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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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DOE OSTI2023

Development of a Portable In Situ Phosphorous Sensor

While phosphorus is a critical nutrient for all forms of life, runoff leads to phosphorus accumulation in surface water where it can cause a variety of health, environmental, and economic problems. The Department of Energy is interested in conducting long-term field experiments to monitor the impact of phosphorus in terrestrial and aquatic environments, and to better understand a cost vs. benefit analysis of reducing phosphorus pollution. Performing such long-term experiments requires affordable sensors capable of monitoring low-level phosphorus concentrations under challenging environmental conditions. However, such sensors are currently not available. The goal of this proposed project is to develop and demonstrate a low-cost portable phosphorus sensor suitable for in situ measurements. We will determine the technical requirements for a Raman-based sensor system, design and build a signal amplifier, integrate it with a Raman-based sensor, and demonstrate a proof-of-concept level sensor system. The expected accomplishments for Phase I include the identification of the technical requirements of a combined Raman laser/spectrometer and cavity enhancement system, building a proof-of-concept level sensor system capable of detecting orthophosphate compounds at the desired level of 0.25 mg P/L and organic P compounds, and verification of the sensor performance under laboratory and field conditions. In addition, we will identify initial hardening requirements that will need to be implemented during Phase II. While we plan to develop an integrated sensor system for monitoring phosphorus, the cavity-based enhancement system can also be used in combination with other (non-phosphorus) Raman sensors that we plan to develop or that are already commercially available. A recent market report highlights the increasing demand for such environmental monitoring applications, with the market for chemical detection anticipated to grow at a compound annual growth rate of 6.5% (2020-2025). Wide-spread monitoring of phosphorus could reduce the damage from eutrophication in freshwater, which is estimated to be $2.2 billion annually, thereby increasing biodiversity, reducing costs required for drinking water treatment, and decreasing economic losses related to recreation and angling and lake property values.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A mixture of grass–legume cover crop species may ameliorate water stress in a changing climate

Climate change models predict increasing precipitation variability in the mid-latitude regions of Earth, generating a need to reduce the negative impacts of these changes on crop production. Despite considerable research on how cover crops support agriculture in a changing climate, understanding is limited of how climate change influences the growth of cover crops. We investigated the early development of two common cover crop species—crimson clover (Trifolium incarnatum) and rye (Secale cereale)—and hypothesized that growing them in the mixture would ameliorate stress from drought or waterlogging. This hypothesis was tested in a 25-day greenhouse experiment, where the two factors (species number and water stress) were fully crossed in randomized blocks, and plant responses were quantified through survival, growth rate, biomass production and root morphology. Water stress negatively influenced the early growth of these two species in contrasting ways: crimson clover was susceptible to drought while rye performed poorly under waterlogging. Per-plant biomass in rye was always greater in mixture than in monoculture, while per-plant biomass of crimson clover was greater in mixture under drought. Both species grew longer roots in mixture than in monoculture under drought, and total biomass of mixtures did not differ significantly from the more-productive monoculture (rye) in any water condition. In the face of increasingly variable precipitation, growing crimson clover and rye together has potential to ameliorate water stress, a possibility that should be further investigated in field experiments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

New soil carbon sequestration with nitrogen enrichment: a meta-analysis

Background and aims: Through agriculture and industry, humans are increasing the deposition and availability of nitrogen (N) in ecosystems worldwide. Carbon (C) isotope tracers provide useful insights into soil C dynamics, as they allow to study soil C pools of different ages. In this study we evaluated to what extent N enrichment affects soil C dynamics in experiments that applied C isotope tracers. Methods: Using meta-analysis, we synthesized data from 35 published papers. We made a distinction between “new C” and “old C” stocks, i.e., soil C derived from plant C input since the start of the isotopic enrichment, or unlabeled, pre-existing soil C. Results: Averaged across studies, N addition increased new soil C stocks (+30.3%), total soil C stocks (+6.1%) and soil C input proxies (+30.7%). Although N addition had no overall, average, effect on old soil C stocks and old soil C respiration, old soil C stocks increased with the amount of N added and respiration of old soil C declined. Nitrogen-induced effects on new soil C and soil C input both decreased with the amount of extraneous N added in control treatments. Conclusion: Although our findings require additional confirmation from long-term field experiments, our analysis provides isotopic evidence that N addition stimulates soil C storage both by increasing soil C input and (at high N rates) by decreasing decomposition of old soil C. Furthermore, we demonstrate that the widely reported saturating response of plant growth to N enrichment also applies to new soil C storage.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Using synthetic infrared spectra derived from n/k optical constants for standoff detection of chemical deposits

