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At least 163 records · Page 9

Evaluation of eastern gamagrass as dual-purpose complementary bioenergy and forage feedstock to switchgrass

Switchgrass (SG) is considered a model bioenergy crop and a warm-season perennial grass (WSPG) that traditionally served as forage feedstock in the United States. To avoid the sole dependence on SG for bioenergy production, evaluation of other crops to diversify the pool of feedstock is needed. We conducted a 3-year field experiment evaluating eastern gamagrass (GG), another WSPG, as complementary feedstock to SG in one- and two-cut systems, with or without intercropping with crimson clover or hairy vetch, and under different nitrogen (N) application rates. Our results showed that GG generally produced lower biomass (by 29.5%), theoretical ethanol potential (TEP, by 2.8%), and theoretical ethanol yield (TEY, by 32.9%) than corresponding SG under the same conditions. However, forage quality measures, namely acid detergent fiber (ADF), crude protein (CP), and elements P, K, Ca, and Mg were significantly higher in GG than those in SG. Nitrogen fertilizer significantly enhanced biomass (by 1.54 Mg ha -1 ), lignin content (by 2.10 g kg -1 ), and TEY (787.12 L ha -1 ) in the WSPGs compared to unfertilized treatments. Intercropping with crimson clover or hairy vetch did not significantly increase biomass of the WSPGs, or TEP and TEY in unfertilized plots. This study demonstrated that GG can serve as a complementary crop to SG and could be used as a dual-purpose crop for bioenergy and forage feedstock in farmers' rotations.

09 BIOMASS FUELS↗

An integrated landscape designed for commodity and bioenergy crops for a tile-drained agricultural watershed

Here, locating bioenergy crops on strategically selected subfield areas of marginal interest for commodity agriculture can increase environmental sustainability. Location and choice of bioenergy crops should improve environmental benefits with minimal disruption of current food production systems. We identified subfield soils of a tile-drained agricultural watershed as marginal if they had areas of low crop productivity index (CPI), were susceptible to nitrate-nitrogen (NO 3 –N) leaching, or were susceptible to at least two other forms of environmental degradation (marginal areas). In the test watershed (Indian Creek watershed, IL) with annual precipitation of 852 mm, 3% of soils were CPI areas and 22% were marginal areas. The Soil and Water Assessment Tool was used to forecast the impact of growing switchgrass ( Panicum virgatum L.), willow ( Salix spp.), and big bluestem ( Andropogon gerardi Vitman) in these subfield areas on annual grain yields, NO 3 –N and sediment exports, and water yield. Simulated conversion of CPI areas from current land use to bioenergy crops had no significant (p ≤ 0.05) impact on grain production and reduced NO 3 –N and sediment exports by 5.0 to 6.0% and 3.0%, respectively. Conversion of marginal areas from current land use to switchgrass forecasted the production of 34,000 t of biomass and reductions in NO 3 –N (26.0%) and sediment (33.0%) exports. Alternatively, conversion of marginal areas from current land use to willow forecasted similar reductions as switchgrass for sediment but significantly (p ≤ 0.01) lower reductions in annual NO 3 –N export (18.0 vs. 26.0%).

09 BIOMASS FUELS↗

Incorporating Bioenergy in Sustainable Landscape Designs Workshop Two: Agricultural Landscapes

The Bioenergy Technologies Office hosted two workshops on Incorporating Bioenergy in Sustainable Landscape Designs with Oak Ridge and Argonne National Laboratories in 2014. The second workshop focused on agricultural landscapes and took place in Argonne, IL from June 24—26, 2014. The workshop brought together experts to discuss how landscape design can contribute to the deployment and assessment of sustainable bioenergy. This report summarizes the discussions that occurred at this particular workshop.

09 BIOMASS FUELS↗

Bioenergy Feedstock Library Annual Summary Report

The Bioenergy Feedstock Library (BFL), part of the Biomass Feedstock National User Facility (BFNUF) located at INL, is a physical sample repository and a web-accessible electronic database. The BFL stores physical and chemical characteristics of biomass and waste carbon sources for energy use as well as samples generated from across U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) funded projects. The objective of this Bioenergy Feedstock Library Annual Summary Report for 2022 is to focus on the (1) publicly available analytical data and equipment tracked through the BFNUF, (2) physical samples available for request, (3) sample and data archival progress from recent BETO-funded projects, and (4) publicly available data sets created upon request from BETO, INL projects, or outside entities. This report highlights key statistics from FY22 and available data and information important for INL, BFL users, academics, and industry.

