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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Targeted modulation of pennycress lipid droplet proteins impacts droplet morphology and seed oil content

SUMMARY Lipid droplets (LDs) are unusual organelles that have a phospholipid monolayer surface and a hydrophobic matrix. In oilseeds, this matrix is nearly always composed of triacylglycerols (TGs) for efficient storage of carbon and energy. Various proteins play a role in their assembly, stability and turnover, and even though the major structural oleosin proteins in seed LDs have been known for decades, the factors influencing LD formation and dynamics are still being uncovered mostly in the “model oilseed” Arabidopsis. Here we identified several key LD biogenesis proteins in the seeds of pennycress, a potential biofuel crop, that were correlated previously with seed oil content and characterized here for their participation in LD formation in transient expression assays and stable transgenics. One pennycress protein, the lipid droplet associated protein‐interacting protein (LDIP), was able to functionally complement the Arabidopsis ldip mutant, emphasizing the close conservation of lipid storage among these two Brassicas. Moreover, loss‐of‐function ldip mutants in pennycress exhibited increased seed oil content without compromising plant growth, raising the possibility that LDIP or other LD biogenesis factors may be suitable targets for improving yields in oilseed crops more broadly.

Guzha, Athanas↗
NASA NTRS1977

A plant canopy light absorption model with application to wheat

From the light absorption model the absorption of light in the photosynthetically active region of the spectrum was calculated for a Penjamo wheat crop for several situations including: (1) the percent absorption of the incident radiation by a canopy having a four layer structure; (2) the percent absorption of light by the individual layers within a four layer canopy and by the underlying soil; (3) the percent absorption of light by each vegetative canopy layer for variable sun angle; and (4) the cumulative solar energy absorbed by the developing wheat canopy as it progresses from a single layer through its growth stages to a three layer canopy. This calculation was also presented as a function of the leaf area index.

Chance, J. E.↗
NASA NTRS1981

Sample selection in foreign similarity regions for multicrop experiments

The selection of sample segments in the U.S. foreign similarity regions for development of proportion estimation procedures and error modeling for Argentina, Australia, Brazil, and USSR in AgRISTARS is described. Each sample was chosen to be similar in crop mix to the corresponding indicator region sample. Data sets, methods of selection, and resulting samples are discussed.

Malin, J. T.↗
NASA NTRS1985

Controlled environment life support system: Calcium-related leaf injuries on plants

A calcium related injury in lettuce termed tipburn was the focus of this study. It affects the young developing leaves as they become enclosed during head formation. It is a good model system to study because the injury can be induced with good predictability and lettuce is one of the crops chosen by the CELSS program for concentrated study. Investigations were undertaken to study a number of different procedures, that would have the potential for encouraging movement of calcium into the young developing leaves and to study the time course and pattern of calcium accumulation in developing leaves to provide a basis for developing effective control procedures for this injury.

Tibbitts, T. W.↗
NASA NTRS2001

On the Use and Validation of Mosaic Heterogeneity in Atmospheric Numerical Models

The mosaic land modeling approach allows for the representation of multiple surface types in a single atmospheric general circulation model grid box. Each surface type, collectively called 'tiles' correspond to different sets of surface characteristics (e.g. for grass, crop or forest). Typically, the tile space data is averaged to grid space by weighting the tiles with their fractional cover. While grid space data is routinely evaluated, little attention has been given to the tile space data. The present paper explores uses of the tile space surface data in validation with station observations. The results indicate the limitations that the mosaic heterogeneity parameterization has in reproducing variations observed between stations at the Atmospheric Radiation Measurement Southern Great Plains field site.

