Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Bioenergy crop”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A daily, 250 m and real-time gross primary productivity product (2000–present) covering the contiguous United States

Abstract. Gross primary productivity (GPP) quantifies the amount of carbon dioxide (CO2) fixed by plants through photosynthesis. Although as a key quantity of terrestrial ecosystems, there is a lack of high-spatial-and-temporal-resolution, real-time and observation-based GPP products. To address this critical gap, here we leverage a state-of-the-art vegetation index, near-infrared reflectance of vegetation (NIRV), along with accurate photosynthetically active radiation (PAR), to produce a SatelLite Only Photosynthesis Estimation (SLOPE) GPP product for the contiguous United States (CONUS). Compared to existing GPP products, the proposed SLOPE product is advanced in its spatial resolution (250 m versus >500 m), temporal resolution (daily versus 8 d), instantaneity (latency of 1 d versus >2 weeks) and quantitative uncertainty (on a per-pixel and daily basis versus no uncertainty information available). These characteristics are achieved because of several technical innovations employed in this study: (1) SLOPE couples machine learning models with MODIS atmosphere and land products to accurately estimate PAR. (2) SLOPE couples highly efficient and pragmatic gap-filling and filtering algorithms with surface reflectance acquired by both Terra and Aqua MODIS satellites to derive a soil-adjusted NIRV (SANIRV) dataset. (3) SLOPE couples a temporal pattern recognition approach with a long-term Cropland Data Layer (CDL) product to predict dynamic C4 crop fraction. Through developing a parsimonious model with only two slope parameters, the proposed SLOPE product explains 85 % of the spatial and temporal variations in GPP acquired from 49 AmeriFlux eddy-covariance sites (324 site years), with a root-mean-square error (RMSE) of 1.63 gC m−2 d−1. The median R2 over C3 and C4 crop sites reaches 0.87 and 0.94, respectively, indicating great potentials for monitoring crops, in particular bioenergy crops, at the field level. With such a satisfactory performance and its distinct characteristics in spatiotemporal resolution and instantaneity, the proposed SLOPE GPP product is promising for biological and environmental research, carbon cycle research, and a broad range of real-time applications at the regional scale. The archived dataset is available at https://doi.org/10.3334/ORNLDAAC/1786 (download page: https://daac.ornl.gov/daacdata/cms/SLOPE_GPP_CONUS/data/, last access: 20 January 2021) (Jiang and Guan, 2020), and the real-time dataset is available upon request.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Rapid in situ nutrient element distribution in plants and soils using laser-induced breakdown spectroscopy ($\mathrm{LIBS}$)

The aim of this study is to develop and test the applicability of a rapid in situ plant chemistry profiling technique to determine elemental composition of small-volume plant and soil samples obtained from a woody bioenergy crop species, Populus trichocarpa. Expanding the research tools available to characterize the nutrient element correlations among plant tissue types and soil depths is a critical need in the path of understanding productivity and adaptation of plants to variations in external abiotic and biotic factors and developing sustainable perennial bioenergy crops that are co-optimized for biomass valorization aboveground and carbon sequestration belowground. Several plant root, stem, and soil samples were tested using laser-induced breakdown spectroscopy (LIBS) to evaluate the presence and distribution of nutrient elements. Samples were tested as collected and after being dried and cross sectioned to evaluate the effectiveness of using LIBS for in situ analysis on plant samples. The collected LIBS spectra show the elemental peaks were the same in both the as collected and prepared samples for roots and stems. Qualitative amounts of elements such as H, C, N, O, Li, Na, Mg, K, Ca, Fe, Al, and Si were able to be identified rapidly in raw samples. Here in this report we demonstrate suitability of LIBS in obtaining rapid, in situ, elemental distribution in plant and soil samples, utilizing only small sample volumes and minimal sample preparation. This demonstration opens up a new rapid phenotyping avenue necessary to fill the asymmetrical knowledge gaps in belowground performance of plant systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Foxtail mosaic virus-induced gene silencing (VIGS) in switchgrass (Panicum virgatum L.)