We report results from a recent field experiment to test the validity of using physics-based synthetic infrared spectra to serve as endmembers in a spectral database targeted at chemical deposits. Specifically, the optical constants n and k, (the real and imaginary part of the refractive index) were used to first model infrared reflectance spectra for different thicknesses of chemical layers (e.g. acetaminophen, methylphosphonic acid – MPA, etc.) on various conducting and insulating substrates such as aluminum, wood, and glass. In the experimental portion of the research, thin films of the solid and liquid analytes were deposited onto such substrates to form micron-thick layers of the analytes at different thicknesses: Standoff data from an imaging instrument were then recorded and analyzed to not only identify the different analytes, but also quantify the layer/deposit thickness. To gauge success, the detection results using the synthetic data were compared to the results from hemispherical reflectance (HRF) spectra that were collected for the same sample planchets measured in the field via standoff methods. Preliminary results indicate good agreement between the synthetic reference data as compared to the lab-measured HRF data in terms of their ability to quantitatively reduce longwave infrared data. Specifically, modeled IR spectra for acetaminophen on an aluminum planchet at various thicknesses (1, 2, 5, 10, 15, and 20 µm) were synthesized and compared with standoff field reflectance data as well as HRF laboratory reflectance spectra for two samples: a 5.2 µm- and 12.8 µm-thick layer of acetaminophen on aluminum. Using a first-order approximation, analysis of the field data estimates the thicknesses of the samples to be 2 and 10 µm for the two samples, respectively, while the HRF laboratory data yields thickness estimates of between 5-10 µm and 10 µm, respectively. Both yield reasonable estimates, with the uncertainty most likely due to factors yet to be accounted for in the synthetic spectra such as light scattering.

complex index of refraction, optical constants, hy↗
DOE OSTI2021

Soil organic carbon cycling in response to simulated soil moisture variation under field conditions

The combination of extended dry periods and high intensity rainfall, common in the southeastern US, leads to greater variability in soil moisture and consequently increases uncertainty to microbial processes pertinent to soil carbon (C) mineralization. However, field-based findings on soil moisture sensitivity to soil C cycling are very limited. Therefore, a field experiment was conducted in 2018 and 2019 on a soybean (Glycine max L.) cropland in the southeastern US with three soil moisture treatments: drought (simulated using rainout-shelter from June to October in each year), rainfed (natural precipitation), and irrigated (irrigation and precipitation). Soil respiration was measured weekly from May to November in both years. Soil samples were collected multiple times each year from 0–5, 5–15, and 15–30 cm depths to determine microbial biomass C (MBC), extractable organic C (EOC), hydrolytic enzyme activities, and fungal abundance. The cumulative respiration under drought compared to other treatments was lower by 32% to 33% in 2018 and 38% to 45% in 2019. Increased MBC, EOC, and fungal abundance were observed under drought than other treatments. Specific enzyme activity indicated fewer metabolically active microbes under drought treatment compared to rainfed and irrigated treatments. Also, maintenance of enzyme pool was observed under drought condition. These results provide critical insights on microbial metabolism in response to soil moisture variation and how that influences different pools of soil C under field conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Phenome‐to‐genome insights for evaluating root system architecture in field studies of maize

