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At least 127 records · Page 7

Abiotic Stress Reorganizes Rhizosphere and Endosphere Network Structure of Sorghum bicolor

Sorghum bicolor is a promising bioenergy feedstock with high biomass production and unusual tolerance for stresses, such as water and nutrient limitation. Although the membership of the sorghum microbiome in response to stress has been explored, relatively little is known about how microbe–microbe networks change under water- or nutrient-limited conditions. This is important because network changes can indicate impacts on the functionality and stability of microbial communities. We performed network-based analysis on the core bacterial and archaeal community of an agronomically promising high biomass bioenergy genotype, Grassl, grown under nitrogen and water stress. Stress caused relatively minor changes in bacterial abundances within soil, rhizosphere, and endosphere communities but led to significant changes in bacterial network structure and modularity. We found a complete reorganization of network roles in all plant compartments, as well as an increase in the modularity and proportion of positive associations, which potentially could represent coexistence and cooperation in the sorghum bacterial/archaeal community under stress. Although stressors are often believed to be destabilizing, we found stressed networks were as or more stable than non-stressed networks, likely due to their redundancy and compartmentalization. Together, these findings support the idea that both sorghum and its bacterial/archaeal community can be resilient to future environmental stressors.

09 BIOMASS FUELS↗

Integrated Modeling Driven Evaluation of Opportunities for Climate‐Resilient Perennial Biomass Crop Plantings in Flood‐Prone Agricultural Landscapes

Adapting to future climate change in flood-prone landscapes will require climate-resilient agricultural systems. Planting perennial crops, like switchgrass and willow, along river corridors can mitigate future flooding while supporting bioenergy markets. We developed an integrated assessment linking climate, hydrologic, and inundation model results to assess future flood risk to river-adjacent agricultural lands in the Mid-Atlantic Region (MAR) and explore this opportunity. We produced ensemble streamflow projections for every MAR stream using a hydrologic model driven by a suite of downscaled and bias-corrected Coupled Model Intercomparison Project Phase 6 climate projections. We then conducted high-resolution inundation mapping based on projected flood frequencies for baseline and future periods. Results show that in the near-term future, at least two-thirds of the streams will experience 100-year floods more severe than the baseline 200-year floods. Riparian zones are projected to face a median rise of inundation by 9.5%–24.1%. Results show that there is an opportunity to mitigate flooding in over half of MAR's counties with the quantities of switchgrass and willow plantings anticipated for mature bioenergy markets, even under the most extreme (200-year) flood events. Our integrated modeling framework can guide similar regions to evaluate opportunities for flood-resilient agricultural systems under climate change.

60 APPLIED LIFE SCIENCES↗

Climate-focused Life Cycle Assessments of Biochar Production by an ARTi Pyrolysis Reactor and an Air Burners CharBoss® Air Curtain Incinerator

This report presents a limited, dynamic, consequential life cycle assessment (LCA) to compare the climate impacts of two biochar production methods using wood as a feedstock. The two methods are a pyrolysis reactor supplied by ARTi (Des Moines, IA, https://www.arti.com/) and a T26 CharBoss® air curtain incinerator supplied by Air Burners, Inc. (Palm City, FL, https://airburners.com/). The underlying LCA methodology is described in a chapter by Singh et al. (2024) and implemented in the form of a workbook freely available as online Supplementary Material for the chapter. For the convenience of the reader, a pre-print version of the relevant portions of Singh et al. (2024) is attached as Appendix A to this report. Specific assumptions and calculations to obtain the input parameters used in this LCA for each production method are described in the Methodology section below. This implementation of the LCA considers emissions associated with biomass loading, comminution and conversion, biochar decay in soil, and the production and use of bioenergy generated during the conversion process. The LCA is “limited” in that upstream emissions associated with biomass production, harvest, transportation, and land-use change, as well as embodied emissions in equipment and facilities are not considered. Similarly, downstream emissions from biochar transport and incorporation into soil (i.e., tillage), and the impact of biochar soil amendments on soil greenhouse gas (GHG) emissions (other than CO 2 from biochar decay in soil), soil organic carbon stocks, crop response, and surface albedo are not considered. As the intent is to compare different biochar production methods in a simple unbiased manner, the primary alternative biomass pathway for the LCA is immaculate combustion, which is the hypothetical instantaneous and complete conversion of carbon in the biomass to CO 2 at time zero without generation of any other greenhouse gases or aerosols (GHGAs) or any useful bioenergy. Use of this pathway provides relative values for the production methods and, when the embodied emissions are similar and the same feedstock is used, these relative values are reasonable approximations for those attained with a full LCA.

09 BIOMASS FUELS↗

Agent-based Modeling for the Multi-objective Optimization of Energy Production Pathways: Integrated Techno-Economics and Life Cycle Assessment

This project developed an integrated modeling framework to evaluate how purpose-grown bioenergy feedstocks could support large-scale sustainable aviation fuel production in the United States. Led by Colorado State University with project partners, the work combined geographically resolved analysis, techno-economic assessment, life cycle assessment, multi-objective optimization, and agent-based modeling to examine feedstock performance, deployment potential, land-use implications, and adoption dynamics. The overall goal was to identify practical and sustainable pathways for producing aviation fuel from feedstocks such as energy crops, woody crops, oilseeds, and algae while helping inform policy, investment, and research needs tied to national SAF goals. In essence, the project provides a systems-level assessment of the opportunities and constraints associated with scaling bioenergy-based aviation fuels in the U.S.