Abstract Background Although the genome for the allotetraploid bioenergy crop switchgrass ( Panicum virgatum ) has been established, limitations in mutant resources have hampered in planta gene function studies toward crop optimization. Virus-induced gene silencing (VIGS) is a versatile technique for transient genetic studies. Here we report the implementation of foxtail mosaic virus (FoMV)-mediated gene silencing in switchgrass in above- and below-ground tissues and at different developmental stages. Results The study demonstrated that leaf rub-inoculation is a suitable method for systemic gene silencing in switchgrass. For all three visual marker genes, Magnesium chelatase subunit D ( ChlD ) and I ( ChlI ) as well as phytoene desaturase ( PDS ), phenotypic changes were observed in leaves, albeit at different intensities. Gene silencing efficiency was verified by RT-PCR for all tested genes. Notably, systemic gene silencing was also observed in roots, although silencing efficiency was stronger in leaves (~ 63–94%) as compared to roots (~ 48–78%). Plants at a later developmental stage were moderately less amenable to VIGS than younger plants, but also less perturbed by the viral infection. Conclusions Using FoMV-mediated VIGS could be achieved in switchgrass leaves and roots, providing an alternative approach for studying gene functions and physiological traits in this important bioenergy crop.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Agent-based modeling to evaluate the effects of harvesting biomass and hunting on ring-necked pheasant ( Phasianus colchicus ) populations

As the US strives to divest from fossil fuels, dedicated energy crops have increased in popularity because of their potential to serve as a renewable source of transportation fuel and biomass-generated electricity. Whereas the impacts of crop agriculture on biodiversity have been well-documented, less is known about the potential impacts that growing bioenergy crops could have on wildlife. Here we look specifically at the ring-necked pheasant (Phasianus colchicus) and how pheasant populations may be influenced by growing and harvesting bioenergy crops. We explored effects of temporal harvest strategies at the field scale on biomass yield and pheasant population size. To investigate, we developed an agent-based model (ABM) that simulates ring-necked pheasants, tractors, hunters, and vegetation classes. One such vegetation class is land that is enrolled in a Conservation Reserve Program (CRP) plan specifically targeting pheasant conservation. Using this ABM, we assessed four different landscapes—corn-dominated, CRP-dominated, grassland-dominated, and mixed landscape—under strategies that varied the time of harvest. We also used ecological valuation to compare scenario outcomes from an economic perspective. We determined that biomass yield and pheasant population size were sensitive to harvesting times. Our scenarios totaled between ~$931,000 (minimum) and $3.8 million (maximum) over all landscapes, though on average harvesting in late spring generated the most value ($2.45 million) and harvesting in fall was a close second in terms of profitability ($2.39 million).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Airborne hyperspectral imaging of nitrogen deficiency on crop traits and yield of maize by machine learning and radiative transfer modeling