Abstract Understanding the genetic basis of root system architecture (RSA) in crops requires innovative approaches that enable both high‐throughput and precise phenotyping in field conditions. In this study, we evaluated multiple phenotyping and analytical frameworks for quantifying RSA in mature, field‐grown maize in three field experiments. We used forward and reverse genetic approaches to evaluate >1700 maize root crowns, including a diversity panel, a biparental mapping population, and maize mutant and wild‐type alleles at two known RSA genes,DEEPER ROOTING 1(DRO1) andRootless1(Rt1). We show the utility of increasing the dimensionality of traditional two‐dimensional (2D) techniques, referred to as the “2D multi‐view” method, to improve the capture of whole root system information for mapping genetic variation influencing RSA. Comparison of univariate and multivariate genome‐wide association study (GWAS) approaches revealed that multivariate traits were effective at dissecting complex RSA phenotypes and identifying pleiotropic quantitative trait loci (QTLs). Overall, three‐dimensional (3D) root models generated from X‐ray computed tomography and digital phenotyping captured a larger proportion of RSA trait variations compared to other methods of root phenotyping, as evidenced by both genome‐wide and single‐gene analyses. Among the individual root traits, root pulling force emerged as a highly heritable estimate of RSA that identified the largest number of shared QTLs with 3D phenotypes. Our study shows that integrating complementary phenotyping technologies helps to provide a more comprehensive understanding of the genetic architecture of RSA in field‐grown maize.

Genetics & Heredity↗
DOE OSTI2023

Extrapolation Domains for Aggregating Environmental Outcomes from Local to Regional Levels

Billions of dollars are invested every year to run field experiments to quantify the response of crops to new technologies and associated environmental outcomes. Given the diversity of environments where crop production occurs, conducting these research studies without a robust framework for research site selection and upscaling results to larger spatial scales is inefficient. In this project, researchers from the University of Nebraska-Lincoln used their unique Technology Extrapolation Domains framework (TED) as a tool to guide the selection of experimental sites and as basis for aggregating and validating environmental outcomes from local to regional levels. In the present project, we first used the TED framework to evaluate the current distribution and area coverage of the current SMARTFARM sites. The purpose was to showcase how it is possible to use the TED framework to guide site selection and extrapolate results over space. Additionally, the original TED framework was expanded to account for other factors influencing environmental outcomes by inclusion of three additional variables: soil organic matter, soil texture, and topographic wetness index. The resulting expanded framework (TED-E) was validated using nitrogen (N) losses from corn in the United States as a case study. To do so, we used N balance as a proxy to N losses and we evaluated the capacity of the framework to explain variation in N balance across fields and across countries. We found that the TED-E has substantially higher predictive power than the original TED framework to explain spatial variation in N balance. However, improvements in predictive power with the TED-E tool come at the expense of a higher number of TEDs needed to achieve a given crop area coverage compared with the original TED framework. We conclude that the new TED-E framework can help aggregate and extrapolate environmental outcomes from research sites to regional levels and improve the visualization of their spatial patterns across the United States. An online version of the framework is available at: https://www.toolted.org/

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Alterations in soil pH emerge as a key driver of the impact of global change on soil microbial nitrogen cycling: Evidence from a global meta-analysis

Soil nitrogen (N) cycling is critical to the productivity of terrestrial ecosystems. However, the impact of global change factors (GCFs) on the microbial mediators of N cycling pathways has yet to be synthesized, and it also remains unclear whether the response of the abundance of N-cycling genes can predict changes in their corresponding processes. We synthesized 8322 paired observations of soil microorganisms related to N cycling from field experiments in which GCFs (climate change and nutrient addition) were manipulated. We found that the abundance of soil microbes and most N-cycling genes were resistant to elevated CO 2 , experimental warming and water addition/reduction; however, N addition and the combination of N addition with other GCFs significantly increased the abundance of ammonia oxidizer bacteria (amoA-AOB). The results indicated that in steady-state (natural) conditions, the main factors driving the global abundance of soil bacteria, archaea and N-cycling genes varied in terms of the contributions of climatic and edaphic factors. However, upon manipulation of GCFs, the induced change in soil pH was the most essential factor associated with changes in the abundance of soil microbes and N-cycling genes. Notably, the changes in ammonia-oxidizing archaea (amoA-AOA) and amoA-AOB genes, in addition to genes involved in denitrification (nirS and nirK), were significantly correlated with the rates of their corresponding processes, but GCF-induced shifts in the potential nitrification rate (PNR) were explained well by changes in the abundance of the amoA-AOB gene under GCFs. In conclusion, our study highlights how ongoing GCFs impact the abundance of soil microbes and N-cycling genes, which might have a profound impact on terrestrial N cycling. Our field-based results provide new insights into the drivers of the abundance of soil microbes and N-cycling genes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Evaluation of subsurface transport processes of delayed gas signatures applicable to underground nuclear explosions

