Location: Global Change and Photosynthesis Research
2023 Annual Report
Objectives
Objective 1: Improve photosynthetic efficiency along with water/nitrogen use efficiency in crops for greater food production and bioenergy crop yields.
1.1 Decrease leaf chlorophyll content to maximize water and nitrogen use efficiency without reduction in the daily integral of canopy carbon.
1.2 Lower energetic costs of photorespiration by installing improved engineered chloroplast photorespiratory bypass pathways.
1.3 Stack best performing reduced chlorophyll and photorespiratory traits to combine efficiencies.
1.4 Determine the heritability of photosynthetic traits in maize, and map QTL for photosynthetic traits and their response to abiotic stress.
Objective 2: Identify key regulatory factors controlling carbon and nitrogen assimilation and partitioning in crop plants for improving seed composition and yields.
2.1 Determine the impact of canopy microenvironment on soybean seed composition as affected by canopy position.
2.2 Optimize Rubisco activase (Rca) regulation for dynamic light and temperature environments.
Objective 3: Identify new genetic loci for enhancing crop resilience to environmental extremes (higher temperature and increased drought) by determining the major loci and physiological mechanisms that modulate crop performance in response to elevated atmospheric CO2 and tropospheric ozone (GxE).
3.1 Test the response of diverse soybean cultivars to elevated [CO2] and advance genetic populations for mapping CO2 response in soybean.
3.2 Use functional genomic and metabolomic approaches to dissect the mechanistic basis for O3 response in maize.
3.3 Investigate the interactive effects of elevated [O3] and drought stress or high temperature stress on crops.
Objective 4: Advance the optimization of central ecosystem services for current and alternative food and bioenergy production systems for carbon, water, nutrient cycling, and energy partitioning, by determining the linkages among genetic, physiological, whole-plant, and ecosystem processes (GxE).
4.1 Quantify direct and indirect ecosystem services for traditional and alternative agroecosystem including but extending beyond harvestable yield.
4.2 Dissociate the impacts of rising temperature and increasing vapor pressure deficit on key ecosystem processes and crop yield.
4.3 Develop techniques for high-throughput phenotyping of leaf and canopy physiological properties to better associate genotype to phenotype.
4.4 Incorporate improved physiological understanding of crop responses to global change and stress conditions into mechanistic crop production models.
Approach
The overall goal of this project is to identify factors affecting food and bioenergy crop production, with an emphasis on photosynthetic performance and intensifying environmental stress. Overall, the experimental approaches combine biophysics, biochemistry, physiology, molecular biology, genetics and genomics. The research will include both laboratory- and field-based studies. Specific approaches for each objective are:
Objective 1 – utilize systems biology and transgenic approaches to decrease canopy chlorophyll and reduce flux through photorespiration, as well as to identify genetic variation in photosynthetic traits.
Objective 2 – assess the impact of canopy microenvironment on soybean seed composition and engineer Rubisco activase to improve function in dynamic light and temperature environments.
Objective 3 – identify genetic loci and the mechanistic basis for enhancing crop responses to global climate change by using free air concentration enrichment and functional genomic and metabolic approaches.
Objective 4 – optimize food and bioenergy production systems by high-throughput phenotyping and modeling. Mechanistic crop production models will be developed to improve understanding of carbon, water and nutrient cycling responses to environmental changes.
Progress Report
This is the final report for project 5012-21000-030-000D which terminated in June 2023 and resulted in 127 peer- reviewed publications. See the report for the replacement project, 5012-21000-032-000D, “Enhancing Photosynthesis for Agricultural Resiliency and Sustainability” for new research directions and progress.
In support of Objective 1, research aimed to improve photosynthetic efficiency in crops by altering chlorophyll content in the canopy, inserting alternative metabolic pathways to limit photorespiration, and determining the heritability of photosynthetic traits and their response to abiotic stress. After two SYs retired midway through the project period, a new SY was hired, and research shifted to improve nitrogen use efficiency by identifying and manipulating transcriptional regulators that integrate nitrogen availability with photosynthesis. Substantial progress was made towards improving photosynthetic efficiency, including successful construction of a metabolic pathway in transgenic tobacco that efficiently bypassed photorespiration and resulted in 40% more productive plants. This approach was patented and is currently being tested in food and forestry crop species. The heritability of photosynthesis and photosynthetic response to ozone was determined in a half diallel maize population grown at ambient and elevated ozone concentrations at the Soybean Free Air Concentration Enrichment facility. Research discovered that photosynthetic response to ozone pollution was a good predictor of seed yield response to ozone pollution, the heritability of photosynthesis was greater in elevated ozone pollution, and hybrids created from parents Hp301 and NC338 showed greater sensitivity to ozone stress. Progress towards improving nitrogen use efficiency was made by growing Arabidopsis at varying nitrogen and light conditions and characterized gene expression and physiological traits, including photosynthesis, nitrogen content, and biomass. We used gene regulatory network modeling and gene expression-to-trait machine learning to identify transcription factors that are important for physiological outcomes. Mutant lines were then used to characterize how disruption of four of the transcription factors predicted to be most influential affected traits under varying nitrogen and light conditions.