Nitrogen is an essential nutrient that directly affects plant photosynthesis, crop yield, and biomass production for bioenergy crops, but excessive application of nitrogen fertilizers can cause environmental degradation. To achieve sustainable nitrogen fertilizer management for precision agriculture, there is an urgent need for nondestructive and high spatial resolution monitoring of crop nitrogen and its allocation to photosynthetic proteins as that changes over time. Here, we used visible to shortwave infrared (400–2400 nm) airborne hyperspectral imaging with high spatial (0.5 m) and spectral (3–5 nm) resolutions to accurately estimate critical crop traits, i.e., nitrogen, chlorophyll, and photosynthetic capacity (CO 2 -saturated photosynthesis rate, V max,27 ), at leaf and canopy scales, and to assess nitrogen deficiency on crop yield. We conducted three airborne campaigns over a maize (Zea mays L.) field during the growing season of 2019. Physically based soil-canopy Radiative Transfer Modeling (RTM) and data-driven approaches i.e. Partial-Least Squares Regression (PLSR) were used to retrieve crop traits from hyperspectral reflectance, with ground truth of leaf nitrogen, chlorophyll, V max,27 , Leaf Area Index (LAI), and harvested grain yield. To improve computational efficiency of RTMs, Random Forest (RF) was used to mimic RTM simulations to generate machine learning surrogate models RTM-RF. The results show that prior knowledge of soil background and leaf angle distribution can significantly reduce the ill-posed RTM retrieval. RTM-RF achieved a high accuracy to predict leaf chlorophyll content (R 2 = 0.73) and LAI (R 2 = 0.75). Meanwhile, PLSR exhibited better accuracy to predict leaf chlorophyll content (R 2 = 0.79), nitrogen concentration (R 2 = 0.83), nitrogen content (R 2 = 0.77), and V max,27 (R 2 = 0.69) but required measured traits for model training. We also found that canopy structure signals can enhance the use of spectral data to predict nitrogen related photosynthetic traits, as combining RTM-RF LAI and PLSR leaf traits well predicted canopy-level traits (leaf traits × LAI) including canopy chlorophyll (R 2 = 0.80), nitrogen (R 2 = 0.85) and V max,27 (R 2 = 0.82). Compared to leaf traits, we further found that canopy-level photosynthetic traits, particularly canopy V max,27 , have higher correlation with maize grain yield. This study highlights the potential for synergistic use of process-based and data-driven approaches of hyperspectral imaging to quantify crop traits that facilitate precision agricultural management to secure food and bioenergy production.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Transforming our understanding of chloroplast-associated genes through comprehensive characterization of protein localizations and protein-protein interactions

Bioenergy crops are a renewable source of fuels and are a critical base for building a carbon-neutral economy. Rational engineering of bioenergy crops has the potential to enhance the yields. However, our ability to engineer plants is limited because the functions of most genes remain unknown. Systematic characterization of gene function in plants thus has the potential to greatly accelerate bioenergy research. Here, we focus on the chloroplast, an underexplored energy-producing organelle that is a hallmark of plants. The chloroplast is one of the promising targets of biofuel crop engineering efforts because of its central role in photosynthesis, metabolism, and intracellular signaling. However, the protein composition of the chloroplast and the functions of most of its proteins remain poorly characterized. At the core of this project, we sought to comprehensively determine the localization of chloroplast-associated proteins and generate a spatially defined protein-protein interaction network for chloroplast. For this purpose, we used the leading model alga Chlamydomonas reinhardtii, which greatly increased experimental speed and throughput. We illustrated the value of our findings to land plants by determining the localization of Arabidopsis thaliana land plant homologs of the Chlamydomonas proteins. Altogether, we were successful in determining the localization of 1,034 chloroplast-associated proteins in Chlamydomonas. The localizations provide numerous insights into the spatial organization of chloroplasts and how they function to support photosynthesis. The localization patterns of distinct proteins revealed new chloroplast structures and revealed new spatial organization inside the chloroplast. We also identified new components of known chloroplast structures, such as the chloroplast envelope, nucleoid, plastoglobuli, and pyrenoid. We identified these new components by investigating the interacting partners of known proteins. Many proteins localized in both the chloroplast and other cellular structures, thereby hinting at new functions and communication between cellular structures. We also applied machine learning on the atlas to generate predictions for the location of all of the proteins in Chlamydomonas. This enabled us to assign putative functions to many uncharacterized proteins based on their cellular location. Altogether, this research establishes a rich resource that opens new avenues of investigation and guides future work in deciphering and manipulating chloroplast function. Next, we developed an extensive protein-protein interaction network for the chloroplast by performing affinity purification-mass spectrometry on ~1,150 tagged chloroplast-associated proteins, the first such large-scale study in any photosynthetic organism. This dataset reveals 4,694 high-confidence protein-protein interactions, offering insights into the functions of thousands of conserved poorly-characterized chloroplast proteins. This systematic identification of protein-protein interactions in the chloroplast also provides multiple exciting new research directions and a detailed blueprint of the chloroplast's operation. This research lays the groundwork to decipher the inner workings of the chloroplast, the cell structure at the heart of photosynthesis. The spatial atlas and protein-protein interactions reveal chloroplast organizational features that would not have been accessible with traditional approaches. The localization mapping, insights into the function, and research materials generated further provide a rich resource for the research community to advance the understanding of how the chloroplast is organized to enable engineering of enhanced photosynthetic organisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Characterizing proteases in sorghum drought response using activity-based protein profiling (ABPP)

