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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Natural deep eutectic solvents (NADES) assisted deconstruction of oilcane bagasse for high lipid and sugar recovery

In a novel approach, metabolically engineered sugarcane “Oilcane” has been investigated for fractionation of lipid and cellulose-rich pulp, using certain Natural deep eutectic solvents (NADES). The exploration of eco- friendly solvents are at the forefront of harnessing the biofuel potential of modern bioenergy crops. For this, six combinations of NADES were prepared using choline chloride (ChCl) as HBA and lactic acid (LA), oxalic acid (OA) and glycerol (Gly) as HBD and were further explored for pretreatment of oilcane bagasse in a molar ratio of 1:1 and 1:2. The impact of NADES ratio, biomass loading (10–50%), residence time (1–2 h), and temperature (90–140 °C) were evaluated for delignification, lipid content, sugar release after enzymatic hydrolysis. The finding demonstrated that under the optimal condition of ChCl: LA (1:2 molar ratio), 140 °C with 2 h retention time, the lipid content in the pre-treated substrate was increased to 2.5-fold (~8% w/w) and > 80% glucose yield was achieved after 72 h of hydrolysis of pre-treated bagasse. High solid loading (~50%) during pretreatment resulted in a similar glucose yield. Furthermore, recycling studies demonstrated that nearly 95 to 98% NADES could be recycled after each pretreatment for up to five consecutive cycles without any significant loss in chemical structure as confirmed by 1 H NMR and FT IR. FT IR and XRD analyses of native and pre-treated biomass were performed to visualize the morphological changes during NADES pretreatment and their impact on sugar yield. The findings of the study may be used to establish NADES-based biorefinery for the valorization of lipids, and carbohydrates for fuels and chemicals production.

09 BIOMASS FUELS↗
DOE OSTI2026

The Value of Reversible Carbon Storage in a Zero-Emissions World

Atmospheric carbon dioxide removal (CDR) is required to stabilize global temperature. CDR can be achieved via ecosystem-based approaches that are cost-effective but reversible (e.g., soil and forest management) or by more durable but expensive approaches (e.g., direct air capture coupled with geologic storage). Here, we examine trade-offs between these approaches, focusing on timing, climate impacts, and cost. We simulated reversible carbon accrual for a range of CDR contract structures using a general minimalist model of ecosystem carbon cycling, and parameterized it to simulate US agricultural soil management─specifically cover cropping─as a case study. We then quantified the resulting impact on atmospheric carbon and global temperature using a climate model emulator. We find that maintaining a patchwork of reversible CDR projects by replacing lapsed projects with new projects can reduce warming by 22–195 μ°C in 2100 and that the magnitude of this cooling effect depends on how effectively the patchwork is maintained. Long-term maintenance of reversible CDR projects requires institutional stability that cannot be guaranteed over multiple decades. Consequently, effective CDR ultimately requires replacing reversible projects with durable projects. To address this problem, we modeled the cost of replacing reversible agricultural soil CDR with geologic CDR. We found that using reversible CDR as a bridge to durable CDR is potentially more cost-effective as a global cooling strategy (0.20–0.81 billion USD per μ°C avoided) than perpetual maintenance of reversible CDR (0.32–1.31 billion USD per μ°C avoided) or an immediate transition to durable CDR (1.37–2.19 billion USD per μ°C avoided). However, we emphasize that institutional commitments to maintain reversible CDR projects cannot be guaranteed. Reliance on reversible CDR as a bridge to durable CDR therefore carries an unknown amount of risk and will only function if efforts to maintain reversible CDR are robust.

carbon capture and storage↗
DOE OSTI2021

Opportunities for Treatment and Reuse of Agricultural Drainage in the United States