09 BIOMASS FUELS↗

Bioenergy Feedstock Library Annual Summary Report 2024

The Bioenergy Feedstock Library (BFL), part of the Biomass Feedstock National User Facility (BFNUF) located at Idaho National Laboratory (INL), is a physical sample repository and a web-accessible electronic database. The BFL stores physical and chemical characteristics of biomass and waste carbon sources for energy use, as well as samples generated from U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) and U.S. Department of Agriculture-funded projects. The objective of this Bioenergy Feedstock Library Annual Summary Report for 2024, similar to the 2023 Annual Summary Report , is to focus on the updates to: (1) publicly available analytical data and equipment tracked through the BFNUF, (2) significant increases in the physical samples available for request, (3) sample and data archival progress from recent BETO-funded projects, and (4) publicly available data sets created upon request from BETO, INL projects, or outside entities compared to the previous annual summary reports. This report highlights key statistics and available data and information important for INL, BFL users, academics, and industry.

09 BIOMASS FUELS↗

2024 Bioenergy Industry Status Report

This report provides a snapshot of the bioenergy industry status at the end of 2024. The report compliments other annual market reports from the Department of Energy's (DOE's) Office of Energy Efficiency and Renewable Energy (EERE) offices and is supported by DOE'sOffice of Critical Minerals and Energy Innovation's Alternative Fuels and Feedstocks Office. The 2024 Bioenergy Industry Status Report focuses on past year data covering multiple dimensions of the bioenergy industry and does not attempt to make future market projections. There report covers production, consumption, plants, trade, and end-use for all biofuels, biopower, and biobased products where data is available. The report provides a balanced and unbiased assessment of the industry and associated markets. It is openly available to the public and is intended to complement other industry reports with a focus on DOE stakeholder needs.

09 BIOMASS FUELS↗

Water loss through evapotranspiration after precipitation events in bioenergy crops grown in similar climatic conditions

The relationship between precipitation and evapotranspiration (ET) is critical to understanding water cycle related dynamics in ecosystems, including crops. Existing studies of bioenergy crops have primarily focused on annual or seasonal ET rates, with less attention given to the immediate ET response following precipitation events. This study examines the variation in ET rates in the days subsequent to precipitation events across various bioenergy crops—corn, switchgrass, and prairies—utilizing 13 years (2010–2022) of growing season data. Meteorological and eddy covariance flux data were collected from seven eddy covariance flux towers as part of the GLBRC scale-up experiment at the Kellogg Biological Station Long Term Ecological Research sites. The analysis revealed that average ET peaked the day after precipitation and declined linearly over the following days, with a statistically significant relationship (p-value = 0.00027, R2 = 0.96). Neither the type of biofuel vegetation nor the historical land use significantly influenced ET post-precipitation events (p-values = 0.53 and 0.153, respectively). Key predictors of ET following precipitation events include shortwave radiation, season, day of the year, ambient temperature, vapor pressure deficit (VPD), long-wave radiation, precipitation amount, soil moisture, and annual variability. These findings enhance our comprehension of ET responses in bioenergy crop systems, with implications for water management in sustainable agriculture.

09 BIOMASS FUELS↗

Site and Bioenergy Cropping System Similarly Affect Distinct Live and Total Soil Microbial Communities

Bioenergy crops are a promising energy alternative to fossil fuels. During bioenergy feedstock production, crop inputs shape the composition of soil microbial communities, which in turn influences nutrient cycling and plant productivity. In addition to cropping inputs, site characteristics (e.g., soil texture, climate) influence bacterial and fungal communities. We explored the response of soil microorganisms to bioenergy cropping system (switchgrass vs. maize) and site (sandy loam vs. silty loam) within two long-term experimental research stations. The live and total microbial community membership was investigated using 16S and ITS amplicon sequencing of soil RNA and DNA. For both nucleic acid types, we expected fungi and prokaryotes to be differentially impacted by crop and site due their dissimilar life strategies. We also expected live communities to be more strongly affected by site and crop than the total communities due to a sensitivity to recent stimuli. Instead, we found that prokaryotic and fungal community composition was primarily driven by site with a secondary crop effect, highlighting the importance of soil texture and fertility in shaping both communities. Specific highly abundant prokaryotic and fungal taxa within live communities were indicative of site and cropping systems, providing insight into treatment-specific, agriculturally relevant microbial taxa that were obscured within total community profiles. Within live prokaryote communities, predatory Myxobacteria spp. were largely indicative of silty and switchgrass communities. Within live fungal communities, Glomeromycota spp. were solely indicative of switchgrass soils, while a few very abundant Mortierellomycota spp. were indicative of silty soils. Site and cropping system had distinct effects on the live and total communities reflecting selection forces of plant inputs and environmental conditions over time. Comparisons between RNA and DNA communities uncovered live members obscured within the total community as well as members of the relic DNA pool. The associations between live communities and relic DNA are a product of the intimate relationship between the ephemeral responses of the live community and the accumulation of DNA within necromass that contributes to soil organic matter, and in turn shapes soil microbial dynamics.