Sorghum (Sorghum bicolor) is a C4 grass species that is a major food and bioenergy crop grown worldwide. Understanding the response of sorghum to climate change is therefore critical to future sustainable food and bioenergy production. Major advancements in genome sequencing have provided a wealth of genomic data for DOE-relevant plant species, but the functions of many of these genes remain unknown. Genotype to phenotype characterization of sorghum and other bioenergy crops is needed to identify key genes responsible for plant resilience to drought and other environmental stressors. Proteases, which modulate protein degradation and cellular signaling processes by catalyzing the hydrolysis of proteins into smaller proteins, peptides, or amino acids, are highly implicated in plant drought stress responses. We developed a method for using activity-based protein profiling (ABPP) of selected protease activities (serine and cysteine proteases) to characterize drought stress responses in sorghum roots and leaves. Analysis of these ABPP data identified several known serine and cysteine proteases as well as uncharacterized sorghum proteins which may have protease activities that can be explored in future validation studies.

09 BIOMASS FUELS↗
DOE OSTI2026

Data for Sugar Accumulation Enhancement in Sorghum Stem is Associated with Reduced Reproductive Sink Strength and Increased Phloem Unloading Activity

Sweet sorghum has emerged as a promising source of bioenergy mainly due to its high biomass and high soluble sugar yield in stems. Studies have shown that loss-of-function Dry locus alleles have been selected during sweet sorghum domestication, and decapitation can further boost sugar accumulation in sweet sorghum, indicating that the potential for improving sugar yields is yet to be fully realized. To maximize sugar accumulation, it is essential to gain a better understanding of the mechanism underlying the massive accumulation of soluble sugars in sweet sorghum stems in addition to the Dry locus. We performed a transcriptomic analysis upon decapitation of near-isogenic lines for mutant (d, juicy stems, and green leaf midrib) and functional (D, dry stems and white leaf midrib) alleles at the Dry locus. Our analysis revealed that decapitation suppressed photosynthesis in leaves, but accelerated starch metabolic processes in stems. SbbHLH093 negatively correlates with sugar levels supported by genotypes (DD vs. dd), treatments (control vs. decapitation), and developmental stages post anthesis (3d vs.10d). D locus gene SbNAC074A and other programmed cell death-related genes were down regulated by decapitation, while sugar transporter-encoding gene SbSWEET1A was induced. Both SbSWEET1A and Invertase 5 were detected in phloem companion cells by RNA in situ assay. Loss of the SbbHLH093 homolog, AtbHLH093, in Arabidopsis led to a sugar accumulation increase. This study provides new insights into sugar accumulation enhancement in bioenergy crops, which can be potentially achieved by reducing reproductive sink strength and enhancing phloem unloading.

Transcriptomics↗
DOE OSTI2023

Evaluating the incentive for soil organic carbon sequestration from carinata production in the Southeast United States