Irrigation accounts for 42% of the total freshwater withdrawals in the United States. Climate change, the pressure of a growing population, degrading water quality, and increased competition from other sectors could constrain continuous supply to meet future agricultural water demand. This study presents an evaluation framework to assess the potential reuse of agricultural drainage water for crop irrigation. Using a regional approach, we review the current state of agricultural drainage treatment and reuse and the institutional, economic, and other barriers that can influence the reuse decision. In the 31 eastern states, agricultural drainage contains valuable nutrients that can be reused for irrigation with minimal treatment, while the 17 western states struggle with large volumes of saline drainage that can contain constituents of concern (e.g., selenium), preventing reuse without treatment. Using a new decision-support tool called WaterTAP3, a potential treatment train for saline agricultural drainage was analyzed to identify treatment challenges, research needs, and the potential implementation at a larger scale. As demonstrated by our case study, desalination of agricultural drainage is costly and energy intensive and will require sizable investments to fully develop and optimize technologies as well as manage the generated waste and brine.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Bioprocessing, Recovery, and Mass Balance of Vegetative Lipids from Metabolically Engineered “Oilcane” Demonstrates Its Potential as an Alternative Feedstock for Drop-In Fuel Production

Plant oils are increasingly in demand as renewable feedstocks for biodiesel and biochemicals. Currently, oilseeds are the primary source of plant oils. Although the vegetative tissues of plants express lipid metabolism pathways, they do not hyper- accumulate lipids. Elevated synthesis, storage, and accumulation of lipids in vegetative tissues have been achieved by metabolic engineering of sugarcane to produce “oilcane”. This study evaluates the potential of oilcane as a renewable feedstock for the co- production of lipids and fermentable sugars. Oilcane was grown under favorable climatic and field conditions in Florida (FLOC) as well as during an abbreviated growing season, outside its typical growing region, in Illinois (ILOC). The potential lipid yield of 0.35 tons/ha was projected from the hyperaccumulation of fatty acids in the stored vegetative biomass of FLOC, which is approaching the lipid yield of soybean (0.44 tons/ha). Processing of the vegetative tissues of oilcane recovered 0.20 tons/ha, which represents the recovery of 55% of the total lipids from FLOC. Chemical-free hydrothermal bioprocessing of ILOC and FLOC bagasse and leaves at 180 °C for 10 min prevented the degeneration of in situ plant lipids. Here, this allowed the recovery of lipids at the end of the bioprocess with a major fraction of lipids remaining in the biomass residues after pretreatment and saccharification. Improvements through refined biomass processing, crop management, and metabolic engineering are expected to boost lipid yields and make oilcane a prime feedstock for the production of biodiesel.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Cycles-L: A Coupled, 3-D, Land Surface, Hydrologic, and Agroecosystem Landscape Model

Managing landscapes to increase agricultural productivity and environmental stewardship can be informed by spatially-distributed models that operate at spatial and temporal scales that are intervention-relevant. This paper presents Cycles-L, a landscape-scale agroecosystem and hydrologic modeling system, using as a test case a watershed in Pennsylvania. Cycles-L emerges from melding the landscape and hydrology structure of Flux-PIHM, a 3-D land surface hydrologic model, with the agroecosystem processes in the Cycles model. Consequently, Cycles-L can simulate processes affected by topography, soil heterogeneity, and management practices, owing to its physically-based hydrology that can simulate horizontal and vertical transport of solutes with water. The model was tested at a 730-ha experimental watershed within the Mahantango Creek watershed. Cycles-L simulated well stream water and mineral nitrogen discharge (Nash-Sutcliffe coefficient 0.55 and 0.60, respectively) and grain yield (root mean square error 1.2 Mg ha -1 ). Cycles-L outputs are as good or better than those obtained with the uncoupled Flux-PIHM (water discharge) and Cycles (grain yield) models. Modeled spatial patterns of nitrogen fluxes like denitrification illustrate the combined control of crop management and topography. For example, denitrification is almost twice as high when simulated with Cycles-L than when simulated with Cycles 1-D. Due to its spatial and temporal resolution, Cycles-L fills a gap in the availability of models that operate at a scale relevant to evaluate interventions in the landscape. Cycles-L can become a central component in tools for climate change scenario analysis, precision agriculture, precision conservation, and artificial intelligence-based decision support systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A regional nuclear conflict would compromise global food security

