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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11

The Brachypodium ENCODE Project – from sequence to function: Predicting physiological responses in grasses to facilitate engineering of biofuel crops

The overarching goal of this proposal was to gain deep knowledge of chromatin dynamics and gene networks related to stress responses in grasses. To accomplish this goal our Brachypodium ENCODE project (1) coupled drought-focused physiological analysis with multiple layers of ENCODE ‘omics’ profiling; (2) obtained fundamental information about the Brachypodium transcriptome, epigenome, chromatin dynamics, and gene regulatory networks; and (3) elucidated the regulatory dynamics of gene networks that can be manipulated to increase energy grass crop productivity.

09 BIOMASS FUELS↗

Plant Synthetic Biology Conference – Travel Awardees and Speakers

The overarching goals of the Plant Synthetic Biology (SynBio) Conference, convened by the American Society of Plant Biologists (ASPB), were to raise community consciousness of what SynBio is and what it can do in key areas, including crop productivity, specialty chemicals, biosensors, and microbe-plant interactions. Within that context, the conference had two broad objectives. First, to feature a set of leading university and industry speakers from the US and Europe whose research on plants and microbes spans the SynBio spectrum with respect both to technology and to applications, as well as short talks (selected from submitted abstracts) on cutting-edge topics. And second, to foster exchanges among public sector scientists and industry scientists, whose participation as poster presenters, exhibitors, and sponsors was actively encouraged because so much innovative SynBio work is being carried out at dynamic young companies.

60 APPLIED LIFE SCIENCES↗

Step Catalysis to Synthesize Fossil-Free Ammonia at Atmospheric Pressure (Final Technical Report)

Affordable fossil-free ammonia synthesis will enable high-yield sustainable crop production for a growing world population while preserving the planet and making the best use of water and land. Simple technology amenable to intermittent operation using renewable energy will be made available through step catalysis activating dinitrogen at atmospheric pressure by nitride formation. Project objectives: (1) At the single particle level, quantify and analyze N2 activation by doped or alloyed manganese macroscopic- and nano particles at atmospheric pressure, (2) Quantify and analyze ammonia synthesis from doped or alloyed metal nitride particles when contacting them with hydrogen at atmospheric pressure, and (3) Integrate experimental data and atomic-level computational models to predict the behavior of metal alloys in nitrogen activation and subsequent ammonia synthesis.

10 SYNTHETIC FUELS↗

BTRIC Technical Support for Appalachia: FY 2023 Summary Report on Net Negative Carbon Building Demonstration with AgPod

This study investigates the effects of various concentrations of carbon dioxide (CO 2 ) on the photosynthesis and biomass accumulation of crops growing in an Agricultural Pod (AgPod). The initial test crop was kale. It has been found that increasing the CO 2 concentration in the AgPod promotes higher photosynthetic rates in kale plants up to 1300 ppm (highest CO 2 concentration). An interesting finding was that net photosynthetic rates of kale leaves remain unsaturated until unusually high levels of photosynthetically active radiation (PAR, > 1200 µmolm-2s-1) and CO 2 concentration (> 1100 ppm) are reached. Such high levels of saturating PAR and CO 2 concentration values rarely occur under natural conditions, suggesting a promising potential for carbon capture via enriched greenhouse crop production. This task is one part of an overall plan to incorporate an AgPod to utilize carbon captured from the atmosphere to achieve net negative carbon emissions in a small neighborhood or community.

54 ENVIRONMENTAL SCIENCES↗

Conserved genetic mechanisms for biotic stress in sorghum (Final report)

Developing durable disease resistance for biofuel crops is crucial, particularly as the range of biofuel crop production expands and pathogens of other plant species evolve to cause diseases of bioenergy feedstocks. Setosphaeria species are significant pathogens of the Andropogonae, and S. turcica can infect both maize and sorghum. Sorghum leaf blight (SLB), caused by S. turcica, is widespread and can decrease grain yields up to 50%, reduce forage quantity and quality, and predispose plants to other diseases, such as anthracnose. Our overall objective was to gain a systems-level understanding of the pathosystem by leveraging natural genetic variation, host specificity of the pathogen, and transcriptome analysis to improve biotic stress resistance in sorghum. We proposed three specific goals: 1) Identify sorghum alleles conferring resistance to S. turcica using natural genetic variation. 2) Characterize genes associated with biotic stress response in sorghum. 3) Identify fungal genes responsible for host specificity.

