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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

AmeriFlux FLUXNET-1F US-UiA University of Illinois Switchgrass

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-UiA University of Illinois Switchgrass. This is the FLUXNET version of the carbon flux data for the site US-UiA University of Illinois Switchgrass produced by applying the standard ONEFlux (1F) software. Site Description - Field was treated with Potash, lime and diammonium phosphate before planting. Herbicide application included 2,4-D for 2008, 2009. 56 kg/ha nitrogen applied in 2010, 2011, 2012, 2013, 2014, 2016. Measurements were suspended on June 14, 2016 and resumed on May 28, 2024.

Bernacchi, Carl↗
DOE OSTI2025

Draft genome of the switchgrass head smut pathogen Tilletia maclaganii V.2

The head smut (Tilletia maclaganii) is a significant pathogen of the bioenergy crop switchgrass. T. maclaganii typically is more prevalent in older stands of switchgrass and can contribute to significant biomass loss. Here, we outline the methods for the sequencing, assembly, and annotation of the first reference genome for Tilletia maclaganii.

Benucci, Gian Maria Niccolò [GLBRC - Michigan Stat↗
DOE OSTI2011

Pollen Viability and Longevity of Switchgrass ( Panicum virgatum L.)

ABSTRACT Pollen is essential for seed production and serves as the primary means of gene flow in outcrossing species like switchgrass ( Panicum virgatum L.). There is a lack of information on basic pollen biology in switchgrass. This study investigated pollen viability, pollen longevity, and pollen size using different materials, including the tetraploid cultivar Alamo, the octoploid cultivar Cave‐in‐Rock, and transgenic Alamo plants. Pollen grains were collected from field‐grown Alamo and Cave‐in‐Rock plants, and greenhouse‐grown transgenics. Pollen size was in the range of 42.5 to 54.0 μm; no significant difference was observed in average pollen size between transgenic and control plants. Increasing temperature and ultraviolet‐B irradiation negatively affected pollen viability and longevity, while relative humidity had only limited impact. Weather conditions had a large impact on pollen longevity. Under sunny atmospheric conditions, pollen longevity of both cultivars decreased rapidly, with a half‐life of <4.9 min and a complete loss of viability in 20 min. Under cloudy atmospheric conditions, the half‐life of pollen was more than fivefold longer than under sunny conditions, and it took approximately 150 min to lose viability completely. No difference in pollen viability and longevity was found between transgenic and nontransgenic control plants.

Ge, Yaxin↗
DOE OSTI2022

Sustainability Trait Modeling of Field-Grown Switchgrass (Panicum virgatum) Using UAV-Based Imagery

Unmanned aerial vehicles (UAVs) provide an intermediate scale of spatial and spectral data collection that yields increased accuracy and consistency in data collection for morphological and physiological traits than satellites and expanded flexibility and high-throughput compared to ground-based data collection. In this project, we used UAV-based multispectral imagery collected from MicaSense RedEdge-M on a DJI Matrice 600 Pro for automated phenotyping of field-grown switchgrass (Panicum virgatum), a leading bioenergy feedstock. The raw images were processed with Pix4D Mapper to create the reflectance data, and vegetation indices were calculated from a UAV-based multispectral camera. Statistical models were developed for rust disease caused by Puccinia novopanici, leaf chlorophyll, nitrogen, and lignin contents. For the first time, UAV remote sensing technology was used to explore the potential for multiple traits associated with sustainable production of switchgrass. One statistical model was developed for each individual trait based on the statistical correlation between vegetation indices and the corresponding trait.

CBI↗
DOE OSTI2026

Root of the matter-Impacts of harvest frequency on soil C and nutrients in switchgrass

We evaluated how harvest frequency affected plant C allocation and soil-water nutrient concentrations in a switchgrass (Panicum virgatumL.) system on the Eastern Shore of Maryland, U.S.A. Switchgrass established in 2023 was harvested once (1Cut), twice (2Cut), or three times (3Cut) during the 2024 growing season to represent potential feedstock-management regimes for anaerobic digestion. Aboveground biomass was measured at each harvest, and root biomass distribution, root C stocks, and soil properties were assessed to 60 cm after the growing season. During 2025, rainfall-synchronized soil water collected with tension lysimeters was analyzed for dissolved inorganic nitrogen (DIN) and inorganic phosphate (Pi) concentrations.