Soil organic carbon (SOC) can be increased by cultivating bioenergy crops to produce low-carbon fuels, improving soil quality and agricultural productivity. This study evaluates the incentives for farmers to sequester SOC by adopting a bioenergy crop, carinata. Two agricultural management scenarios – business as usual (BaU) and a climate-smart (no-till) practice – were simulated using an agent-based modeling approach to account for farmers’ carinata adoption rates within their context of traditional crop rotations, the associated profitability, influences of neighboring farmers, as well as their individual attitudes. Here, using the state of Georgia, US, as a case study, the results show that farmers allocated 1056 × 10 3 acres (23.8%; 2.47 acres is equivalent to 1 ha) of farmlands by 2050 at a contract price of $\$6.5$ per bushel of carinata seeds and with an incentive of $50Mg -1 CO2e SOC sequestered under the BaU scenario. In contrast, at the same contract price and SOC incentive rate, farmers allocated 1152 × 10 3 acres (25.9%) of land under the no-till scenario, while the SOC sequestration was 483.83 × 10 3 Mg CO2e, which is nearly four times the amount under the BaU scenario. Thus, this study demonstrated combinations of seed prices and SOC incentives that encourage farmers to adopt carinata with climate-smart practices to attain higher SOC sequestration benefits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Cell Wall Compositions of Sorghum bicolor Leaves and Roots Remain Relatively Constant Under Drought Conditions

Renewable fuels are needed to replace fossil fuels in the immediate future. Lignocellulosic bioenergy crops provide a renewable alternative that sequesters atmospheric carbon. To prevent displacement of food crops, it would be advantageous to grow biofuel crops on marginal lands. These lands will likely face more frequent and extreme drought conditions than conventional agricultural land, so it is crucial to see how proposed bioenergy crops fare under these conditions and how that may affect lignocellulosic biomass composition and saccharification properties. We found that while drought impacts the plant cell wall of Sorghum bicolor differently according to tissue and timing of drought induction, drought-induced cell wall compositional modifications are relatively minor and produce no negative effect on biomass conversion. This contrasts with the cell wall-related transcriptome, which had a varied range of highly variable genes (HVGs) within four cell wall-related GO categories, depending on the tissues surveyed and time of drought induction. Further, many HVGs had expression changes in which putative impacts were not seen in the physical cell wall or which were in opposition to their putative impacts. Interestingly, most pre-flowering drought-induced cell wall changes occurred in the leaf, with matrix and lignin compositional changes that did not persist after recovery from drought. Most measurable physical post-flowering cell wall changes occurred in the root, affecting mainly polysaccharide composition and cross-linking. This study couples transcriptomics to cell wall chemical analyses of a C4 grass experiencing progressive and differing drought stresses in the field. As such, we can analyze the cell wall-specific response to agriculturally relevant drought stresses on the transcriptomic level and see whether those changes translate to compositional or biomass conversion differences. Our results bolster the conclusion that drought stress does not substantially affect the cell wall composition of specific aerial and subterranean biomass nor impede enzymatic hydrolysis of leaf biomass, a positive result for biorefinery processes. Coupled with previously reported results on the root microbiome and rhizosphere and whole transcriptome analyses of this study, we can formulate and test hypotheses on individual gene candidates’ function in mediating drought stress in the grass cell wall, as demonstrated in sorghum.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Available land for cellulosic biofuel production: a supply chain centered comparison

The land that is potentially available to produce dedicated cellulosic bioenergy crops, often referred to as 'marginal' land, depends heavily on the underlying assumptions used to classify and identify it. In this study we compare three definitions and types of marginal land to identify the interactions between the bioenergy landscape and the logistics networks needed for the biofuel supply chain. Typical studies of the scale, cost, and greenhouse gas (GHG) mitigation potential of cellulosic biofuel take a land-centered approach which may neglect to account for the trade-offs between establishing bioenergy crops and the supply chain design decisions needed to allow those crops to be converted to liquid fuel. A mathematical programming approach is used to minimize the total annualized cost of a large-scale field-to-product system producing bioethanol in the USA midwest. Results show that a high concentration of marginal land leads to efficient systems and that the bioenergy landscape design becomes increasingly important with a higher emphasis on GHG mitigation. Additionally, targeted landscape design (including fertilization) with a focus on fields with high soil carbon sequestration potential can greatly reduce the system-wide GHG emissions for only a small increase in the unit cost of biofuel.