09 BIOMASS FUELS↗

Conserved genetic mechanisms for biotic stress in sorghum (Final Report)

Developing durable disease resistance for biofuel crops is crucial, particularly as the range of biofuel crop production expands and pathogens of other plant species evolve to cause diseases of bioenergy feedstocks. Setosphaeria species are significant pathogens of the Andropogonae, and S. turcica can infect both maize and sorghum. Sorghum leaf blight (SLB), caused by S. turcica, is widespread and can decrease grain yields up to 50%, reduce forage quantity and quality, and predispose plants to other diseases, such as anthracnose. Our overall objective was to gain a systems-level understanding of the pathosystem by leveraging natural genetic variation, host specificity of the pathogen, and transcriptome analysis to improve biotic stress resistance in sorghum. We proposed three specific goals: 1) Identify sorghum alleles conferring resistance to S. turcica using natural genetic variation. 2) Characterize genes associated with biotic stress response in sorghum. 3) Identify fungal genes responsible for host specificity.

09 BIOMASS FUELS↗

Zero-Power Wireless Infrared Digitizing Sensors for Large Scale Energy-Smart Farm

This project, funded by ARPA-E and led by Northeastern University, developed zeropower infrared digitizing sensors to optimize irrigation and enhance crop yields. Traditional water stress detection methods are costly and require frequent maintenance, limiting their effectiveness. Our research identified shortwave infrared (SWIR) transmittance as the most reliable indicator of plant water stress and developed plasmonically enhanced micromechanical photoswitches (PMPs) that operate with minimal power. The sensors offer low-cost, large-scale deployment, auto-calibration across different crops, and a 10-year battery life, significantly reducing maintenance costs. The system achieved 4x greater accuracy than conventional soil moisture sensors while ensuring economic feasibility. By enabling precision irrigation, this technology conserves water, enhances crop productivity, and lowers operational costs, making it a scalable solution for sustainable agriculture and global food security.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Thioredoxin VdTrx1, an unconventional secreted protein, is a virulence factor in Verticillium dahliae

Understanding how plant pathogenic fungi adapt to their hosts is of critical importance to securing optimal crop productivity. In response to pathogenic attack, plants produce reactive oxygen species (ROS) as part of a multipronged defense response. Pathogens, in turn, have evolved ROS scavenging mechanisms to undermine host defense. Thioredoxins (Trx) are highly conserved oxidoreductase enzymes with a dithiol-disulfide active site, and function as antioxidants to protect cells against free radicals, such as ROS. However, the roles of thioredoxins in Verticillium dahliae , an important vascular pathogen, are not clear. Through proteomics analyses, we identified a putative thioredoxin (VdTrx1) lacking a signal peptide. VdTrx1 was present in the exoproteome of V. dahliae cultured in the presence of host tissues, a finding that suggested that it plays a role in host-pathogen interactions. We constructed a VdTrx1 deletion mutant Δ VdTrx1 that exhibited significantly higher sensitivity to ROS stress, H 2 O 2 , and tert -butyl hydroperoxide ( t -BOOH). In vivo assays by live-cell imaging and in vitro assays by western blotting revealed that while VdTrx1 lacking the signal peptide can be localized within V. dahliae cells, VdTrx1 can also be secreted unconventionally depending on VdVps36, a member of the ESCRT-II protein complex. The Δ VdTrx1 strain was unable to scavenge host-generated extracellular ROS fully during host invasion. Deletion of VdTrx1 resulted in higher intracellular ROS levels of V. dahliae mycelium, displayed impaired conidial production, and showed significantly reduced virulence on Gossypium hirsutum , and model plants, Arabidopsis thaliana and Nicotiana benthamiana . Thus, we conclude that VdTrx1 acts as a virulence factor in V. dahliae .