09 BIOMASS FUELS↗
DOE OSTI2025

Estimating Switchgrass Biomass Yield and Lignocellulose Composition from UAV-Based Indices

Innovative methods for estimating commercial-scale switchgrass yields and feedstock quality are essential to optimize harvest logistics and biorefinery efficiency for sustainable aviation fuel production. This study utilized vegetation indices (VIs) derived from multispectral images to predict biomass yield and lignocellulose concentrations of advanced bioenergy-type switchgrass cultivars (“Liberty” and “Independence”) under two N rates (28 and 56 kg N ha –1 ). Field-scale plots were arranged in a randomized complete block design (RCBD) and replicated three times at Urbana, IL. Multispectral images captured during the 2021–2023 growing seasons were used to extract VIs. The results show that linear and exponential models outperformed partial least square and random forest models, with mid-August imagery providing the best predictions for biomass, cellulose, and hemicellulose. The green normalized difference vegetation index (GNDVI) was the best univariate predictor for biomass yield (R 2 = 0.86), while a multivariate combination of the GNDVI and normalized difference red-edge index (NDRE) enhanced prediction accuracy (R 2 = 0.88). Cellulose was best predicted using the NDRE (R 2 = 0.53), whereas hemicellulose prediction was most effective with a multivariate model combining the GNDVI, NDRE, NDVI, and green ratio vegetation index (GRVI) (R 2 = 0.44). These findings demonstrate the potential of UAV-based VIs for the in-season estimation of biomass yield and cellulose concentration.

09 BIOMASS FUELS↗
DOE OSTI2015

High-Density Single Nucleotide Polymorphism Linkage Maps of Lowland Switchgrass using Genotyping-by-Sequencing

Switchgrass (Panicum virgatum L.) is a warm-season perennial grass with promising potential as a bioenergy crop in the United States. However, the lack of genomic resources has slowed the development of plant lines with optimal characteristics for sustainable feedstock production. We generated high-density single nucleotide polymorphism (SNP) linkage maps using a reduced-representation sequencing approach by genotyping 231 F 1 progeny of a cross between two parents of lowland ecotype from the cultivars Kanlow and Alamo. Over 350 million reads were generated and aligned, which enabled identification and ordering of 4611 high-quality SNPs. The total lengths of the resulting framework maps were 1770 cM for the Kanlow parent and 2059 cM for the Alamo parent. These maps show collinearity with maps generated with polymerase chain reaction (PCR)-based simple-sequence repeat (SSR) markers, and new SNP markers were identified in previously unpopulated regions of the genome. Transmission segregation distortion affected all linkage groups (LGs) to differing degrees, and ordering of distorted markers highlighted several regions of unequal inheritance. Framework maps were adversely affected by the addition of distorted markers with varying severity, but distorted maps were of higher marker density and provided additional information for analysis. Alignment of these linkage maps with a draft version of the switchgrass genome assembly demonstrated high levels of collinearity and provides greater confidence in the validity of both resources. This methodology has proven to be a rapid and cost-effective way to generate high-quality linkage maps of an outcrossing species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Candidate Variants for Additive and Interactive Effects on Bioenergy Traits in Switchgrass ( Panicum virgatum L.) Identified by Genome‐Wide Association Analyses

Switchgrass ( Panicum virgatum L.) is a promising herbaceous energy crop, but further gains in biomass yield and quality must be achieved to enable a viable bioenergy industry. Developing DNA markers can contribute to such progress, but depiction of genetic bases should be reliable, involving simple additive marker effects and also interactions with genetic backgrounds (e.g., ecotypes) or synergies with other markers. We analyzed plant height, C content, N content, and mineral concentration in a diverse panel consisting of 512 genotypes of upland and lowland ecotypes. We performed association analyses based on exome capture sequencing and tested 439,170 markers for marginal effects, 83,290 markers for marker × ecotype interactions, and up to 311,445 marker pairs for pairwise interactions. Analyses of pairwise interactions focused on subsets of marker pairs preselected on the basis of marginal marker effects, gene ontology annotation, and pairwise marker associations. Our tests identified 12 significant effects. Homology and gene expression information corroborated seven effects and indicated plausible causal pathways: flowering time and lignin synthesis for plant height; plant growth and senescence for C content and mineral concentration. Four pairwise interactions were detected, including three interactions preselected on the basis of pairwise marker correlations. Furthermore, a marker × ecotype interaction and a pairwise interaction were confirmed in an independent switchgrass panel. Our analyses identified reliable candidate variants for important bioenergy traits. Moreover, they exemplified the importance of interactive effects for depicting genetic bases and illustrated the usefulness of preselecting marker pairs for identifying pairwise marker interactions in association studies.