These regulators provide targets for researchers and breeders interested in optimizing nitrogen-photosynthesis interactions to improve nitrogen use efficiency.
In support of Objective 2, research identified key regulatory factors controlling carbon and nitrogen assimilation and partitioning. Studies focused on Rubisco activase, the enzyme that facilitates the release of sugar-phosphate inhibitors from the active sites of Rubisco and plays a central role in initiating and sustaining Rubisco activity under varying environmental conditions. Research discovered a novel regulatory role of Arabidopsis Rubisco activase phosphorylation at threonine-78. Conservative substitution of serine for threonine-78 resulted in impaired functionality of Rubisco activase. Further research used RNAi to reduce Rubisco activase alpha to below detectable levels. Rubisco activase alpha is the form of activase that is redox regulated, and the RNAi experiments showed no significant effect of knocking down the enzyme on photosynthesis or growth. This suggests that Rubisco activase alpha is not involved in regulation of Rubisco activase oligomer activity in soybean, unlike other species.
In support of Objective 3, we grew historical soybean cultivars and a population of soybean recombinant inbred lines at ambient and elevated carbon dioxide concentrations in the field at the Soybean Free Air Concentration Enrichment facility, which allows crops to be grown under future atmospheric conditions in the field under fully open air conditions. Atmospheric carbon dioxide continues to climb by two to three parts per million (ppm) per year, driving climate change and providing an opportunity to adapt crops to atmospheric change. A soybean recombinant inbred population of 200 lines was grown in 2022 and planted again in May 2023. The lines are grown in replicated plots (n=4) at ambient and elevated (600 parts per million) carbon dioxide concentration.
Development, growth, leaf area index, photosynthesis, biomass production, yield and seed quality were measured. Leaf reflectance was measured to estimate photosynthetic capacity, specific leaf area and leaf nitrogen content using partial least squares regression models. Elevated carbon dioxide decreased photosynthetic capacity and leaf nitrogen content along with canopy transpiration. Canopy transpiration was estimated with a rapid new approach linking leaf porometer measurements at different canopy layers with estimates of leaf area index. The population has been genotyped with ~6000 core single nucleotide polymorphisms identified, and we are currently identifying quantitative trait loci associated with soybean response to elevated carbon dioxide concentrations. In addition to identifying soybean lines that could be useful breeding material for adaptation to elevated carbon dioxide, this research is also developing high throughput techniques that can be widely used in the field.
In support of Objective 3, we used experimental approaches and long-term datasets to investigate the interactive effects of drought stress and ozone pollution on agriculture. We established a field experiment at the Soybean Free Air Concentration Enrichment facility with rain exclusion awnings set up inside ambient and elevated ozone plots. For three growing seasons, we studied the interactive effects of ozone and reduced rainfall on soybean growth and productivity, and found that elevated ozone consistently reduced yields, but the interaction with reduced soil moisture varied with season. We further used 10-year satellite vegetation index observations, satellite reanalysis data of soil moisture, vapor pressure deficit, and air temperature from 2012-2021, along with ground- level ozone measurements across the Northern Hemisphere to test the relationship between plant productivity and drought under different ozone concentrations. We found that high ozone concentrations significantly exacerbated the sensitivity of plants to vapor pressure deficit for most plant functional types and across different climate zones at both daily and monthly scales, indicating a role for indirect ozone damage. On average, the negative partial correlation coefficient between vapor pressure deficit and plant productivity decreased by 3% for every 10 ppb increase in ozone according to daily-scale observations. These results may be attributed to reduced stomatal regulation under high ozone concentrations. In contrast, the correlations between temperature and plant productivity were not affected by ozone concentrations. This study highlights that tropospheric ozone is important in considering plant response to droughts and heatwaves under climate change.