Tian, Li↗

Molecular mechanism of Rubisco activase: Dynamic assembly and Rubisco remodeling

Ribulose-1,5-bisphosphate (RuBP) carboxylase-oxygenase (Rubisco) enzyme is the limiting step of photosynthetic carbon fixation, and its activation is regulated by its co-evolved chaperone, Rubisco activase (Rca). Rca removes the intrinsic sugar phosphate inhibitors occupying the Rubisco active site, allowing RuBP to split into two 3-phosphoglycerate (3PGA) molecules. This review summarizes the evolution, structure, and function of Rca and describes the recent findings regarding the mechanistic model of Rubisco activation by Rca. New knowledge in these areas can significantly enhance crop engineering techniques used to improve crop productivity.

59 BASIC BIOLOGICAL SCIENCES↗

Validation of a metabolite–GWAS network for Populus trichocarpa family 1 UDP-glycosyltransferases

Metabolite genome-wide association studies (mGWASs) are increasingly used to discover the genetic basis of target phenotypes in plants such as Populus trichocarpa , a biofuel feedstock and model woody plant species. Despite their growing importance in plant genetics and metabolomics, few mGWASs are experimentally validated. Here, we present a functional genomics workflow for validating mGWAS-predicted enzyme–substrate relationships. We focus on uridine diphosphate–glycosyltransferases (UGTs), a large family of enzymes that catalyze sugar transfer to a variety of plant secondary metabolites involved in defense, signaling, and lignification. Glycosylation influences physiological roles, localization within cells and tissues, and metabolic fates of these metabolites. UGTs have substantially expanded in P. trichocarpa , presenting a challenge for large-scale characterization. Using a high-throughput assay, we produced substrate acceptance profiles for 40 previously uncharacterized candidate enzymes. Assays confirmed 10 of 13 leaf mGWAS associations, and a focused metabolite screen demonstrated varying levels of substrate specificity among UGTs. A substrate binding model case study of UGT-23 rationalized observed enzyme activities and mGWAS associations, including glycosylation of trichocarpinene to produce trichocarpin, a major higher-order salicylate in P. trichocarpa. We identified UGTs putatively involved in lignan, flavonoid, salicylate, and phytohormone metabolism, with potential implications for cell wall biosynthesis, nitrogen uptake, and biotic and abiotic stress response that determine sustainable biomass crop production. Our results provide new support for in silico analyses and evidence-based guidance for in vivo functional characterization.

59 BASIC BIOLOGICAL SCIENCES↗

GmMPK6 Positively Regulates Salt Tolerance through Induction of GmRbohI1 in Soybean

Salt stress is a critical environmental stress that impairs plant growth and development, especially in crop productivity; therefore, understanding the salt response in plants is the basis for their development of salt tolerance. Under salinity, soybean mitogen-activated protein kinase 6 (GmMPK6) is activated and positively regulates reactive oxygen species (ROS) generation. However, it is not yet elucidated how GmMPK6 regulates ROS generation and its role in salt tolerance. Here, we show that GmMPK6, solely activated in NaCl treatment, and gene expression of GmRbohI1 was not only reduced by MPK inhibitor SB202190 in NaCl treatment, but also increased in a GMKK1-expressing protoplast. Furthermore, SB202190 and the NADPH-oxidase inhibitor, diphenyleneiodonium chloride, increased susceptibility to salt stress. The expression of GmRD19A was induced by NaCl treatment, but this expression was compromised by SB202190. Consequently, we revealed that GmMPK6 induces ROS generation through the transcriptional regulation of GmRbohI1 and increases salt tolerance in soybean.