09 BIOMASS FUELS↗
DOE OSTI2023

A single amino acid change led to structural and functional differentiation of PvHd1 to control flowering in switchgrass

Abstract Switchgrass, a forage and bioenergy crop, occurs as two main ecotypes with different but overlapping ranges of adaptation. The two ecotypes differ in a range of characteristics, including flowering time. Flowering time determines the duration of vegetative development and therefore biomass accumulation, a key trait in bioenergy crops. No causal variants for flowering time differences between switchgrass ecotypes have, as yet, been identified. In this study, we mapped a robust flowering time quantitative trait locus (QTL) on chromosome 4K in a biparental F2 population and characterized the flowering-associated transcription factor gene PvHd1, an ortholog of CONSTANS in Arabidopsis and Heading date 1 in rice, as the underlying causal gene. Protein modeling predicted that a serine to glycine substitution at position 35 (p.S35G) in B-Box domain 1 greatly altered the global structure of the PvHd1 protein. The predicted variation in protein compactness was supported in vitro by a 4 °C shift in denaturation temperature. Overexpressing the PvHd1-p.35S allele in a late-flowering CONSTANS-null Arabidopsis mutant rescued earlier flowering, whereas PvHd1-p.35G had a reduced ability to promote flowering, demonstrating that the structural variation led to functional divergence. Our findings provide us with a tool to manipulate the timing of floral transition in switchgrass cultivars and, potentially, expand their cultivation range.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Data from: Leaching losses of dissolved organic carbon and nitrogen from agricultural soils in the upper US Midwest

Leaching losses of dissolved organic carbon (DOC) and nitrogen (DON) from agricultural systems are important to water quality and carbon and nutrient balances but are rarely reported; the few available studies suggest linkages to litter production (DOC) and nitrogen fertilization (DON). In this study we examine the leaching of DOC, DON, NO3-, and NH4+ from no-till corn (maize) and perennial bioenergy crops (switchgrass, miscanthus, native grasses, restored prairie, and poplar) grown between 2009 and 2016 in a replicated field experiment in the upper Midwest U.S. Leaching was estimated from concentrations in soil water and modeled drainage (percolation) rates. DOC leaching rates (kg ha-1 yr-1) and volume-weighted mean concentrations (mg L-1) among cropping systems averaged 15.4 and 4.6, respectively; N fertilization had no effect and poplar lost the most DOC (21.8 and 6.9, respectively). DON leaching rates (kg ha-1 yr-1) and volume-weighted mean concentrations (mg L-1) under corn (the most heavily N-fertilized crop) averaged 4.5 and 1.0, respectively, which was higher than perennial grasses (mean: 1.5 and 0.5, respectively) and poplar (1.6 and 0.5, respectively). NO3- comprised the majority of total N leaching in all systems (59-92%). Average NO3- leaching (kg N ha-1 yr-1) under corn (35.3) was higher than perennial grasses (5.9) and poplar (7.2). NH4+ concentrations in soil water from all cropping systems were relatively low (<0.07 mg N L-1). Perennial crops leached more NO3- in the first few years after planting, and markedly less after. Among the fertilized crops, the leached N represented 14-38% of the added N over the study period; poplar lost the greatest proportion (38%) and corn was intermediate (23%). Requiring only one third or less of the N fertilization compared to corn, perennial bioenergy crops can substantially reduce N leaching and consequent movement into aquifers and surface waters.