Bosilovich, Michael G.↗
NASA NTRS2010

Atmospheric Circulation Anomalies During Two Persistent North American Droughts: 1932-1939 and 1948-1957

We use an early twentieth century (1908-1958) atmospheric reanalysis, based on assimilation of surface and sea level pressure observations, to contrast atmospheric circulation during two periods of persistent drought in North America: 1932-1939 (the Dust Bowl) and 1948-1957. Primary forcing for both droughts is believed to come from anomalous sea surface temperatures (SSTs): a warm Atlantic and a cool eastern tropical Pacific. For boreal winter (October-March) in the 1950s, a stationary wave pattern originating from the tropical Pacific is present, with positive centers over the north Pacific and north Atlantic ocean basins and a negative center positioned over northwest North America and the tropical/subtropical Pacific. This wave train is largely absent for the 1930s drought; boreal winter height anomalies are organized much more zonally, with positive heights extending across northern North America. For boreal summer (April-September) during the 1930s, a strong upper level ridge is centered over the Great Plains; this feature is absent during the 1950s and appears to be linked to a weakening of the Great Plains low-level jet (GPLLJ). Subsidence anomalies are co-located over the centers of each drought: in the central Great Plains for the 1930s and in a band extending from the southwest to the southeastern United States for the 1950s. The location and intensity of this subsidence during the 1948-1957 drought is a typical response to a cold eastern tropical Pacific, but for 1932-1939 deviates in terms of the expected intensity, location, and spatial extent. Overall, circulation anomalies during the 1950s drought appear consistent with the expected response to the observed SST forcing. This is not the case for the 1930s, implying some other causal factor may be needed to explain the Dust Bowl drought anomalies. In addition to SST forcing, the 1930s were also characterized by massive alterations to the land surface, including regional-scale devegetation from crop failures and intensive wind erosion and dust storms. Incorporation of these land surface factors into a general circulation model greatly improves the simulation of precipitation and subsidence anomalies during this drought, relative to simulations with SST forcing alone. Even with additional forcing from the land surface, however, the model still has difficulty reproducing some of the other circulation anomalies, including weakening of the GPLLJ and strengthening of the upper level ridge during AMJJAS. This may be due to either weaknesses in the model or uncertainties in the boundary condition estimates. Still, analysis of the circulation anomalies supports the conclusion of an earlier paper (Cook et al. in Proc Natl Acad Sci 106:4997, 2009), demonstrating that land degradation factors are consistent with the anomalous nature of the Dust Bowl drought.

Cook, Benjamin↗
NASA NTRS2020

Ohio River Basin Water Resources: Monitoring Flash Drought Potential and Quantifying the Hydrologic Impacts in the Ohio River Basin

Flash drought conditions emerge in a matter of weeks following persistent weather anomalies, such as high temperatures or large vapor pressure deficits, that drive increased evaporative demand. Vegetation response rapidly depletes soil moisture, threatening surface water supplies, triggering significant crop loss, and increasing wildfire risk. Drought indices sensitive to flash drought are currently not included in drought forecast models in the Ohio River Basin (ORB). The team assessed and compared drought indices, gauge-based data, and satellite measurements over the course of the September 2019 flash drought event in the Ohio River Basin to investigate environmental fingerprints throughout flash drought evolution. Potential leading flash drought indicators were compared to the Standardized Precipitation Index (SPI) to aid the National Weather Service (NWS) Ohio River Forecast Center and Kentucky Climate Center in producing early warning flash drought forecasts. These drought indices included Evaporative Demand Drought Index (EDDI), Standardized Precipitation Evapotranspiration Index (SPEI), and Landscape Evaporative Response Index (LERI) (derived from Terra Moderate Resolution Imaging Spectroradiometer (MODIS)). Drought index behavior inherently varies based on parameters incorporated - EDDI measures evaporative demand through potential evapotranspiration, and demonstrates more variations due to sensitivity to seasonal changes in evaporative demand throughout the 2010-2019 study period. Conversely, LERI measures evaporative response through actual evapotranspiration, representing different environmental changes. Soil moisture response was evaluated using Soil Moisture Active Passive (SMAP) L-band radiometer data and Kentucky Mesonet gauge-based measurements. This analysis enables climatologists and weather forecasters to keep decision-makers and stakeholders better informed about drought risks, and to implement the appropriate actions for preparation of drought onset.