Radioactive gas signatures from underground nuclear explosions (UNEs) result from gas-migration processes occurring in the subsurface. The processes considered in this study either drive or retard upward migration of gases from the detonation cavity. The relative importance of these processes is evaluated by simulating subsurface transport in a dual-permeability medium for the multi-tracer Noble Gas Migration Experiment (NGME) originally intended to study some aspects of transport from a UNE. For this experiment, relevant driving processes include weak two-phase convection driven by the geothermal gradient, over pressuring of the detonation cavity, and barometric pumping while gas sorption, dissolution, radioactive decay, and usually diffusion represent retarding processes. From deterministic simulations we found that over-pressuring of the post-detonation chimney coupled with barometric pumping produced a synergistic effect amplifying the tracer-gas reaching the surface. Bounding simulations indicated that the sorption and dissolution of gases, tending to retard transport, were much smaller than anticipated by earlier laboratory studies. The NGME observations themselves show that differences in gas diffusivity have a larger effect on influencing upward transport than do the combined effects of tracer-gas sorption and dissolution, which is consistent with a Sobol’ sensitivity analysis. Both deterministic simulations and those considering parametric uncertainties of transport-related properties predict that the excess in concentration of SF 6 compared to 127 Xe as might be captured in small volumetric samples should be much smaller than the order-of-magnitude contrast found in the large-volume gas samples taken at the site. While extraction of large-volume subsurface gas samples is shown to be capable of distorting in situ gas compositions, the highly variable injection rate of SF 6 into the detonation cavity relative to that of 127 Xe at the start of the field experiment is the most likely explanation for the large difference in observed concentrations.

58 GEOSCIENCES↗
DOE OSTI2026

Measurements of TRACER pre-convective conditions and mesoscale circulations using small unmanned aircraft systems (sUAS)

Improved comprehension of the physical processes governing convective cloud formation and lifecycle are of critical importance for understanding and predicting future climate states. The influence of these clouds on the planetary energy budget, including on precipitation, is significant. Things are particularly complex in coastal regimes, where gradients in aerosol particle properties, localized circulations such as sea breezes, and large population centers are found. To date, numerical models struggle to accurately represent these critical clouds and are therefore challenged to provide a realistic view on the planetary energy budget. Through the proposed research, we deployed two uncrewed aircraft systems (UAS) equipped with a variety of instruments alongside sensors deployed by the US Department of Energy Atmospheric Radiation Measurement (ARM) program for the TRACER (Tracking Aerosol Convection Interactions Experiment) field campaign. The two small UAS platforms consisted of a CU RAAVEN fixed-wing airplane and an OU CopterSonde system, with the copter collecting frequent vertical profiles of thermodynamic and kinematic variables such as temperature, pressure, wind and humidity. At the same time, the fixed-wing captured horizontal gradients of these quantities and aerosol size distribution. These systems were deployed south of the Houston metro area, in an area that is impacted by the Gulf of Mexico sea breeze on a daily basis. These observations offer enhanced and complementary perspectives to those provided by the DOE ARM Mobile Facility (AMF) which is was deployed in southeast Houston, and an ancillary site in a more rural location west of the urban Houston area. Quality-controlled versions of the UAS data were collected and posted on the DOE ARM data archive after the conclusion of the campaign where they are accessible by the research community and general public. The UAS perspective offers revolutionary insight into key spatial and temporal effects that have not been evaluated previously.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Exploring the impacts of unprecedented climate extremes on forest ecosystems: hypotheses to guide modeling and experimental studies