In support of Objective 4, several new phenotyping techniques were developed, including a plot-level screening tool for quantification of photosynthetic parameters and pigment content in crops using hyperspectral reflectance from sunlit leaf pixels. This tool provides an advancement from leaf-level photosynthetic and phenotyping efforts and can rapidly assess many photosynthetic traits and pigment content of a crop canopy. Advances in identifying the most cost effective and computationally efficient methods to integrate proximal remote sensing techniques for photosynthetic phenotyping were also published. In addition to hyperspectral reflectance, Light Detection and Ranging (LIDAR) approaches for measuring canopy height, 3-dimensional structure and leaf angle have been established. Further research developed an open- air humidifying system consisting of a high-pressure air compressor coupled with horizontal pipes each outfitted with misting nozzles was assembled and replicated in the field along with infrared heating arrays. The combination of misting nozzles with compressed air allowed the misted vapor to mix with the atmosphere and increase the humidity within the plots. Infrared heaters increased canopy temperature above soybean plots and together the system enabled testing of high temperature with and without vapor pressure deficit stress. In 2022, soybeans were grown from canopy closure to maturity with elevated temperature and altered vapor pressure deficit. A third year of the experiment is underway in 2023. The effects of rising temperatures and altered vapor pressure deficit are difficult to disentangle using historical datasets, and this experiment provides critical data for understanding these individual components of global climate change on agricultural productivity.
Accomplishments
1. Increased sensitivity of plants to atmospheric drought under high tropospheric ozone concentrations. Ozone is a damaging air pollutant that often accompanies heat waves and droughts. All three stresses impact plant productivity, however, whether plant responses to drought and heat vary at different ozone concentrations has not been studied at the regional scale. ARS researchers in Urbana, Illinois, investigated interactions between ozone, drought, temperature, and plant productivity across the Northern Hemisphere using a combination of remotely sensed and ground-level monitoring data. For most North American vegetation types and climate zones, high ozone concentrations increased plant susceptibility to atmospheric drought. Plants showed greater vulnerability to low humidity under high ozone concentrations, but not greater vulnerability to high temperature stress. As background ozone concentrations continue to increase across the globe, understanding their impacts on productivity is important for modeling ecosystem carbon and water balance. This study reveals the critical role that ozone can play in altering plant responses to low humidity. This identifies a new factor, ozone, that needs to be considered more directly in global models of plant productivity.
2. Growing corn and soybeans together increase plasticity of resource use, but do not improve yields. Growing corn and soybeans together in the same field in the Midwest could potentially have ecosystem service benefits over large-scale single crop systems that may underutilize resource capture on a land-area basis. ARS researchers in Urbana, Illinois, investigated competition for light, between maize and soybean grown in an intercropping system, along with the impact of corn plant density on yield. The study found that intercropped corn favored physiological plasticity, while intercropped soybean invested in both physiological and architectural plasticity. However, a high corn plant density did not improve yields in either monoculture or intercrop systems. Our research revealed a decrease in land-use efficiency of 9%-19% in the intercrop system, thus providing crucial insight into strategies for future crop cultivar improvements in intercrop designs. These findings provide significant implications for improving crop productivity in the Midwest. Farmers, agronomists, and policy-makers can use these insights to redesign cultivation strategies, optimizing intercrop systems for increased light-use efficiency and yield.
3. Improved statistical analyses for comparing new methods. Developing new tools to quickly measure crop traits is a key focus of plant phenotyping. Pearson’s correlation coefficient is typically used to compare methods, but this statistic is incapable of determining whether a new method is a suitable replacement for an existing one. A better statistical analysis compares bias and variances of the two methods. ARS researchers in Urbana, Illinois, have developed hyperspectral methods to measure photosynthetic capacity in seconds rather than the 15 to 20 minutes required by infrared gas exchange analysis, and compared the two methods using the two different analyses. Results showed that using Pearson’s coefficient can lead to incorrect conclusions, incorrectly rejecting a new, more precise method. Researchers comparing methods would find this statistical analysis an improvement over their current analyses, and it will help the field overall to produce better instruments and methods.
Review Publications
Pelech, E.A., Evers, J.B., Pederson, T.L., Drag, D.W., Fu, P., Bernacchi, C.J. 2023. Leaf, plant, to canopy: A mechanistic study on aboveground plasticity and plant density within a maize–soybean intercrop system for the Midwest, USA. Plant Cell and Environment. 46(2):405-421. https://doi.org/10.1111/pce.14487.
Shanks, C.M., Huang, J., Cheng, C., Shih, H., Brooks, M.D., Alvarez, J.M., Araus, V., Swift, J., Henry, A., Coruzzi, G.M. 2022. Validation of a high-confidence regulatory network for gene-to-NUE phenotype in field-grown rice. Frontiers in Plant Science. https://doi.org/10.3389/fpls.2022.1006044.
Gardner, A., Jiang, M., Ellsworth, D., Mackenzie, A., Pritchard, J., Bader, M., Barton, C., Bernacchi, C.J., Calfapietra, C., Crous, K., et al. 2022. Optimal stomatal theory predicts CO2 responses of stomatal conductance in both gymnosperm and angiosperm trees. New Phytologist. 237(4):1229-1241. https://doi.org/10.1111/nph.18618.