Ramstein, Guillaume P.↗
DOE OSTI2013

Metagenomes of tropical soil-derived anaerobic switchgrass-adapted consortia with and without iron

Tropical forest soils decompose litter rapidly with frequent episodes of anoxia, making it likely that bacteria using alternate terminal electron acceptors (TEAs) such as iron play a large role in supporting decomposition under these conditions. The prevalence of many types of metabolism in litter deconstruction makes these soils useful templates for improving biofuel production. To investigate how iron availability affects decomposition, we cultivated feedstock-adapted consortia (FACs) derived from iron-rich tropical forest soils accustomed to experiencing frequent episodes of anaerobic conditions and frequently fluctuating redox. One consortium was propagated under fermenting conditions, with switchgrass as the sole carbon source in minimal media (SG only FACs), and the other consortium was treated the same way but received poorly crystalline iron as an additional terminal electron acceptor (SG + Fe FACs). We sequenced the metagenomes of both consortia to a depth of about 150 Mb each, resulting in a coverage of 26× for the more diverse SG + Fe FACs, and 81× for the relatively less diverse SG only FACs. Both consortia were able to quickly grow on switchgrass, and the iron-amended consortium exhibited significantly higher microbial diversity than the unamended consortium. We found evidence of higher stress in the unamended FACs and increased sugar transport and utilization in the ironamended FACs. This work provides metagenomic evidence that supplementation of alternative TEAs may improve feedstock deconstruction in biofuel production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Data from: Associative nitrogen fixation (ANF) in switchgrass (Panicum virgatum) across a nitrogen input gradient

Associative N fixation (ANF), the process by which dinitrogen gas is converted to ammonia by bacteria in casual association with plants, has not been well-studied in temperate ecosystems. We examined the ANF potential of switchgrass (Panicum virgatum L.), a North American prairie grass whose productivity is often unresponsive to N fertilizer addition, via separate short-term 15N2 incubations of rhizosphere soils and excised roots four times during the growing season. Measurements occurred along N fertilization gradients at two sites with contrasting soil fertility (Wisconsin, USA Mollisols and Michigan, USA Alfisols). In general, we found that ANF potentials declined with long-term N addition, corresponding with increased soil N availability. Although we hypothesized that ANF potential would track plant N demand through the growing season, the highest root fixation rates occurred after plants senesced, suggesting that root diazotrophs exploit carbon (C) released during senescence, as C is translocated from aboveground tissues to roots for wintertime storage. Measured ANF potentials, coupled with mass balance calculations, suggest that ANF appears to be an important source of N to unfertilized switchgrass, and, by extension, to temperate grasslands in general.

09 BIOMASS FUELS↗
DOE OSTI2016

Data from: Diversity and population structure of northern switchgrass as revealed through exome capture sequencing