Abstract. Climatic extreme events are expected to occur more frequently in the future, increasing the likelihood of unprecedented climate extremes (UCEs) or record-breaking events. UCEs, such as extreme heatwaves and droughts, substantially affect ecosystem stability and carbon cycling by increasing plant mortality and delaying ecosystem recovery. Quantitative knowledge of such effects is limited due to the paucity of experiments focusing on extreme climatic events beyond the range of historical experience. Here, we present a road map of how dynamic vegetation demographic models (VDMs) can be used to investigate hypotheses surrounding ecosystem responses to one type of UCE: unprecedented droughts. As a result of nonlinear ecosystem responses to UCEs that are qualitatively different from responses to milder extremes, we consider both biomass loss and recovery rates over time by reporting a time-integrated carbon loss as a result of UCE, relative to the absence of drought. Additionally, we explore how unprecedented droughts in combination with increasing atmospheric CO2 and/or temperature may affect ecosystem stability and carbon cycling. We explored these questions using simulations of pre-drought and post-drought conditions at well-studied forest sites using well-tested models (ED2 and LPJ-GUESS). The severity and patterns of biomass losses differed substantially between models. For example, biomass loss could be sensitive to either drought duration or drought intensity depending on the model approach. This is due to the models having different, but also plausible, representations of processes and interactions, highlighting the complicated variability of UCE impacts that still need to be narrowed down in models. Elevated atmospheric CO2 concentrations (eCO2) alone did not completely buffer the ecosystems from carbon losses during UCEs in the majority of our simulations. Our findings highlight the consequences of differences in process formulations and uncertainties in models, most notably related to availability in plant carbohydrate storage and the diversity of plant hydraulic schemes, in projecting potential ecosystem responses to UCEs. We provide a summary of the current state and role of many model processes that give way to different underlying hypotheses of plant responses to UCEs, reflecting knowledge gaps which in future studies could be tested with targeted field experiments and an iterative modeling–experimental conceptual framework.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Root-associated bacterial communities and root metabolite composition are linked to nitrogen use efficiency in sorghum

ABSTRACT The development of cereal crops with high nitrogen use efficiency (NUE) is a priority for worldwide agriculture. In addition to conventional plant breeding and genetic engineering, the use of the plant microbiome offers another approach to improving crop NUE. To gain insight into the bacterial communities associated with sorghum lines that differ in NUE, a field experiment was designed comparing 24 diverse Sorghum bicolor lines under sufficient and deficient nitrogen (N). Amplicon sequencing and untargeted gas chromatography–mass spectrometry were used to characterize the bacterial communities and the root metabolome associated with sorghum genotypes varying in sensitivity to low N. We demonstrated that N stress and sorghum type (energy, sweet, and grain sorghum) significantly impacted the root-associated bacterial communities and root metabolite composition of sorghum. We found a positive correlation between sorghum NUE and bacterial richness and diversity in the rhizosphere. The greater alpha diversity in high NUE lines was associated with the decreased abundance of a dominant bacterial taxon, Pseudomonas . Multiple strong correlations were detected between root metabolites and rhizosphere bacterial communities in response to low N stress. This indicates that the shift in the sorghum microbiome due to low N is associated with the root metabolites of the host plant. Taken together, our findings suggest that host genetic regulation of root metabolites plays a role in defining the root-associated microbiome of sorghum genotypes differing in NUE and tolerance to low N stress. IMPORTANCE The development of crops that are more nitrogen use-efficient (NUE) is critical for the future of the enhanced sustainability of agriculture worldwide. This objective has been pursued mainly through plant breeding and plant molecular engineering, but these approaches have had only limited success. Therefore, a different strategy that leverages soil microbes needs to be fully explored because it is known that soil microbes improve plant growth through multiple mechanisms. To design approaches that use the soil microbiome to increase NUE, it will first be essential to understand the relationship among soil microbes, root metabolites, and crop productivity. Using this approach, we demonstrated that certain key metabolites and specific microbes are associated with high and low sorghum NUE in a field study. This important information provides a new path forward for developing crop genotypes that have increased NUE through the positive contribution of soil microbes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

All the light we cannot see: Climate manipulations leave short and long‐term imprints in spectral reflectance of trees