Wang, Y., Stutz, S., Bernacchi, C.J., Boyd, R., Ort, D.R., Long, S. 2022. Increased bundle-sheath leakiness of CO2 during photosynthetic induction shows a lack of co-ordination between the C4 and C3 cycles. New Phytologist. 236(5):1661-1675. https://doi.org/10.1111/nph.18485.
Song, D., De Silva, K., Brooks, M.D., Kamruzzaman, M. 2023. Biomass prediction based on hyperspectral images of the Arabidopsis canopy. Computers and Electronics in Agriculture. 210: Article 107939. https://doi.org/10.1016/j.compag.2023.107939.
Wu, G., Guan, K., Jiang, C., Kimm, H., Miao, G., Yang, X., Bernacchi, C.J., Sun, X., Suyker, A.E., Moore, C.E. 2023. Can upscaling ground nadir SIF to eddy covariance footprint improve the relationship between SIF and GPP in croplands. Agricultural and Forest Meteorology. 338. Article 109532. https://doi.org/10.1016/j.agrformet.2023.109532.
Sinha, E., Calvin, K., Bond-Lamberty, B., Drewniak, B., Ricciuto, D., Sargsyan, K., Cheng, Y., Bernacchi, C.J., Moore, C. 2023. Modeling perennial bioenergy crops in the E3SM land model (ELMv2). Journal of Advances in Modeling Earth Systems. 15(1). Article e2022MS003171. https://doi.org/10.1029/2022MS003171.
Sinha, E., Bond-Lamberty, B., Calvin, K., Drewniak, B., Bisht, G., Bernacchi, C.J., Blakely, B., Moore, C. 2023. The impact of crop rotation and spatially varying crop parameters in the E3SM Land Model (ELMv2). Journal of Geophysical Research-Biogeosciences. 128(3). Article e2022JG007187. https://doi.org/10.1029/2022JG007187.
Eckardt, N.A., Ainsworth, E.A., Bahuguna, R.N., Broadley, M.R., Busch, W., Carpita, N.C., Castrillo, G., Chory, J., DeHaan, L.R., Duarte, C.M., et al, 2022. Climate change challenges, plant science solutions. The Plant Cell. 35(1):24-66. https://doi.org/10.1093/plcell/koac303.
Tamang, B., Zhang, Y., Zambrano, M., Ainsworth, E.A. 2022. Anatomical determinants of gas exchange and hydraulics vary with leaf shape in soybean. Annals of Botany. 131(6):909-920. https://doi.org/10.1093/aob/mcac118.
Wang, S., Guan, K., Zhang, C., Jiang, C., Zhou, Q., Li, K., Qin, Z., Ainsworth, E.A., He, J., Wu, J., Schaefer, D., Gentry, L.E., Margenot, A.J., Herzberger, L. 2022. Airborne hyperspectral imaging of cover crops through radiative transfer process-guided machine learning. Remote Sensing of Environment. 285. Article 113386. https://doi.org/10.1016/j.rse.2022.113386.
Burroughs, C.H., Montes, C.M., Mollar, C.A., Mitchell, N.G., Michael, A., Peng, B., Kimm, H., Pederson, T.L., Lipka, A.E., Bernacchi, C.J., Guan, K., Ainsworth, E.A. 2023. Reductions in leaf area index, pod production, seed size, and harvest index drive yield loss to high temperatures in soybean. Journal of Experimental Botany. 74(5):1629-1641. https://doi.org/10.1093/jxb/erac503.
Aspray, E.K., Mies, T.A., McGrath, J.A., Montes, C.M., Dalsing, B., Puthuval, K.K., Whetten, A., Herriott, J., Li, S., Bernacchi, C.J., McGrath, J.M., Ainsworth, E.A., et al. 2023. Two decades of fumigation data from the Soybean Free Air Concentration Enrichment facility. Scientific Data. 10. Article 226. https://doi.org/10.1038/s41597-023-02118-x.
Fu, P., Hu, L., Ainsworth, E.A., Tai, X., Myint, S.W., Zhan, W., Blakely, B.J., Bernacchi, C.J. 2021. Enhanced drought resistance of vegetation growth in cities due to urban heat, CO2 domes and O3 troughs. Environmental Research Letters. 16(12). Article 124052. https://doi.org/10.1088/1748-9326/ac3b17.
Digrado, A., Ainsworth, E.A. 2023. Modifying canopy architecture to optimize photosynthesis in crops. In: Sharwood, R., editor. Understanding and Improving Crop Photosynthesis. Cambridge, UK: Burleigh Dodds Science Publishing Limited. p. 159-202. http://dx.doi.org/10.19103/AS.2022.0119.11.