59 BASIC BIOLOGICAL SCIENCES↗

Bioenergy sorghum nodal root bud development: morphometric, transcriptomic and gene regulatory network analysis

Bioenergy sorghum’s large and deep nodal root system and associated microbiome enables uptake of water and nutrients from and deposition of soil organic carbon into soil profiles, key contributors to the crop’s resilience and sustainability. The goal of this study was to increase our understanding of bioenergy sorghum nodal root bud development. Sorghum nodal root bud initiation was first observed on the stem node of the 7 th phytomer below the shoot apex. Buds were initiated near the upper end of the stem node pulvinus on the side of the stem opposite the tiller bud, then additional buds were added over the next 6-8 days forming a ring of 10-15 nascent nodal root buds around the stem. Later in plant development, a second ring of nodal root buds began forming on the 17 th stem node immediately above the first ring of buds. Overall, nodal root bud development can take ~40 days from initiation to onset of nodal root outgrowth. Nodal root buds were initiated in close association with vascular bundles in the rind of the pulvinus. Stem tissue forming nascent nodal root buds expressed sorghum homologs of genes associated with root initiation (WOX4), auxin transport (LAX2, PIN4), meristem activation (NGAL2), and genes involved in cell proliferation. Expression of WOX11 and WOX5, genes involved in root stem niche formation, increased early in nodal root bud development followed by genes encoding PLTs, LBDs (LBD29), LRP1, SMB, RGF1 and root cap LEAs later in development. A nodal root bud gene regulatory network module expressed during nodal root bud initiation predicted connections linking PFA5, SPL9 and WOX4 to genes involved in hormone signaling, meristem activation, and cell proliferation. A network module expressed later in development predicted connections among SOMBRERO, a gene involved in root cap formation, and GATA19, BBM, LBD29 and RITF1/RGF1 signaling. Overall, this study provides a detailed description of bioenergy sorghum nodal root bud development and transcriptome information useful for understanding the regulation of sorghum nodal root bud formation and development.

09 BIOMASS FUELS↗

From chromatin to crop: epigenetic innovations in bioenergy systems

Energy crops encompass a diverse array of plant species cultivated primarily as a source of biomass for energy generation and biofuel production. As such, they play a pivotal role in the transition to sustainable energy systems. However, their productivity is often limited by environmental stresses, nutrient availability, and the need for optimized yield. While traditional breeding and genetic engineering have driven improvements, challenges such as narrow genetic diversity, long development cycles, trait instability, and unexpected gene interactions remain. Epigenetics offers a largely untapped opportunity to overcome these constraints by regulating gene expression through mechanisms that are dynamic, finely tuned, and responsive to environmental and developmental cues. Epigenetic modifications including DNA methylation, histone post-translational changes, and small non-coding RNAs influence nearly all aspects of plant development and physiology, including traits central to bioenergy crops. While these mechanisms are well characterized in model species such as Arabidopsis thaliana, they remain underexplored in many purpose-grown energy crops. This review summarizes the current state of knowledge of epigenetic regulation in bioenergy species, explores how these mechanisms can be leveraged to enhance crop resilience and productivity, and identifies gaps in our understanding. By characterizing epigenetic mechanisms and harnessing epigenetic variation, we can expand the toolkit for developing resilient, high-yielding bioenergy crops to meet future environmental and energy demands.