A limited nuclear war between India and Pakistan could ignite fires large enough to emit more than 5 Tg of soot into the stratosphere. Climate model simulations have shown severe resulting climate perturbations with declines in global mean temperature by 1.8 °C and precipitation by 8%, for at least 5 y. Here we evaluate impacts for the global food system. Six harmonized state-of-the-art crop models show that global caloric production from maize, wheat, rice, and soybean falls by 13 (±1)%, 11 (±8)%, 3 (±5)%, and 17 (±2)% over 5 y. Total single-year losses of 12 (±4)% quadruple the largest observed historical anomaly and exceed impacts caused by historic droughts and volcanic eruptions. Colder temperatures drive losses more than changes in precipitation and solar radiation, leading to strongest impacts in temperate regions poleward of 30°N, including the United States, Europe, and China for 10 to 15 y. Integrated food trade network analyses show that domestic reserves and global trade can largely buffer the production anomaly in the first year. Persistent multiyear losses, however, would constrain domestic food availability and propagate to the Global South, especially to food-insecure countries. By year 5, maize and wheat availability would decrease by 13% globally and by more than 20% in 71 countries with a cumulative population of 1.3 billion people. In view of increasing instability in South Asia, this study shows that a regional conflict using <1% of the worldwide nuclear arsenal could have adverse consequences for global food security unmatched in modern history.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Seasonal dynamics of core fungi in the switchgrass phyllosphere, and co-occurrence with leaf bacteria

Plant leaves harbor complex microbial communities that influence plant health and productivity. Nevertheless, a detailed understanding of phyllosphere community assembly and drivers is needed, particularly for phyllosphere fungi. Here, we investigated seasonal dynamics of epiphytic phyllosphere fungal communities in switchgrass ( Panicum virgatum L.), a focal bioenergy crop. We also leverage previously published data on switchgrass phyllosphere bacterial communities from the same experimental plants, allowing us to compare fungal and bacterial dynamics and explore inter-Domain network associations in the switchgrass phyllosphere. Overall, we found a strong impact of sampling date on fungal community composition, with multiple taxonomic levels exhibiting clear temporal patterns in relative abundance. In addition, leaf nitrogen concentration, leaf dry matter content, plant height, and minimum daily air temperature explained significant variation in phyllosphere fungal communities, likely due to their correlation with sampling date. Finally, among the core taxa, fungal-bacterial network associations were much more common than bacteria-bacteria associations, suggesting the importance of inter-Domain phylogenetic diversity in microbiome assembly. Although our findings highlight the complexity of phyllosphere microbiome assembly, the clear temporal patterns in lineage-specific fungal abundances give promise to the potential for accurately predicting shifts in fungal phyllosphere communities throughout the growing season, a key research priority for sustainable agriculture.

16S rRNA↗
DOE OSTI2020

Corn stover harvest reduces soil CO 2 fluxes but increases overall C losses

Abstract Harvesting corn ( Zea mays L.) stover for use as bioenergy feedstock may provide short‐term economic benefits and perhaps improve grain yield in continuous corn systems, but excessive stover removal may lead to long‐term depletion of soil C stocks. To better quantify the impacts of stover harvest on the soil C balance, we investigated CO 2 fluxes under three harvest treatments (none, moderate, and high) in three continuous corn systems: (a) no tillage and no biochar applications, (b) chisel plowing with biochar amendments, and (c) chisel plowing without biochar amendments were quantified. We sampled static chambers 14, 13, and 15 times in 2010, 2011, and 2012, respectively, and the measurements were used to calibrate the Agricultural Production Systems sIMulator model. Although CO 2 ‐C emissions did not differ among the three systems, both moderate (approximately 30%) and high (approximately 60%) stover removal rates reduced simulated CO 2 ‐C emissions by nearly 10% and more than 22%, respectively. Despite these reductions in CO 2 flux, the sum of CO 2 ‐C and stover C exceeded CO 2 ‐C losses in those plots without stover removal. This finding suggested soil C depletion was occurring for the soil and crop management practices used, even though depletion was not evident after 3 years. Application of biochar increased soil C levels, suggesting it may be able to offset some C losses. We conclude that for sustainable, highly productive agroecosystems that include stover harvest, all agronomic practices must be optimized to minimize C losses and maintain soil quality.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Comparisons of biomass, water use efficiency and water use strategies across five genomic groups of Populus and its hybrids