Abstract Anthropogenic climate change, particularly changes in temperature and precipitation, affects plants in multiple ways. Because plants respond dynamically to stress and acclimate to changes in growing conditions, diagnosing quantitative plant‐environment relationships is a major challenge. One approach to this problem is to quantify leaf responses using spectral reflectance, which provides rapid, inexpensive, and nondestructive measurements that capture a wealth of information about genotype as well as phenotypic responses to the environment. However, it is unclear how warming and drought affect spectra. To address this gap, we used an open‐air field experiment that manipulates temperature and rainfall in 36 plots at two sites in the boreal‐temperate ecotone of northern Minnesota, USA. We collected leaf spectral reflectance (400–2400 nm) at the peak of the growing season for three consecutive years on juveniles (two to six years old) of five tree species planted within the experiment. We hypothesized that these mid‐season measurements of spectral reflectance capture a snapshot of the leaf phenotype encompassing a suite of physiological, structural, and biochemical responses to both long‐ and short‐time scale environmental conditions. We show that the imprint of environmental conditions experienced by plants hours to weeks before spectral measurements is linked to regions in the spectrum associated with stress, namely the water absorption regions of the near‐infrared and short‐wave infrared. In contrast, the environmental conditions plants experience during leaf development leave lasting imprints on the spectral profiles of leaves, attributable to leaf structure and chemistry (e.g., pigment content and associated ratios). Our analyses show that after accounting for baseline species spectral differences, spectral responses to the environment do not differ among the species. This suggests that building a general framework for understanding forest responses to climate change through spectral metrics may be possible, likely having broader implications if the common responses among species detected here represent a widespread phenomenon. Consequently, these results demonstrate that examining the entire spectrum of leaf reflectance for environmental imprints in contrast to single features (e.g., indices and traits) improves inferences about plant‐environment relationships, which is particularly important in times of unprecedented climate change.

Stefanski, Artur [Department of Forest Resources U↗
DOE OSTI2022

Genetic variation in nitrogen‐use efficiency and its associated traits in dryland winter wheat ( Triticum aestivum L.) cultivars released from the 1940s to the 2010s in Shaanxi Province, China

Abstract BACKGROUND Improving the nitrogen‐use efficiency (NUE) of wheat can help mitigate the problems of poor soil fertility under dryland conditions. We conducted field experiments using three nitrogen (N) fertilization levels (0, 120, and 180 kg ha −1 ) applied to eight dryland wheat cultivars to assess NUE and its associated traits. RESULTS The grain yield significantly increased with the improvement in variety, mainly as a result of a substantial increase in 1000‐grain weight and harvest index. Modern wheat varieties have stabilized at an optimal plant height and exhibited improved performance in terms of NUE, partial N productivity, N harvest index, and grain protein content compared to older varieties. The NUE of wheat gradually increased with variety replacement. The net photosynthesis rate of the flag leaves in the filling stage improved with the year of cultivar release; Increasing soil–plant analysis development (SPAD) values of flag leaves in the flowering and filling stages were observed over time, with the flag leaves of modern varieties showing a high chlorophyll content in the filling stage. Additionally, the principal component analysis showed that the SPAD value, grain number per unit area, transpiration rate, leaf area, and grain protein content positively contributed to the clustering of the N180 and modern cultivars (from the 2000s to 2010s). CONCLUSION Overall, high levels of N application did not significantly improve the NUE of wheat. However, modern wheat varieties can optimize N distribution, increase flag leaf photosynthetic capacity, and improve photosynthesis ability, thus enhancing NUE to achieve high yields under a suitable level of N supply. © 2022 Society of Chemical Industry.

Lian, Huida↗
DOE OSTI2023

Registration of ‘Cedar Creek’ switchgrass

‘Cedar Creek’ (Reg. no. CV-290, PI 700113) switchgrass (Panicum virgatum L.) was selected for increased winter survivorship for three cycles, using surviving plants from ‘Kanlow’. The first two cycles were conducted at multiple locations in Wisconsin, and the third cycle was conducted at the Cedar Creek Ecosystem Science Reserve, East Bethel, MN. All seed production and increases were conducted by either Illinois State University or the University of Illinois. Field evaluations of the third-cycle population were conducted at five locations in Wisconsin between 2017 and 2021, located within USDA hardiness zones 3–5. Field experiments were planted in both 2016 and 2017. Averaged over the five locations and all trial years, Cedar Creek had 91% ground cover, compared with 96% for Cave-in-Rock, 95% for Shawnee, and 91% for Liberty. Biomass yield of Cedar Creek averaged 12.17 Mg ha –1 , which was 20% higher than Liberty, 30% higher than Cave-in-Rock, 31% higher than Shawnee, and 520% higher than Kanlow. Cedar Creek is a high-biomass lowland-type of switchgrass and is the first lowland-type adapted to USDA hardiness zones 3–5. Cedar Creek was released to the public by USDA-ARS in 2021.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Registration of ‘Independence’ switchgrass