09 BIOMASS FUELS↗

Environmental and Economic Assessments and Uncertainties of Multiple Lignocellulosic Biomass Utilization for Bioenergy Products: Case Studies

Life-cycle assessment (LCA) and techno-economic analysis (TEA) were applied to assess the economic feasibility and environmental benefits of utilizing multiple biomass feedstocks for bioenergy products under three different technological pathways with consideration of uncertainties. Three cases were studied for the production of pellets, biomass-based electricity, and pyrolysis bio-oil. A Monte Carlo simulation was used to examine the uncertainties of fossil energy consumption, bioenergy conversion efficiency, stochastic production rate, etc. The cradle-to-gate LCA results showed that pellet production had the lowest greenhouse gas (GHG) emissions, water and fossil fuels consumption (8.29 kg CO2 eq (equivalent), 0.46 kg, and 105.42 MJ, respectively). The conversion process presented a greater environmental impact for all three bioenergy products. When producing 46,929 Mg of pellets, 223,380 MWh of electricity, and 78,000 barrels of pyrolysis oil, the net present values (NPV) indicated that only pellet and electricity production were profitable with NPVs of $1.20 million for pellets, and $5.59 million for biopower. Uncertainty analysis indicated that pellet production showed the highest uncertainty in GHG emission, and bio-oil production had the least uncertainty in GHG emission but had risks producing greater-than-normal amounts of GHG. Biopower production had the highest probability to be a profitable investment with 85.23%.

09 BIOMASS FUELS↗

Predicting Biomass Yields of Advanced Switchgrass Cultivars for Bioenergy and Ecosystem Services Using Machine Learning

The production of advanced perennial bioenergy crops within marginal areas of the agricultural landscape is gaining interest due to its potential to sustainably produce feedstocks for biofuels and bioproducts while also improving the sustainability and resilience of commodity crop production. However, predicting the biomass yields of this production system is challenging because marginal areas are often relatively small and spread around agricultural fields and are typically associated with various abiotic conditions that limit crop production. Machine learning (ML) offers a viable solution as a biomass yield prediction tool because it is suited to predicting relationships with complex functional associations. The objectives of this study were to (1) evaluate the accuracy of commonly applied ML algorithms in agricultural applications for predicting the biomass yields of advanced switchgrass cultivars for bioenergy and ecosystem services and (2) determine the most important biomass yield predictors. Datasets on biomass yield, weather, land marginality, soil properties, and agronomic management were generated from three field study sites in two U.S. Midwest states (Illinois and Iowa) over three growing seasons. The ML algorithms evaluated in the study included random forests (RFs), gradient boosting machines (GBMs), artificial neural networks (ANNs), K-neighbors regressor (KNR), AdaBoost regressor (ABR), and partial least squares regression (PLSR). Coefficient of determination (R 2 ) and mean absolute error (MAE) were used to evaluate the predictive accuracy of the tested algorithms. Results showed that the ensemble methods, RF (R 2 = 0.86, MAE = 0.62 Mg/ha), GBM (R 2 = 0.88, MAE = 0.57 Mg/ha), and GBM (R 2 = 0.78, MAE = 0.66 Mg/ha), were the most accurate in predicting biomass yields of the Independence, Liberty, and Shawnee switchgrass cultivars, respectively. This is in agreement with similar studies that apply ML to multi-feature problems where traditional statistical methods are less applicable and datasets used were considered to be relatively small for ANNs. Consistent with previous studies on switchgrass, the most important predictors of biomass yield included average annual temperature, average growing season temperature, sum of the growing season precipitation, field slope, and elevation. This study helps pave the way for applying ML as a management tool for alternative bioenergy landscapes where understanding agronomic and environmental performance of a multifunctional cropping system seasonally and interannually at the sub-field scale is critical.

09 BIOMASS FUELS↗

Invertebrate and Plant Community Diversity of an Illinois Corn–Soybean Field with Integrated Shrub Willow Bioenergy Buffers

Perennial bioenergy crop production within intensively managed agricultural landscapes has the potential to improve the sustainability, resiliency, and diversity of these landscapes. Perennial crops are ideal because of their high production potential on marginal lands relative to grain crops (e.g., corn and soybean) and their ability to provide additional ecosystem service benefits. When agricultural landscapes are designed to target specific services, determining the non-targeted services of perennial bioenergy crops can further promote their adoption. This 3-year study addresses this proposition by evaluating the canopy invertebrates and understory plant (non-target crop) communities using bee bowls and point measurement of ground coverage, respectively, within a grain field integrated with shrub willow buffer systems designed for nutrient loss reduction. Greater plant diversity and richness were observed under willow than under grain, resembling that of the surrounding riparian community with more perennial, native species. However, the same relationship did not hold true for invertebrates, with seasonality having a significant influence resulting in similar communities observed in willow and grain plots. The presence of unique plant and invertebrate species in both willow and grain crops as well as foraging pollinators on both crop and non-target crop species highlights the importance of habitat heterogeneity for supporting biodiversity and the potential benefits of buffer bioenergy landscape designs.