59 BASIC BIOLOGICAL SCIENCES↗

Inference of Gene Regulatory Network Uncovers the Linkage between Circadian Clock and Crassulacean Acid Metabolism in Kalanchoë fedtschenkoi

The circadian clock drives time-specific gene expression, enabling biological processes to be temporally controlled. Plants that conduct crassulacean acid metabolism (CAM) photosynthesis represent an interesting case of circadian regulation of gene expression as stomatal movement is temporally inverted relative to stomatal movement in C3 plants. The mechanisms behind how the circadian clock enabled physiological differences at the molecular level is not well understood. Recently, the rescheduling of gene expression was reported as a mechanism to explain how CAM evolved from C3. Therefore, we investigated whether core circadian clock genes in CAM plants were re-phased during evolution, or whether networks of phase-specific genes were simply re-wired to different core clock genes. We identified candidate core clock genes based on gene expression features and then applied the Local Edge Machine (LEM) algorithm to infer regulatory relationships between this new set of core candidates and known core clock genes in Kalanchoë fedtschenkoi. We further inferred stomata-related gene targets for known and candidate core clock genes and constructed a gene regulatory network for core clock and stomata-related genes. Our results provide new insight into the mechanism of circadian control of CAM-related genes in K. fedtschenkoi, facilitating the engineering of CAM machinery into non-CAM plants for sustainable crop production in water-limited environments.

59 BASIC BIOLOGICAL SCIENCES↗

Examining the Characteristics of the Cropland Data Layer in the Context of Estimating Land Cover Change

The United States Department of Agriculture (USDA) Cropland Data Layer (CDL) provides spatially explicit information about crop production area and has served as a prevalent data source for characterizing cropland change in the U.S. in the last decade. Understanding the accuracy of the CDL is paramount because of the reliance on it for management and policy making. This study examined the characteristics of the CDL from 2007 to 2017 using comparisons to other USDA datasets. The results showed when examining the cropland area for the same year, the CDL produced comparable trends with other datasets (R 2 > 0.95), but absolute area differed. The estimated area of cropland changes from 2007 to 2012, 2008 to 2012 and 2012 to 2017 varied from weak to moderate correlation between the CDL and the tabular data (R 2 = 0.005~0.63). Differences in area of cropland change varied widely between data sources with the CDL estimating much larger change area. A series of image processing techniques designed to improve the confidence in cropland change estimated using the CDL reduced the area of estimated cropland change. The techniques also, unexpectedly, lowered the correlation in change estimated between the CDL and the tabular datasets. Estimated land cover change area varied widely based on analyses applied and could reverse from increasing to declining area in cropland. Further analyses showed unlikely change scenarios when comparing different year combinations. The authors recommend the CDL only be used for land cover change analysis if the error can be estimated and is within change estimates.

58 GEOSCIENCES↗

Predicting Short-Term Deformation in the Central Valley Using Machine Learning

Land subsidence caused by excessive groundwater pumping in Central Valley, California, is a major issue that has several negative impacts such as reduced aquifer storage and damaged infrastructures which, in turn, produce an economic loss due to the high reliance on crop production. This is why it is of utmost importance to routinely monitor and assess the surface deformation occurring. Two main goals that this paper attempts to accomplish are deformation characterization and deformation prediction. The first goal is realized through the use of Principal Component Analysis (PCA) applied to a series of Interferomtric Synthetic Aperture Radar (InSAR) images that produces eigenimages displaying the key characteristics of the subsidence. Water storage changes are also directly analyzed by the use of data from the Gravity Recovery and Climate Experiment (GRACE) twin satellites and the Global Land Data Assimilation System (GLDAS). The second goal is accomplished by building a Long Short-Term Memory (LSTM) model to predict short-term deformation after developing an InSAR time series using LiCSBAS, an open-source InSAR time series package. The model is applied to the city of Madera and produces better results than a baseline averaging model and a one dimensional convolutional neural network (CNN) based on a mean squared error metric showing the effectiveness of machine learning in deformation prediction as well as the potential for incorporation in hazard mitigation models. The model results can directly aid policy makers in determining the appropriate rate of groundwater withdrawal while maintaining the safety and well-being of the population as well as the aquifers’ integrity.

58 GEOSCIENCES↗

The Potential for Solar Farms to Protect Crops Against Extreme Weather Events

With climate change posing serious risks to crop production, solar PV has the potential to protect agriculture against extreme climate events. This concept has significant implications for agrivoltaics, but large gaps exist in the physical understanding of the climate resiliency that solar PV can bring to agriculture, and current studies focus on one-off designs ideal to protect against specific climate events. This study investigates key climate events that threaten agriculture throughout the year, including winter, spring, and summer climate threats.