Switchgrass (Panicum virgatum L.), a valuable forage and bioenergy crop, is established more easily than other native perennial warm-season grasses, but its establishment is still slower than that of annual crops. Vigorous switchgrass establishment is crucial for achieving its full potential yield and for effectively competing with weeds for water and nutrient availability. To satisfy this demand, ‘Independence’ (Reg. no. CV-295, PI 704577) switchgrass was developed at the University of Illinois at Urbana-Champaign. Independence was selected for establishment vigor, winter survivorship, and high biomass yield for two cycles from ‘Kanlow’. Here, it is characterized by rapid establishment, robust seedling growth, and the capacity to achieve peak production by the second year. Independence is well adapted to USDA hardiness zones 5b–7b. In field experiments conducted from 2016 to 2017, averaged over seven locations and all years, Independence annually yielded 13 Mg ha –1 of biomass, outperforming ‘Cave-in-Rock’ by 31%, ‘Liberty’ by 15%, ‘Shawnee’ by 42%, ‘Summer’ by 81%, and ‘Sunburst’ by 129%. In wet marginal sites in Illinois from 2020 to 2023, Independence exhibited an average biomass yield of 12 Mg ha –1 , outperforming Shawnee by 31%, Liberty by 27%, and Kanlow by 19%, indicating its potential use on less productive land for annual crops. Independence was publicly released by the University of Illinois at Urbana-Champaign in October 2021.

09 BIOMASS FUELS↗
DOE OSTI2024

Data driven discovery and quantification of hyperspectral leaf reflectance phenotypes across a maize diversity panel

Abstract Estimates of plant traits derived from hyperspectral reflectance data have the potential to efficiently substitute for traits, which are time or labor intensive to manually score. Typical workflows for estimating plant traits from hyperspectral reflectance data employ supervised classification models that can require substantial ground truth datasets for training. We explore the potential of an unsupervised approach, autoencoders, to extract meaningful traits from plant hyperspectral reflectance data using measurements of the reflectance of 2151 individual wavelengths of light from the leaves of maize ( Zea mays ) plants harvested from 1658 field plots in a replicated field trial. A subset of autoencoder‐derived variables exhibited significant repeatability, indicating that a substantial proportion of the total variance in these variables was explained by difference between maize genotypes, while other autoencoder variables appear to capture variation resulting from changes in leaf reflectance between different batches of data collection. Several of the repeatable latent variables were significantly correlated with other traits scored from the same maize field experiment, including one autoencoder‐derived latent variable (LV8) that predicted plant chlorophyll content modestly better than a supervised model trained on the same data. In at least one case, genome‐wide association study hits for variation in autoencoder‐derived variables were proximal to genes with known or plausible links to leaf phenotypes expected to alter hyperspectral reflectance. In aggregate, these results suggest that an unsupervised, autoencoder‐based approach can identify meaningful and genetically controlled variation in high‐dimensional, high‐throughput phenotyping data and link identified variables back to known plant traits of interest.

Tross, Michael C.↗
DOE OSTI2023

Characterization and response of three TNT equivalent materials in subsurface explosions

Energetic compositions utilized for inducing seismic responses are often referred to in terms of their TNT equivalent, a metric which is often misused because observations of interest are not often understood with respect to explosive characteristics. Here, in this investigation, we characterize three energetic compositions used to elicit seismic responses in a highly instrumented testbed to further our understanding of subsurface TNT equivalence. Three different energetic sources are prepared and studied for their fidelity to thermochemically predicted detonation behavior. We present effects of subsurface detonation on subsurface rock and seismic emission as a function of energetic source material within the testbed. Field experiments were conducted using a single thermochemical yield of 5 kg using diverse sources consisting of nitromethane, ammonal, and PBXN‐5 (an HMX based plastic bonded explosive) mixtures at the Energetic Materials Research and Testing Center in Socorro, New Mexico. Relative performance of energy density‐related detonation parameters, such as detonation velocity and pressure, affect the observed response in the subsurface. Most notable, equal thermochemical yields described in terms of TNT equivalence do not correlate to equal thermochemical effects in the subsurface.

Blue Canyon Dome↗