09 BIOMASS FUELS↗
DOE OSTI2023

Bioenergy’s Role in Soil Carbon Storage Decarbonizing Transportation, Agriculture, and Industrial Sectors Workshop Summary Report

On March 28–29, 2022, the U.S. Department of Energy’s (DOE) Bioenergy Technologies Office (BETO) hosted the public virtual workshop “Bioenergy’s Role in Soil Carbon Storage.” Given the recent emphasis of the Biden administration on decarbonizing transportation, agriculture, and industrial sectors of the U.S. economy, this workshop examined how decarbonization through enhanced soil carbon storage while growing bioenergy crops is possible by discussing challenges and opportunities that affect soil carbon levels. Stakeholders representing academia, industry, the farming community, agricultural and forestry sectors, municipalities, and federal agencies involved in soil carbon storage participated in this workshop. A series of keynote presentations, plenary presentations, and stakeholder input sessions provided opportunities for sharing knowledge and identifying research and development (R&D) needs for future advances in soil carbon storage in relation to bioenergy crops. This document provides an overview of the content discussed in the presentations, as well as a summary of the stakeholder input received during the session discussions.

09 BIOMASS FUELS↗
DOE OSTI2024

Impacts of Legacy and Contemporary Nitrogen Inputs on N 2 O and CO 2 Emissions in Miscanthus and Maize Cultivated Soils

ABSTRACT Nutrient inputs influence the sustainability of bioenergy crop production through contemporary (shortly after addition) and legacy effects (persisting over years) on microbial nitrogen (N) and carbon cycling, which contribute to greenhouse gas emissions. However, the relative importance of contemporary and legacy effects and how that could vary by crop functional types is poorly understood. Considering its rhizomatous roots and perennial growth, we hypothesized that Miscanthus × giganteus (M×g) would be more sensitive to legacy N fertilization and the historical context of its environment than an annual crop like maize. To test this hypothesis, we examined the effects of legacy and contemporary N inputs on nitrous oxide (N 2 O) and carbon dioxide (CO 2 ) emissions, as well as key N cycling genes in soils where M×g and maize were grown. A 150‐day soil incubation experiment was conducted using soils from a long‐term M×g and maize fertility experiment with three historic N fertilization rates (0, 112, and 336 kg N ha −1 year −1 ) and a contemporary amendment (60 mg N kg −1 ) with negative control (0 mg N kg −1 ). We observed significant increases in cumulative N 2 O emissions in Mxg soils relative to maize soils, particularly at higher legacy fertilization rates, while contemporary N had no significant effect. Bacterial amo A gene abundance, which plays a significant role in nitrification in nutrient‐rich soils, also increased with higher legacy fertilization rates in M×g soils but was unaffected by the contemporary N. In maize soils, legacy and contemporary N did not significantly affect N 2 O emissions, but cumulative CO 2 emissions and amo A gene abundance significantly increased. The abundances of nor B genes were not significantly influenced by either legacy fertilization or contemporary N amendments in either soil. Our findings demonstrate the greater importance of fertilization history over contemporary N in mediating soil N 2 O emissions, particularly for perennial bioenergy crops.

09 BIOMASS FUELS↗
DOE OSTI2024

Process strategies for recovery of sugars, lipids, and lignin from oilcane bagasse using natural deep eutectic solvents (NADES)

Sugarcane is being enhanced as a bioenergy crop by engineering it to accumulate and store lipids along with polymeric sugars in vegetative tissues. However, there is no existing process that allows for processing this new crop to recover both lipid and cellulosic sugars from the oilcane bagasse. Therefore, a comprehensive investi- gation of two pretreatment methods—natural deep eutectic solvents (NADES) and chemical-free hydrothermal pretreatment (HT) was conducted to judge their suitability for recovering fermentable sugars, lipids, and lignin from bagasse. Two NADES, i.e., choline chloride: lactic acid (ChCl:LA) and betaine: lactic acid (BT:LA) were prepared using a 1:2 M ratio and were evaluated for pretreatment of oilcane bagasse at 10, 20, and 50 % (w/w) solids, followed by enzymatic hydrolysis at 10 % (w/w) solids. Notably, ChCl:LA NADES treatment at 10 % (w/ w) solids at 140 °C for 2 h, solubilized 78.8 % of lignin and 80.4 % of hemicellulose and allowed 82.7 % enzymatic conversion of glucans to glucose. In contrast, HT pretreatment removed approximately 87.6 % of the hemicellulose and provided an enzymatic glucose yield of 69.7 %. Furthermore, ChCl:LA operated at 50 % solids loading the enriched lipids 2.6-fold (9.2 wt%) in recovered solids compared to HT (6.4 %) and BT:LA (5.1 %) pretreatment processes. NMR-HSQC and GPC analysis showed that ChCl:LA also cleaved the most lignin β–O–4 linkages and demonstrated lower molecular weight compared to HT. As a result, this study demonstrates that NADES pretreatment is an effective green processing method for recovering lipids, sugars, and lignin from bioenergy crops at high solid loading (50 % w/w) within the context of an integrated biorefinery.