09 BIOMASS FUELS↗

Bioenergy market competition for biomass: A system dynamics review of current policies

There is growing interest in the United States and abroad to increase the use of biomass as an energy source due to environmental and energy security benefits. In the United States, the biofuel and biopower industries are regulated by different policies and different agencies and have different drivers, which impact the maximum price the industries are willing to pay for biomass. This article describes a dynamic computer simulation model that analyzes future behavior of bioenergy feedstock markets based on varying policy and technical options. The model simulates the long-term dynamics of these markets by treating advanced biomass feedstocks as a commodity and projecting the total demand of each industry, as well as the market price over time. The model is used for an analysis of the United States bioenergy feedstock market that projects supply, demand, and market price given three independent buyers: domestic biopower, domestic biofuels, and foreign exports. With base-case assumptions, the biofuels industry is able to dominate the market and meet the federal Renewable Fuel Standard (RFS) targets for advanced biofuels. Further analyses suggest that United States bioenergy studies should include estimates of export demand for biomass in their projections, and that GHG-limiting policy would partially shield both industries from export dominance.

09 BIOMASS FUELS↗

Bioenergy Knowledge Discovery Framework (KDF) Fact Sheet

The Bioenergy Knowledge Discovery Framework (KDF) is an online collaboration and geospatial analysis tool that allows researchers, policymakers, and investors to explore and engage the latest bioenergy research. This publication describes how the KDF harnesses Web 2.0 and social networking technologies to build a collective knowledge system that facilitates collaborative production, integration, and analysis of bioenergy-related information.

bioenergy, knowledge, discovery, framework, KDF, n↗

BioEnergy Science Center

The BioEnergy Science Center, led by Oak Ridge National Laboratory, has been making advances in biofuels for over a decade. These achievements in plant genomics, microbial engineering, biochemistry, and plant physiology will carry over into the Center for Bioenergy Innovation, a new Department of Energy bioenergy research center.

09 BIOMASS FUELS↗

The DOE Bioenergy Research Centers: History, Operations, and Scientific Output

Over the past 7 years, the US Department of Energy's Office of Biological and Environmental Research has funded three Bioenergy Research Centers (BRCs). These centers have developed complementary and collaborative research portfolios that address the key technical and economic challenges in biofuel production from lignocellulosic biomass. All three centers have established a close, productive relationship with DOE's Joint Genome Institute (JGI). This special issue of Bioenergy Research samples the breadth of basic science and engineering work required to underpin a diverse, sustainable, and robust biofuel industry. In this report, which was collaboratively produced by all three BRCs, we discuss the BRC contributions over their first 7 years to the development of renewable transportation fuels. In additon, we also highlight the BRC research published in the current issue and discuss technical challenges in light of recent progress.

09 BIOMASS FUELS↗

Opportunities for bioenergy crops to support transitions from irrigated agriculture and conserve the U.S. High Plains Aquifer

This study investigates potential economic and groundwater driven transitions from irrigated maize production—the dominant irrigated cropping system in the High Plains Aquifer (HPA) region—to alternative crops such as sorghum and switchgrass, two common bioenergy feedstocks. Unsustainable groundwater extraction in the U.S. High Plains presents critical challenges including reduced irrigation capacities, diminished crop yields, lower land values, and escalating energy costs. Using a spatially explicit optimization framework combined with comprehensive economic and hydrogeological data, we evaluate optimal land-use strategies and irrigation system investments over a 30-year planning period. Results indicate significant regional variability in the future economic viability of irrigated agriculture, driven by differences in aquifer recharge rates, groundwater availability, and market conditions. Nebraska and parts of northern Texas can sustain irrigated maize profitability due to relatively favorable groundwater conditions and lower land rents, respectively. In contrast, many portions of Kansas and southern Texas are more likely to transition to dryland agriculture within two decades. Colorado and New Mexico show potential for significant adoption of switchgrass production as an alternative biomass-based energy crop. Overall, over the 30-year horizon, our model implies that approximately 23% of currently irrigated maize area across the HPA region may transition to dryland farming under business-as-usual conditions. This transition is complemented by a threefold increase in non-irrigated sorghum production, from 0.20 to 0.77 Mt yr−1, indicating that groundwater-driven shifts in agricultural production may support a larger regional base for bioenergy feedstocks. The study also reveals opportunities for producers to optimize economic returns and biomass production potential.

60 APPLIED LIFE SCIENCES↗