Abstract Genetic improvement and hybridization in the Populus genus have led to the development of genotypes exhibiting fast growth, high rooting ability and disease resistance. However, while large biomass production is important for bioenergy crops, efficient use of resources including water is also important in sites lacking irrigation and for maintaining ecosystem water availability. In addition, comparison of water use strategies across a range of growth rates and genetic variability can elucidate whether certain strategies are shared among the fastest growing and/or most water use efficient genotypes. We estimated tree water use throughout the second growing season via sapflow sensors of 48 genotypes from five Populus taxa; P. deltoides W. Bartram ex Marshall × P. deltoides (D × D), P. deltoides × P. maximowiczii A. Henry (D × M), P. deltoides × P. nigra L. (D × N), P. deltoides × P. trichocarpa Torr. & Gray (D × T) and P. trichocarpa × P. deltoides (T × D) and calculated average canopy stomatal conductance ( G S ). We regressed G S and atmospheric vapor pressure deficit (VPD) wherein the slope of the relationship represents stomatal sensitivity to VPD. At the end of the second growing season, trees were harvested, and their dry woody biomass was used to calculate whole tree water use efficiency (WUE T ). We found that D × D and D × M genotypes exhibited differing water use strategies with D × D genotypes exhibiting high stomatal sensitivity while retaining leaves while D × M genotypes lost leaf area throughout the growing season but exhibited low stomatal sensitivity. Across measured taxa, biomass growth was positively correlated with WUE T , and genotypes representing each measured taxa except D × N and T × D had high 2‐year dry biomass of above 6 kg/tree. Overall, these data can be used to select Populus genotypes that combine high biomass growth with stomatal sensitivity and WUE T to limit the negative impacts of bioenergy plantations on ecosystem water resources.

09 BIOMASS FUELS↗
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↗
DOE OSTI2024

Altering plant carbon allocation to stems has distinct effects on rhizosphere soil microbiome assembly, interactions, and potential functions in sorghum

Abstract Altering plant carbon allocation from leaves to stems is key to improve biomass for forage, fuel, and renewable chemicals. The sorghum dry stalk ( D ) locus controls a quantitative trait for sugar accumulation, with enhanced carbon allocation in the stems of juicy green ( dd ) sorghum but reduced carbon allocation in that of dry white ( DD ) sorghum. However, it remains unclear whether altering sorghum sugar accumulation in stem affects below‐ground microbiome. Here we investigated sorghum rhizosphere soil microbiome in near isogenic lines with different magnitude of carbon allocations and accumulation in the stems. Results showed that enhanced carbon accumulation in stems of juicy green sorghum results in stronger selection in rhizosphere microbiome assembly. The rhizosphere soil microbial communities selected in juicy green sorghum tended to be fast‐growing microbial taxa which possessed potential functions that would promote higher potential capacity to use chemically labile carbon sources and potentially result in higher potential decomposition rates. We found the rhizosphere microbes selected by juicy green sorghum form weaker interactions than dry white sorghum. This is the first comprehensive study revealing how the different magnitude of carbon allocations to stems regulates microbial community assembly, microbial interaction, and microbial functions. This study indicates that future plant modification for bioenergy crops should also consider the impacts on belowground microbial community without compromising the sustainability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Agricultural Management Legacy Effects on Switchgrass Growth and Soil Carbon Gains

Switchgrass ( Panicum virgatum L.) is a native North American grass currently considered a high-potential bioenergy feedstock crop. However, previous reports questioned its effectiveness in generating soil organic carbon (SOC) gains, with resultant uncertainty regarding the monoculture switchgrass's impact on the environmental sustainability of bioenergy agriculture. We hypothesize that the inconsistencies in past SOC accrual results might be due, in part, to differences in prior land management among the systems subsequently planted to switchgrass. To test this hypothesis, we measured SOC and other soil properties, root biomass, and switchgrass growth in an experimental site with a 30-year history of contrasting tillage and N-fertilization treatments, 7 years after switchgrass establishment. We determined switchgrass' monthly gross primary production (GPP) for six consecutive years and conducted deep soil sampling. Nitrogen fertilization expectedly stimulated switchgrass growth; however, a tendency for better plant growth was also observed under unfertilized settings in the former no-till soil. In topsoil, SOC significantly increased from 2007 to 2023 in fertilized treatments of both tillage histories, with the greatest increase observed in fertilized no-till. Fertilized no-till also had the highest particulate organic matter content in the topsoil, with no differences among the treatments observed in deeper soil layers. However, regardless of fertilization, the tillage history had a strong effect on stratification with depth of SOC, total N, and microbial biomass C. Results suggested that historic and ongoing N fertilization had a substantial impact on switchgrass growth and soil characteristics, while tillage legacy had a much weaker, but still discernible, effect.