Adelaide Schmid↗
NASA NTRS2020

Ohio River Basin Water Resources: Monitoring Flash Drought Potential and Quantifying the Hydrologic Impacts in the Ohio River Basin Utilizing NASA Earth Observations

Flash drought conditions emerge in a matter of weeks following persistent weather anomalies, such as high temperatures or large vapor pressure deficits, that drive increased evaporative demand. Vegetation response rapidly depletes soil moisture, threatening surface water supplies, triggering significant crop loss, and increasing wildfire risk. Drought indices sensitive to flash drought are currently not included in drought forecast models in the Ohio River Basin (ORB). The team assessed and compared drought indices, gauge-based data, and satellite measurements over the course of the September 2019 flash drought event in the Ohio River Basin to investigate environmental fingerprints throughout flash drought evolution. Potential leading flash drought indicators were compared to the Standardized Precipitation Index (SPI) to aid the National Weather Service (NWS) Ohio River Forecast Center and Kentucky Climate Center in producing early warning flash drought forecasts. These drought indices included Evaporative Demand Drought Index (EDDI), Standardized Precipitation Evapotranspiration Index (SPEI), and Landscape Evaporative Response Index (LERI) (derived from Terra Moderate Resolution Imaging Spectroradiometer (MODIS)). Drought index behavior inherently varies based on parameters incorporated -EDDI measures evaporative demand through potential evapotranspiration, and and demonstrates more variations due to sensitivity to seasonal changes in evaporative demand throughout the 2010-2019 study period. Conversely, LERI measures evaporative response through actual evapotranspiration, representing different environmental changes. Soil moisture response was evaluated using Soil Moisture Active Passive (SMAP) L-band radiometer data and Kentucky Mesonet gauge-based measurements. This analysis enables climatologists and weather forecasters to keep decision-makers and stakeholders better informed about drought risks to implement the appropriate actions for preparation of drought onset.

DEVELOP Project Summary↗
DOE OSTI2026

Data from: Coupled machine learning-ecosystem ensemble models substantially improve predictions of nitrous oxide (N 2 O) fluxes from US croplands

Nitrous oxide (N₂O) is a potent and persistent greenhouse gas, with rising atmospheric concentrations driven in part by inefficient use of synthetic nitrogen (N) fertilizers in agriculture. Predicting soil N₂O emissions is challenging due to high spatial and temporal variability arising from complex soil biogeochemical processes. Process-based ecosystem models and standalone machine learning (ML) approaches without extensive site-specific calibration often miss high emission episodes. Here, we show how an Ensemble Modeling System (EMS) based on outputs from an ensemble of ecosystem models coupled to an ensemble of ML models can improve predictions and understanding of N2O fluxes from US cropland. Trained and validated on approximately 12,000 N2O chamber measurements at 17 U.S. Midwest sites (six crops, 35 management practices), the EMS accurately predicted daily fluxes of N2O at both training (R² = 0.84, RMSE = 16.4 g N ha⁻¹ d⁻¹) and held-out testing sites (R² = 0.84, RMSE = 6.2 g N ha⁻¹ d⁻¹). Analyses identified six dominant N₂O drivers: soil organic carbon (SOC), NH₄⁺, NO₃⁻, water-filled pore space (WFPS), soil temperature, and biomass production. Wet, warm soils produced large N₂O peaks only with sufficient SOC and mineral N; in low-SOC soils, fluxes remained low. Incorporating these drivers into process-based models might significantly improve their predictive capacity. The EMS demonstrates a strong potential to predict N₂O fluxes at unseen sites, enabling more reliable regional inventories, improved gap-filling where measurements are sparse, and enhanced understanding of mechanisms to advance targeted mitigation strategies in food, feed, and bioenergy crops.

agricultural sciences↗
NASA NTRS1991

Wheat yield estimation at the farm level using TM Landsat and agrometeorological data

A model for estimating wheat yields on the farm level was developed, that integrates the Landsat TM data and agrometeorological information. Results obtained for a test site in southern Brasil for years of 1986 and 1987 show that the vegetation index derived from Landsat TM could account for the 60 to 40 percent wheat-yield variability observed between the two crop years. Compared to results using either the Landsat TM vegetation index or the agrometeorological data alone, the joint use of both types of data in a single model yielded a significant improvement.

