components, and developmental measurements were collected throughout the season, and biomass and yield were measured at the end of the growing season. As predicted for a C4 plant, elevated [CO2 ] did not stimulate photosynthesis, biomass, or yield. Canopy warming caused a large shift in aboveground allocation by stimulating season-long vegetative biomass and decreasing reproductive biomass accumulation at both CO2 concentrations, resulting in decreased harvest index. Warming caused a reduction in photosynthesis due to down-regulation of photosynthetic biochemical parameters and the decrease in the electron transport rate. The reduction in seed yield with warming was driven by reduced photosynthetic capacity and by a shift in aboveground carbon allocation away from reproduction. This field study portends that future warming will reduce yield in maize, and this will not be mitigated by higher atmospheric [CO2 ] unless appropriate adaptation traits can be introduced into future cultivars.

Heat waves imposed during early pod development in soybean (Glycine max) cause significant yield loss despite a rapid recovery from oxidative stress.

Heat waves already have a large impact on crops and are predicted to become more intense and more frequent in the future. In this study, heat waves were imposed on soybean using infrared heating technology in a fully open-air field experiment. Five separate heat waves were applied to field-grown soybean (Glycine max) in central Illinois, three in 2010 and two in 2011. Thirty years of historical weather data from Illinois were analyzed to determine the length and intensity of a regionally realistic heat wave resulting in experimental heat wave treatments during which day and night canopy temperatures were elevated 6 °C above ambient for 3 days. Heat waves were applied during early or late reproductive stages to determine whether and when heat waves had an impact on carbon metabolism and seed yield. By the third day of each heat wave, net photosynthesis (A), specific leaf weight (SLW), and leaf total nonstructural carbohydrate concentration (TNC) were decreased, while leaf oxidative stress was increased. However, A, SLW, TNC, and measures of oxidative stress were no different than the control ca. 12 h after the heat waves ended, indicating rapid physiological recovery from the high-temperature stress. That end of season seed yield was reduced (~10%) only when heat waves were applied during early pod developmental stages indicates the yield loss had more to do with direct impacts of the heat waves on reproductive process than on photosynthesis. Soybean was unable to mitigate yield loss after heat waves given during late reproductive stages. This study shows that short high-temperature stress events that reduce photosynthesis and increase oxidative stress resulted in significant losses to soybean production in the Midwest, U.S. The study also suggests that to mitigate heat wave-induced yield loss, soybean needs improved reproductive and photosynthetic tolerance to high but increasingly common temperatures.

Biochemical acclimation, stomatal limitation and precipitation patterns underlie decreases in photosynthetic stimulation of soybean (Glycine max) at elevated [CO2] and temperatures under fully open air field conditions.

The net effect of elevated [CO2] and temperature on photosynthetic acclimation and plant productivity is poorly resolved. We assessed the effects of canopy warming and fully open air [CO2] enrichment on (1) the acclimation of two biochemical parameters that frequently limit photosynthesis (A), the maximum carboxylation capacity of Rubisco (Vc,max) and the maximum potential linear electron flux through photosystem II (Jmax), (2) the associated responses of leaf structural and chemical properties related to A, as well as (3) the stomatal limitation (l) imposed on A, for soybean over two growing seasons in a conventionally managed agricultural field in Illinois, USA. Acclimation to elevated [CO2] was consistent over two growing seasons with respect to Vc,max and Jmax. However, elevated temperature significantly decreased Jmax contributing to lower photosynthetic stimulation by elevated CO2. Large seasonal differences in precipitation altered soil moisture availability modulating the complex effects of elevated temperature and CO2 on biochemical and structural properties related to A. Elevated temperature also reduced the benefit of elevated [CO2] by eliminating decreases in stomatal limitation at elevated [CO2]. These results highlight the critical importance of considering multiple environmental factors (i.e. temperature, moisture, [CO2]) when trying to predict plant productivity in the context of climate change.

Future carbon dioxide concentration decreases canopy evapotranspiration and soil water depletion by field-grown maize.

Maize, in rotation with soybean, forms the largest continuous ecosystem in temperate North America, therefore changes to the biosphere-atmosphere exchange of water vapor and energy of these crops are likely to have an impact on the Midwestern US climate and hydrological cycle. As a C4 crop, maize photosynthesis is already CO2 -saturated at current CO2 concentrations ([CO2 ]) and the primary response of maize to elevated [CO2 ] is decreased stomatal conductance (gs ). If maize photosynthesis is not stimulated in elevated [CO2 ], then reduced gs is not offset by greater canopy leaf area, which could potentially result in a greater ET reduction relative to that previously reported in soybean, a C3 species. The objective of this study is to quantify the impact of elevated [CO2 ] on canopy energy and water fluxes of maize (Zea mays). Maize was grown under ambient and elevated [CO2 ] (550 µmol mol(-1) during 2004 and 2006 and 585 µmol mol(-1) during 2010) using Free Air Concentration Enrichment (FACE) technology at the SoyFACE facility in Urbana, Illinois. Maize ET was determined using a residual energy balance approach based on measurements of sensible (H) and soil heat fluxes, and net radiation. Relative to control, elevated [CO2 ] decreased maize ET (7-11%; P < 0.01) along with lesser soil moisture depletion, while H increased (25-30 W m(-2) ; P < 0.01) along with higher canopy temperature (0.5-0.6 °C). This reduction in maize ET in elevated [CO2 ] is approximately half that previously reported for soybean. A partitioning analysis showed that transpiration contributed less to total ET for maize compared to soybean, indicating a smaller role of stomata in dictating the ET response to elevated [CO2 ]. Nonetheless, both maize and soybean had significantly decreased ET and increased H, highlighting the critical role of elevated [CO2 ] in altering future hydrology and climate of the region that is extensively cropped with these species.

Minirhizotron imaging reveals that nodulation of field-grown soybean is enhanced by free-air CO2 enrichment only when combined with drought stress.

The rate of N2 fixation by a leguminous plant is a product of the activity of individual nodules and the number of nodules. Initiation of new nodules and N2 fixation per nodule are highly sensitive to environmental conditions. However, the effects of global environmental change on nodulation in the field are largely unknown. It is also unclear whether legumes regulate nodulation in response to environment solely by varying root production or also by varying nodule density per unit of root length. This study utilised minirhizotron imaging as a novel in situ method for assessing the number, size and distribution of nodules in field-grown soybean (Glycine max (L.) Merr.) exposed to elevated atmospheric CO2 ([CO2]) and reduced precipitation. We found that nodule numbers were 134-229% greater in soybeans grown at elevated [CO2] in combination with reduced precipitation, and this response was driven by greater nodule density per unit of root length. The benefits of additional nodules were probably offset by an unfavourable distribution of nodules in shallow, dry soil in reduced precipitation treatment under elevated [CO2] but not ambient [CO2]. In fact, significant decreases in seed and leaf nitrogen concentration also occurred only in elevated [CO2] with reduced precipitation. This study demonstrates the potential of minirhizotron imaging to reveal previously uncharacterised changes in nodule production and distribution in response to global environmental change.