bioenergy crop production system↗
DOE OSTI2026

Linking Plant and Microbial Traits to Soil Carbon for Reliable and Resilient Bioenergy Systems

Bioenergy systems in the United States offer a dual opportunity to supply renewable feedstocks while enhancing ecosystem services such as hydrologic regulation, erosion control, and soil carbon (C) storage. National assessments highlight the potential to grow perennial energy crops to improve soil function and ecosystem resilience. Realizing this potential requires understanding the ecological mechanisms that govern how C is added, transformed, and stabilized in soils. Plant traits determine the quantity, depth, and chemistry of organic inputs, while microbial processes—including carbon use efficiency, necromass formation, and trophic interactions—mediate their transformation and partitioning among soil carbon pools. These biological pathways are shaped by soil physical and chemical properties, including aggregation, texture, and mineralogy, and by environmental drivers such as temperature, moisture, and disturbance, leading to context-dependent outcomes across landscapes. Management practices that diversify feedstocks, minimize disturbance, and maintain soil cover can promote both biomass production and C retention, while microbial amendments and rhizosphere engineering offer emerging, but often context-dependent, tools to optimize plant–microbe interactions. Trade-offs between biomass yield and soil carbon storage may arise when systems favor rapid aboveground productivity at the expense of belowground inputs and microbial processing, underscoring the importance of trait combinations that support both functions. Advances in monitoring, reporting, and verification—spanning precision agriculture, remote sensing, and biosensing—are improving predictive capacity through microbial-explicit process models and model–experiment (ModEx) frameworks. By connecting soil, plant, and microbial processes with advances in modeling and biosensing, this review outlines research priorities focused on trait-based parameterization and ModEx integration. These priorities will support the design of bioenergy systems that are both reliable and resilient, enhancing renewable energy production and ecosystem sustainability.

bioenergy systems↗
DOE OSTI2022

Comparative transcriptomics and metabolomics reveal specialized metabolite drought stress responses in switchgrass ( Panicum virgatum )

Summary Switchgrass ( Panicum virgatum ) is a bioenergy model crop valued for its energy efficiency and drought tolerance. The related monocot species rice ( Oryza sativa ) and maize ( Zea mays ) deploy species‐specific, specialized metabolites as core stress defenses. By contrast, specialized chemical defenses in switchgrass are largely unknown. To investigate specialized metabolic drought responses in switchgrass, we integrated tissue‐specific transcriptome and metabolite analyses of the genotypes Alamo and Cave‐in‐Rock that feature different drought tolerance. The more drought‐susceptible Cave‐in‐Rock featured an earlier onset of transcriptomic changes and significantly more differentially expressed genes in response to drought compared to Alamo. Specialized pathways showed moderate differential expression compared to pronounced transcriptomic alterations in carbohydrate and amino acid metabolism. However, diterpenoid‐biosynthetic genes showed drought‐inducible expression in Alamo roots, contrasting largely unaltered triterpenoid and phenylpropanoid pathways. Metabolomic analyses identified common and genotype‐specific flavonoids and terpenoids. Consistent with transcriptomic alterations, several root diterpenoids showed significant drought‐induced accumulation, whereas triterpenoid abundance remained predominantly unchanged. Structural analysis verified select drought‐responsive diterpenoids as oxygenated furanoditerpenoids. Drought‐dependent transcriptome and metabolite profiles provide the foundation to understand the molecular mechanisms underlying switchgrass drought responses. Accumulation of specialized root diterpenoids and corresponding pathway transcripts supports a role in drought stress tolerance.