Rudorff, B. F. T.↗
DOE OSTI2025

Soil erosion and lateral carbon fluxes from corn stover-derived biofuel

Abstract Crop residues hold promise to alleviate food vs. fuel competition and contribute to biofuel production. However, the impacts of lateral sediment and carbon fluxes caused by residue removal are not fully understood. Here we employ agroecosystem modeling to conservatively estimate lateral sediment and carbon fluxes resulting from partial corn stover removal in the U.S. Midwest. Results show substantial increases in soil erosion resulting from corn stover removal. For example, the area of continuous corn and corn soybean cropping systems exceeding soil erosion tolerance threshold could increase from 1.1 to 13.3% because of 66% corn stover removal. Depending on removal intensity, conservation, and crop rotation, the stover removal-induced increases in eroded soil organic carbon is equivalent to 3.9–12.5 gCO 2 e MJ −1 , which is comparable to other components of the life cycle impacts of corn stover-derived biofuel. Our findings highlight the need to consider the soil erosion and lateral carbon fluxes impacts of corn stover removal in designing supply chains for cellulosic biofuel production.

Science & Technology - Other Topics↗
NASA NTRS2010

Improved Hypoxia Modeling for Nutrient Control Decisions in the Gulf of Mexico

As required by the Harmful Algal Bloom and Hypoxia Research Control Act of 1998, the Mississippi River/Gulf of Mexico Watershed Nutrient Task Force issued the 2001 Gulf Hypoxia Action Plan (updated in 2008). In response to the Gulf Hypoxia Action Plan of 2001 (updated in 2008), the EPA Gulf of Mexico Hypoxia Modeling and Monitoring Project has established a detailed model for the Mississippi-Attchafalaya River Basin which provides a capability to forecast the multi-source nutrient loading to the Gulf and the subsequent bio-geochemical processes leading to hypoxic conditions and subsequent effects on Gulf habitats and fisheries. The primary purpose of the EPA model is to characterize the impacts of nutrient management actions, or proposed actions on the spatial and temporal characteristics of the Gulf hypoxic zone. The model is expected to play a significant role in determining best practices and improved strategies for incentivizing nutrient reduction strategies, including installation of on-farm structures to reduce sediment and nutrient runoff, use of cover crops and other agricultural practices, restoration of wetlands and riparian buffers, improved waste water treatment and decreased industrial nitrogen emissions. These decisions are currently made in a fragmented way by federal, state, and local agencies, using a variety of small scale models and limited data. During the past three years, EPA has collected an enormous amount of in-situ data to be used in the model. We believe that the use of NASA satellite data products in the model and for long term validation of the model has the potential to significantly increase the accuracy and therefore the utility of the model for the decision making described above. This proposal addresses the Gulf of Mexico Alliance (GOMA) priority issue of reductions in nutrient inputs to coastal ecosystem. It further directly relates to water quality for healthy beaches and shellfish beds and wetland and coastal conservation restoration.

Habib, Shaid↗
DOE OSTI2026

Bioenergy Cropping Reduces the Spatiotemporal Scaling of Soil Bacterial Biodiversity

Widespread bioenergy cropping can transform landscapes, strongly affecting biodiversity. However, the impact of bioenergy cropping on the spatiotemporal scaling of soil biodiversity remains virtually unknown, despite its profound implications for the functioning of the ecological community. Here, we investigated how bioenergy cropping influenced the spatiotemporal scaling of soil bacterial biodiversity in marginal soils (sandy loam and clay loam soils) in Oklahoma, USA. We detected strong, significant species-time-area relationships (STARs) and phylogenetic-time-area relationships (PTARs) in bacterial communities and their lineages, suggesting that STARs and PTARs exist in microbial ecology within the studied system. Also, spatiotemporal scaling rates (the slopes of STAR and PTAR models) varied substantially among bacterial lineages and were positively correlated with their 16S rRNA gene copy numbers, a genomic trait indicative of microbial growth potentials. Strikingly, bioenergy cropping significantly reduced spatiotemporal scaling rates by 6.8%-14.1%, with a more pronounced reduction observed in sandy loam soils, where those rates were significantly lower than in clay loam soils. The heterogeneity of soil phosphorus and carbon resulted in variations in bacterial spatiotemporal scaling rates. Collectively, our findings suggest that bioenergy cropping may alleviate rapid shifts in soil biodiversity across space and time, thereby stabilizing soil biodiversity and supporting its role as part of sustainable land management and climate mitigation strategies.