09 BIOMASS FUELS↗
DOE OSTI2021

Iron incorporation both intra- and extra-cellularly improves the yield and saccharification of switchgrass (Panicum virgatum L.) biomass

Abstract Background Pretreatments are commonly used to facilitate the deconstruction of lignocellulosic biomass to its component sugars and aromatics. Previously, we showed that iron ions can be used as co-catalysts to reduce the severity of dilute acid pretreatment of biomass. Transgenic iron-accumulating Arabidopsis and rice plants exhibited higher iron content in grains, increased biomass yield, and importantly, enhanced sugar release from the biomass. Results In this study, we used intracellular ferritin (FerIN) alone and in combination with an improved version of cell wall-bound carbohydrate-binding module fused iron-binding peptide (IBPex) specifically targeting switchgrass, a bioenergy crop species. The FerIN switchgrass improved by 15% in height and 65% in yield, whereas the FerIN/IBPex transgenics showed enhancement up to 30% in height and 115% in yield. The FerIN and FerIN/IBPex switchgrass had 27% and 51% higher in planta iron accumulation than the empty vector (EV) control, respectively, under normal growth conditions. Improved pretreatability was observed in FerIN switchgrass (~ 14% more glucose release than the EV), and the FerIN/IBPex plants showed further enhancement in glucose release up to 24%. Conclusions We conclude that this iron-accumulating strategy can be transferred from model plants and applied to bioenergy crops, such as switchgrass. The intra- and extra-cellular iron incorporation approach improves biomass pretreatability and digestibility, providing upgraded feedstocks for the production of biofuels and bioproducts.

09 BIOMASS FUELS↗
DOE OSTI2025

Populus PtrbHLH011 Is a Transcriptional Co‐Regulator Involved in the Activation of Cell Wall Biosynthesis by Iron Deprivation

The lack of a mechanistic understanding of the environmental plasticity of secondary cell wall (SCW) biosynthesis restricts large-scale biomass and bioenergy production on marginal lands. Using Populus (poplar), a key bioenergy crop, we discovered that iron deprivation, a prevalent abiotic stress on marginal lands, stimulates SCW biosynthesis in stems. We identified the transcription factor PtrbHLH011 as a critical regulator underlying this response. Through integrated analyses involving phenotypic characterisation of PtrbHLH011 knockout and overexpression plants, functional genomics and molecular investigations, we established that PtrbHLH011 functions as a central regulator of SCW biosynthesis, iron homeostasis and flavonoid biosynthesis by directly repressing essential genes in these pathways. Iron deprivation downregulates PtrbHLH011 expression, subsequently activating these biosynthetic pathways. Notably, cytosine base editing-based knockout of PtrbHLH011 significantly enhanced plant growth, yielding up to a 110% increase in stem diameter and a 300% increase in leaf iron content. These findings present a novel regulatory mechanism linking environmental iron availability to SCW biosynthesis and illustrate a practical strategy to improve biomass yield on iron-deficient marginal lands. Furthermore, our mechanistic insights into PtrbHLH011 target recognition and regulation provide a valuable foundation for precise manipulation of gene regulatory networks, facilitating the development of high-performance bioenergy crops adapted to marginal environments.

59 BASIC BIOLOGICAL SCIENCES↗