Switchgrass (Panicum virgatum L.) is a polyploid, perennial grass species that is native to North America, and is being developed as a future biofuels feedstock crop. Switchgrass is present primarily in two ecotypes: a northern upland ecotype composed of tetraploid and octoploid accessions, and a southern lowland ecotype composed of primarily tetraploid accessions. We employed high-coverage exome capture sequencing (~2.4 Tb) to genotype 537 individuals from 45 upland and 21 lowland populations. From these data, we identified ~27 million single nucleotide polymorphisms (SNPs), of which 1,590,653 high confidence SNPs were used in downstream analyses of diversity within and between the populations. From the 66 populations, we identified five primary population groups within the upland and lowland ecotypes, a result that was further supported through genetic distance analysis. We identified conserved, ecotype restricted non-synonymous SNPs that are predicted to impact protein function in genes that encode CONSTANS (CO) and EARLY HEADING DATE 1 (EHD1), key genes involved in flowering which may contribute to the phenotypic differences between the two ecotypes. We also identified, relative to the near-reference Kanlow population, 17,228 up-copy number variants (CNVs), 112,630 down-CNVs, and 14,430 presence/absence variants (PAV) impacting a total of 9,979 genes, including two upland-specific CNV-clusters. In total, 45,719 genes were impacted by a SNP, CNV, or a PAV across the panel providing a firm foundation to identify functional variation associated with phenotypic traits of interest for biofuel feedstock production.

09 BIOMASS FUELS↗
DOE OSTI2013

Global Simulation of Bioenergy Crop Productivity: Analytical Framework and Case Study for Switchgrass

A global energy crop productivity model that provides geospatially explicit quantitative details on biomass potential and factors affecting sustainability would be useful, but does not exist now. This study describes a modeling platform capable of meeting many challenges associated with global-scale agro-ecosystem modeling. We designed an analytical framework for bioenergy crops consisting of six major components: (i) standardized natural resources datasets, (ii) global field-trial data and crop management practices, (iii) simulation units and management scenarios, (iv) model calibration and validation, (v) high-performance computing (HPC) simulation, and (vi) simulation output processing and analysis. The HPC-Environmental Policy Integrated Climate (HPC-EPIC) model simulated a perennial bioenergy crop, switchgrass (Panicum virgatum L.), estimating feedstock production potentials and effects across the globe. This modeling platform can assess soil C sequestration, net greenhouse gas (GHG) emissions, nonpoint source pollution (e.g., nutrient and pesticide loss), and energy exchange with the atmosphere. It can be expanded to include additional bioenergy crops (e.g., miscanthus, energy cane, and agave) and food crops under different management scenarios. The platform and switchgrass field-trial dataset are available to support global analysis of biomass feedstock production potential and corresponding metrics of sustainability.

Kang, Shujiang↗
DOE OSTI2012

Switchgrass cultivar

A new cultivar of switchgrass `Cimarron` (SL93 2001-1) having increased biomass yield is provided. The switchgrass comprises all the morphological and physiological properties of the cultivar grown from a seed deposited under American Type Culture Collection (ATCC) No. PTA-10116. The invention also provides seeds, progeny, parts and methods of use of Cimarron, such as for the production of biofuels.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Global Simulation of Bioenergy Crop Productivity: Analytical framework and Case Study for Switchgrass

Contemporary global assessments of the deployment potential and sustainability aspects of biofuel crops lack quantitative details. This paper describes an analytical framework capable of meeting the challenges associated with global scale agro-ecosystem modeling. We designed a modeling platform for bioenergy crops, consisting of five major components: (i) standardized global natural resources and management data sets, (ii) global simulation unit and management scenarios, (iii) model calibration and validation, (iv) high-performance computing (HPC) modeling, and (v) simulation output processing and analysis. A case study with the HPC- Environmental Policy Integrated Climate model (HPC-EPIC) to simulate a perennial bioenergy crop, switchgrass (Panicum virgatum L.) and global biomass feedstock analysis on grassland demonstrates the application of this platform. The results illustrate biomass feedstock variability of switchgrass and provide insights on how the modeling platform can be expanded to better assess sustainable production criteria and other biomass crops. Feedstock potentials on global grasslands and within different countries are also shown. Future efforts involve developing databases of productivity, implementing global simulations for other bioenergy crops (e.g. miscanthus, energycane and agave), and assessing environmental impacts under various management regimes. We anticipated this platform will provide an exemplary tool and assessment data for international communities to conduct global analysis of biofuel biomass feedstocks and sustainability.