bacterial diversity↗
NASA NTRSDate not supplied

Atmospheric Boundary-Layer and Flutter Computations Using CFD Model of the Transonic Dynamics Tunnel

This paper presents two Computational Fluid Dynamics (CFD) models of the flow in the NASA Langley Research Center Transonic Dynamics Tunnel (TDT). The TDT is a continuous-flow, closed circuit wind tunnel with a 16- by 16-foot slotted test section with cropped corners. The tunnel was originally built as the 19-ft Pressure Tunnel in 1938, but it was converted to the current transonic tunnel in the 1950s, with capabilities to use either air or heavy gas as the test medium. The first computational model describes the generation of an atmospheric-boundary-layer (ABL) profile inside the tunnel. An ABL, which includes both a wind profile and turbulence content, is one of the aerodynamic characteristics affecting the occurrence of wind-induced oscillations for a launch vehicle sitting on a pad. The challenging part of this analysis was modeling the turbulent flow inside the tunnel. This is due to the special ABL-generating hardware that was installed at the entrance of the TDT test section in order to change the downstream velocity profile and to introduce velocity fluctuations into the flow. The second CFD model builds on the computational aeroelastic results that were generated in support of the second Aeroelastic Prediction Workshop (AePW) for the NASA Benchmark Supercritical Wing (BSCW) configuration. During the AePW, the wing-only configuration (classical free-air model) was analyzed. In the current study, the flutter computations were conducted on the configuration as it was mounted in the TDT during the experiment. This includes the wing attached to the splitter plate that was attached to the wind-tunnel walls. The preliminary results show that the wind-tunnel walls marginally affect flutter prediction.

Pawel Chwalowski↗
DOE OSTI2024

Mini-Canister Radiolysis Testing of ASNF Materials and Surrogates

An experimental irradiation campaign to investigate radiolysis behavior of ASNF was conducted using in situ gas monitoring of small, sealed stainless-steel vessels (mini-canisters) containing aluminum samples with adherent (oxy)hydroxide films under helium backfill. The samples were irradiated with gamma radiation from a Co-60 irradiator. The samples tested included aluminum plate assemblies with lab-grown (oxy)hydroxides as surrogates for fuel as well as an end cropping from an actual ASNF assembly retrieved from long-term wet storage. These experiments enabled investigation of the impacts of various fuel drying approaches on the radiolytic generation rate and measurement of the H 2 yield associated with a reactor exposed sample with reactor-formed (oxy)hydroxide. The resulting data can be incorporated into model development for ASNF in dry storage. This report presents the cumulative results from four surrogate assemblies tested after application of different preparation (drying) conditions as well as the ASNF cropping; some post-irradiation testing was included. The mini-canister results are compared to data from related experimental campaigns that also tested the impact of drying conditions using samples irradiated in glass ampoules and discusses implications of the combined data

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2016

Agricultural Fires in the Southeastern U.S. During SEAC4RS: Emissions of Trace Gases and Particles and Evolution of Ozone, Reactive Nitrogen, and Organic Aerosol