transcriptomics↗
DOE OSTI2026

Rethinking the soil core microbiome

The concept of a core microbiome emerged from host-associated research to describe microbial members or functions conserved across clearly defined spatial, temporal, and biological boundaries. In soil- and plant-associated microbiome research, however, the term has increasingly shifted toward analytically defined subsets selected using study-specific thresholds or criteria. Synthesizing recent literature and cross-site analyses of bioenergy crop field soils, we show that the original biological meaning of the core microbiome has been blurred by dataset-specific analytical criteria. Taxa designated as ‘core’ were highly sensitive to methodological choices and often reflected explanatory value rather than conserved biological membership. Moreover, many studies that identify taxonomic ‘core’ members interpret their significance in functional terms, suggesting that functional conservation may be the biological interest. Taxonomic conservation may not be the most biologically meaningful target in highly heterogeneous soil and rhizosphere systems, where functional conservation may persist despite taxonomic turnover. Accordingly, ‘core microbiome’ should be reserved for microbial components explicitly demonstrated to be conserved across defined spatial, temporal, and environmental dimensions and linked to conserved ecological functions, while taxa selected for explanatory value are better described as ‘explanatory subsets of taxa’. Greater terminological precision will improve cross-study comparability and strengthen ecological inference in plant–soil microbiome research.

bioenergy crops↗
DOE OSTI2020

Prospects for Engineering Biophysical CO 2 Concentrating Mechanisms into Land Plants to Enhance Yields

Although cyanobacteria and algae represent a small fraction of the biomass of all primary producers, their photosynthetic activity accounts for roughly half of the daily CO 2 fixation that occurs on Earth. These microorganisms are able to accomplish this feat by enhancing the activity of the CO 2 -fixing enzyme Rubisco using biophysical CO 2 concentrating mechanisms (CCMs). Biophysical CCMs operate by concentrating bicarbonate and converting it into CO 2 in a compartment that houses Rubisco (in contrast with other CCMs that concentrate CO 2 via an organic intermediate, such as malate in the case of C 4 CCMs). This activity provides Rubisco with a high concentration of its substrate, thereby increasing its reaction rate. The genetic engineering of a biophysical CCM into land plants is being pursued as a strategy to increase crop yields. This review focuses on the progress toward understanding the molecular components of cyanobacterial and algal CCMs, as well as recent advances toward engineering these components into land plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Data for Influence of Particle Size on NIR Spectroscopic Characterization of Sorghum Biomass for the Biofuel Industry

NIR spectroscopy is a rapid and accurate green technology for high-throughput biomass characterization, including sorghum ( Sorghum bicolor ), a promising energy crop for the biofuel industry. This study assessed the influence of particle size on NIR spectroscopic analysis (wavelength range: 867–2535 nm) of sorghum biomass composition. Grown under field conditions, a total of 113 types of genetically diverse sorghum accessions were dried, ground, and sieved (<250, 250–600, 600–850, and > 850 µm particle size) for developing partial least square regression (PLSR) prediction models for moisture, ash, extractive, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin (ASL + AIL). Overall, smaller particle sizes provided better model performance, while no single particle size provided the best performance for all the selected components. With only 9 selected bands and 4 latent variables (LVs), the best PLSR model was obtained for moisture with particle size of 600–850 µm with the square root of the coefficient of determination (R) of 0.85, the ratio of prediction to deviation (RPD) of 2.2, and the root mean square error (RMSE) of 0.46 % in external validation. Similar model performances were also obtained for ash, extractive, glucan, and xylan. This study showed that size reduction could effectively improve NIR spectroscopic analysis for lipid-producing sorghum biomass for the biofuel industry.

Biomass Analytics↗
DOE OSTI2021

UAV-based multispectral time-series imagery of biomass sorghum - 2019

UAV-based high-resolution multispectral time-series orthophotos utilized to understand the relation between growth dynamics, imagery temporal resolution, and end-of-season biomass productivity of biomass sorghum as bioenergy crop. Sensor utilized is a RedEdge Micasense flown at 40 meters above ground level at the Energy Farm- UIUC in 2019.

Bioenergy crops↗