Williams, Henry J↗

Viability and Financial Evaluation of Agrivoltaic Systems in Concord Grape Vineyards

Agrivoltaic systems, combining agriculture and solar photovoltaics (PV), present a forward- looking solution to global challenges in food security and the energy crisis. It can actualize co- located power generation and crop production, effectively mitigating land use conflicts between the solar industry and agriculture [1]. Presently, agrivoltaic research primarily focuses on conventional farmland. To promote the development of agrivoltaics, it’s essential to explore and study diverse application scenarios. Concord grape vineyards in New York consistently experience financial losses, prompting growers to seek additional revenue streams to preserve Concord grape industries [2]. This study presents the pioneering proposal for integrating solar PV into Concord vineyards. Through viability and financial assessment, this agrivoltaic system demonstrates the potential to alleviate grower losses and boost solar developers’ income, establishing a mutually beneficial scenario. Furthermore, it provides a conceptual approach for other vineyards facing similar challenges to mitigate losses and sustain local grape culture.

Williams, Henry J↗

Pixel-Registered Multimodal Synchrotron XRF and FTIR Microscopies Reveal Salinity Stress Response Mechanisms in Pistachio

Background: Salinity is a major abiotic stress that negatively affects nearly all plant species at all stages of growth. Drought and poor-quality irrigation cause high soil salinity and salt accumulation via evaporation, reducing crop productivity. Despite its critical importance, the spatial localization of salt ions and associated biochemical changes within plants experiencing high salinity remains largely unknown. In this study, we developed a multimodal imaging pipeline to understand the impact of salinity on the pistachio rootstock UCB-1 (Pistacia atlantica x Pistacia integerrima). We directly link biochemical fingerprints in stem tissue architecture with salt ion localization to provide insights into the strategies pistachio uses to tolerate salinity. Results: We observed that Pistacia spp. exposed to high salt conditions accumulated Ca, Si, Cl, Al and Mg as hotspots within the pith, compared to the control (of which only Ca and Al co-locate). In contrast, there was a decrease in K between the control and salinity treatment. Hotspots of amide I and II were present in the cortex and pith of the salinity treated sample. Additionally, the salinity treatment resulted in an increased abundance of pectin and carbohydrates within the pith compared to the control, and the abundance of esters/carboxylic acid was greater in the salinity treatment. Conclusions: We determined that Cl and K, S and P, and biochemical components polysaccharide and pectin, esters and carboxylic acid, amide I and cellulose are the strongest drivers of salinity- treatment induced variability. In the cortex and phloem/xylem, a negative K-Ca correlation decreases in the salinity treatment. Several hotspots of elements and amide I (proteins) appear under salinity treatment, particularly in the cortex, suggesting an increase in the production of stress-related proteins (in response to high Cl) and/or structural proteins (i.e. Ca). Together, these results indicate that pistachio responds to salinity through ion compartmentalization coupled with a targeted biochemical adjustment, rather than a broadscale tissue-wide response. Overall, these novel, spatially resolved pixel-registered multimodal imaging data provide an enabling platform to understand the mechanisms of salinity tolerance in Pistacia spp and can be broadly applied to studying stress-related phenotype response in various plant tissues.

FTIR spectromicroscopy↗

Dynamic integration of GCAM-Demeter and CLUBS-Select: Datasets on urban extensification effects on land cover, crop yields, net primary production, and CO2 emissions

The datasets provide background data from McManamay et al. (2024) Nature Communications Earth and Environment. We integrate projected dynamic non-urban lands from GCAM-Demeter with projected dynamic urban lands from SELECT from 2015 to 2100 at 1-km resolution to examine stress to the land system, compromised crop production, and losses in Net Primary Production (NPP), that can arise from the competition over land resources. These datasets include changes to non-urban land use and land cover, estimated losses in crop yields, losses in NPP, and increases in CO2 emissions.

Earth Systems↗