Emissions from 15 agricultural fires in the southeastern U.S. were measured from the NASA DC-8 research aircraft during the summer 2013 Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign. This study reports a detailed set of emission factors (EFs) for 25 trace gases and 6 fine particle species. The chemical evolution of the primary emissions in seven plumes was examined in detail for ~1.2 h. A Lagrangian plume cross-section model was used to simulate the evolution of ozone (O3), reactive nitrogen species, and organic aerosol (OA). Observed EFs are generally consistent with previous measurements of crop residue burning, but the fires studied here emitted high amounts of SO2 and fine particles, especially primary OA and chloride. Filter-based measurements of aerosol light absorption implied that brown carbon (BrC) was ubiquitous in the plumes. In aged plumes, rapid production of O3, peroxyacetyl nitrate (PAN), and nitrate was observed with (Delta)O3/(Delta)CO, (Delta)PAN/(Delta)NOy, and (Delta)nitrate/(Delta)NOy reaching approx. 0.1, approx. 0.3, and approx.0.3. For five selected cases, the model reasonably simulated O3 formation but underestimated PAN formation. No significant evolution of OA mass or BrC absorption was observed. However, a consistent increase in oxygen-to-carbon (O/C) ratios of OA indicated that OA oxidation in the agricultural fire plumes was much faster than in urban and forest fire plumes. Finally, total annual SO2, NOx, and CO emissions from agricultural fires in Arkansas, Louisiana, Mississippi, and Missouri were estimated (within a factor of approx. 2) to be equivalent to approx. 2% SO2 from coal combustion and approx. 1% NOx and approx. 9% CO from mobile sources.

OA mass or BrC absorption↗
DOE OSTI2020

Farmers’ Perceptions of Marginal Land for Biofuel Crops

The dataset includes the survey results about farmers’ perceptions of marginal land availability and the likelihood of a land pixel being marginal based on a machine learning model trained from the survey. Two spreadsheet files are the farmer and farm characteristics (marginal_land_survey_data_shared.xlsx), and the existing land use of marginal lands (land_use_info_sharing.xlsx). Note: the blank cells in these two spreadsheets mean missing values in the survey response. The GeoTiff file includes two bands, one the marginal land likelihood in the Midwestern states (0-1), the other the dominant reason of land marginality (0-5; 0 for farm size, 1 for growing season precipitation, 2 for root zone soil water capacity, 3 for average slope, 4 for growing season mean temperature, and 5 for growing season diurnal range of temperature). To read the data, please use a GIS software such as ArcGIS or QGIS.

marginal land↗
DOE OSTI2024

Photosynthetic responses of switchgrass to light and CO 2 under different precipitation treatments

Switchgrass ( Panicum virgatum L .) is a prominent bioenergy crop with robust resilience to environmental stresses. However, our knowledge regarding how precipitation changes affect switchgrass photosynthesis and its responses to light and CO 2 remains limited. To address this knowledge gap, we conducted a field precipitation experiment with five different treatments, including −50%, −33%, 0%, +33%, and +50% of ambient precipitation. To determine the responses of leaf photosynthesis to CO 2 concentration and light, we measured leaf net photosynthesis of switchgrass under different CO 2 concentrations and light levels in 2020 and 2021 for each of the five precipitation treatments. We first evaluated four light and CO 2 response models (i.e., rectangular hyperbola model, nonrectangular hyperbola model, exponential model, and the modified rectangular hyperbola model) using the measurements in the ambient precipitation treatment. Based on the fitting criteria, we selected the nonrectangular hyperbola model as the optimal model and applied it to all precipitation treatments, and estimated model parameters. Overall, the model fit field measurements well for the light and CO 2 response curves. Precipitation change did not influence the maximum net photosynthetic rate ( P max ) but influenced other model parameters including quantum yield ( α ), convexity ( θ ), dark respiration ( Rd ), light compensation point ( LCP ), and saturated light point ( LSP ). Specifically, the mean P max of five precipitation treatments was 17.6 μmol CO 2 m −2 s −1 , and the ambient treatment tended to have a higher P max . The +33% treatment had the highest α , and the ambient treatment had lower θ and LCP , higher Rd , and relatively lower LSP . Furthermore, precipitation significantly influenced all model parameters of CO 2 response. The ambient treatment had the highest P max , largest α , and lowest θ , R d , and CO 2 compensation point LCP . Overall, this study improved our understanding of how switchgrass leaf photosynthesis responds to diverse environmental factors, providing valuable insights for accurately modeling switchgrass ecophysiology and productivity.

09 BIOMASS FUELS↗