Nair, S. Surendran↗
DOE OSTI2020

Geographic variation in the genetic basis of resistance to leaf rust between locally adapted ecotypes of the biofuel crop switchgrass ( Panicum virgatum )

Local adaptation is an important process in plant evolution, which can be impacted by differential pathogen pressures along environmental gradients. However, the degree to which pathogen resistance loci vary in effect across space and time is incompletely described. As such, to understand how the genetic architecture of resistance varies across time and geographic space, we quantified rust ( Puccinia spp.) severity in switchgrass ( Panicum virgatum ) plantings at eight locations across the central USA for 3 yr and conducted quantitative trait locus (QTL) mapping for rust progression. We mapped several variable QTLs, but two large-effect QTLs which we have named Prr1 and Prr2 were consistently associated with rust severity in multiple sites and years, particularly in northern sites. By contrast, there were numerous small-effect QTLs at southern sites, indicating a genotype-by-environment interaction in rust resistance loci. Interestingly, Prr1 and Prr2 had a strong epistatic interaction, which also varied in the strength and direction of effect across space. Our results suggest that abiotic factors covarying with latitude interact with the genetic loci underlying plant resistance to control rust infection severity. Furthermore, our results indicate that segregating genetic variation in epistatically interacting loci may play a key role in determining response to infection across geographic space.

09 BIOMASS FUELS↗
DOE OSTI2022

Pilot-Scale Pelleting Tests on High-Moisture Pine, Switchgrass, and Their Blends: Impact on Pellet Physical Properties, Chemical Composition, and Heating Values

In this study, we evaluated the pelleting characteristics of southern yellow pine (SYP), switchgrass (SG), and their blends for thermochemical conversion processes, such as pyrolysis and gasification. Using a pilot-scale ring-die pellet mill, we specifically assessed the impact of blend moisture, length-to-diameter (L/D) ratio in the pellet die, and ratio of pine to SG on the physico-chemical properties of the resulting pellets. We found that an increase in pine content by 25–50% marginally affected the bulk density; however, it also led to an increase in calorific value by 7% and a decrease in ash content by 72%. A moisture content of 25% (wet basis) and an L/D ratio of 5 resulted in poor pellet durability at <90% and bulk density values of <500 kg/m 3 , but increasing the L/D ratio to 9 and lowering the moisture content to 20% (w.b.) improved the pellet durability to >90% and the bulk density to >500 kg/m 3 . Blends with ≥50% pine content resulted in lower energy consumption, while a lower L/D ratio resulted in higher pelleting energy. Based on these findings, we successfully demonstrated the high-moisture pelleting of 2.5 ton of pine top residues blended with SG at 60:40 and 50:50 ratios. The quality of the pellets was monitored off-line and at-line by near infrared (NIR) spectroscopy. Multivariate models constructed by combining the NIR data and the pelleting process variables could successfully predict the pine content (R 2 = 0.99), higher heating value (R 2 = 0.98), ash (R 2 = 0.95), durability (R 2 = 0.94), and bulk density (R 2 = 0.86) of the pellets. Thus, we established how blending and densification of SYP and SG biomass could improve feedstock specifications and that NIR spectroscopy can effectively monitor the pellet properties during the high-moisture pelleting process.

09 BIOMASS FUELS↗
DOE OSTI2019

Effect of solvent fractionation pretreatment on energy consumption of cellulose nanofabrication from switchgrass

Lignin-containing cellulose nanofibers (L-CNFs) with various lignin contents were produced by a grinding process from switchgrass, which were pretreated using organosolv fractionation. The effect of different fractionation conditions (temperature and time) and different number of grinder passes on the energy consumption and morphologies of L-CNFs were investigated. Results revealed that nanosized fibers were found in organosolv-fractionated samples before grinding. After several grinding passes, L-CNFs with a similar degree of fibrillation as commercial cellulose nanofibers (CNF) were obtained from the fractionated materials. It is beneficial to save energy consumption in the grinding process. The dimensions and dispersion of L-CNFs were significantly influenced by the lignin content in the L-CNFs. Longer and well-separated nanofibrils were observed from transmission electron microscopy and fluorescence microscopy with appropriate residual lignin (~ 13.7 ± 1.59%) in the L-CNFs compared to those of L-CNFs with either lower or higher lignin contents. Thus, microsized and nanosized lignin particles were successfully obtained in a single process, and they not only facilitated L-CNFs dispersion but also help to decrease the energy consumption during the grinding process.

09 BIOMASS FUELS↗