09 BIOMASS FUELS↗

Leaf-level physiological strategies related to productivity and plasticity of Populus in the Southeastern United States

Introduction: Populus and its hybrids are attractive bioenergy crops and the southeastern United States has broad ability to supply bioenergy markets with woody biomass. Breeding and hybridization have led to superior eastern cottonwood (Populus deltoides W. Bartram ex Marshall) and hybrid poplars adapted to a wide variety of site types not suited for agricultural production. In order to maximize productivity and minimize inputs, genotypes need to efficiently use available site resources and tolerate environmental stresses. In addition, we need to determine plasticity of traits and their coordination across sites to select traits that will broadly characterize genotypes. Therefore, our study objectives were to determine (1) which leaf traits were correlated with growth, (2) if traits and genotypes exhibited significant plasticity across sites, and (3) how traits were coordinated within and across sites and Populus taxa. Methods: We measured trees at two sites in northeastern Mississippi, United States: one upland and one alluvial terrace site. Genotypes included eastern cottonwoods as well as F 1 crosses of eastern cottonwood and P. maximowiczii (Henry), P. nigra (L.) and P. trichocarpa (Torr. & Gray). Results: We found that sites differed in which leaf traits were correlated with productivity; with water use efficiency specifically being positively correlated with growth at an alluvial terrace site, but negatively correlated with growth at an upland site. Tree height growth, leaf isotope composition (δ 13 C and δ 15 N), as well as leaf mass per area (LMA) exhibited the least plasticity across sites, while physiological gas exchange parameters and leaf nitrogen concentration exhibited the highest plasticity. Broadly across taxa, leaf carbon isotope ratios were correlated with intrinsic water use efficiency, and stomatal conductance was positively correlated with photosynthetic nitrogen use efficiency across sites, while leaf nitrogen isotope ratios exhibited contrasting relationships with leaf nitrogen concentration. Discussion: Overall, these results allow us to refine selections of productive genotypes based on site conditions and site-specific relationships with physiological parameters to better match Populus taxa with sites and landowner objectives.

bioenergy feedstocks↗

Allometric and Mobile Terrestrial LiDAR Modeling of Aboveground Woody Biomass of Populus in Coppice Production

Poplars ( Populus spp.) and their hybrids are increasingly being grown in coppice production to generate bioenergy feedstocks at frequent intervals. Allometric equations are re-quired to predict aboveground biomass (AGB) of coppiced individuals with minimal field measurements. Likewise, remote sensing tools like LiDAR (light detection and ranging) can be used if models are available to predict AGB from point cloud data. Therefore, this study sought to develop equations to predict dry woody AGB from field measurements and LiDAR data from coppiced poplar field trials containing eastern cottonwood ( P. del-toides ) and hybrid poplar taxa. We found that taxa-specific allometric models containing the summed basal area of the three largest stems in the coppice provided the best predictive model, with stem height and stem count failing to provide additional explanatory power. The best predictive LiDAR-based model was independent of taxa but had slightly lower adjusted R 2 and higher RMSE than the allometric model. It contained four parameters including crown volume, leaf area index, variance of height returns, and the top point density (i.e., density metric 9 or the proportion of points in the highest point interval when the point cloud is evenly divided into ten vertical intervals). In total, these models can be used to quickly and efficiently estimate dry woody AGB of Populus coppice systems for bioenergy feedstock production.

AGB↗

Developmentally-specific physiological and metabolic responses support drought resilience in switchgrass and constrains biofuel yield

Switchgrass (Panicum virgatum) is a promising bioenergy crop due in part to its resilience to drought stress. However, the significance of drought timing remains poorly understood, both from a plant biology perspective and its impact on downstream biofuel production. This study determines the developmental stage-specific physiological and metabolic responses of switchgrass to drought stress and its implications for biofuel production using a custom-built programmable irrigation system. Vegetative, flowering, and senescence-stage drought significantly reduced carbon dioxide assimilation, and stomatal conductance without affecting biomass yield. Metabolic profiling revealed significant accumulation of glucose, fructose, quinic acid, shikimate and GABA during vegetative-stage drought, while flowering and senescence stages exhibited limited metabolic changes. Similarly, specialized metabolites also displayed distinct developmental patterns, with vegetative-stage drought driving the most pronounced metabolic alterations. Thermochemically-treated and hydrolyzed switchgrass biomass from vegetative-stage drought showed elevated lignocellulose-derived compounds and saponins with the latter most positively correlating with fermentation lag times. Conversely, senescence-stage drought enhanced ethanol yields while lowering saponin levels in the hydrolysates. While vegetative-stage drought enhanced physiological resilience, it compromises downstream biofuel production by introducing fermentation inhibitors, particularly saponins.

biofuel↗

Genetics of Flooding Tolerance in an F 2 Miscanthus sacchariflorus ssp. lutarioriparius × M. sinensis Population

Miscanthus is a warm-season, perennial grass cultivated as a feedstock for bioenergy and bioproducts. M. sacchariflorus ssp. lutarioriparius has high yield potential and is well-adapted to seasonal flooding, but little is known about the genetics of this adaptation. We conducted a quantitative trait locus (QTL) analysis on a population of 332 diploid Miscanthus ×giganteus (Mxg) F2s derived from an initial cross between diploid M. sacchariflorus ssp. lutarioriparius ‘PF30022’ and diploid M. sinensis ‘PMS-014’, followed by intermating 50 F 1 s. Using tanks in a greenhouse to assess the effects of partial submergence on actively growing plants, we compared an aerobic soil control to a 6-week flood treatment. The study's primary objectives were to (1) identify QTL for flooding tolerance in Miscanthus , (2) identify candidate genes and (3) compare ethylene response factors in Miscanthus with those in rice and Arabidopsis , sorghum and maize for binding site sequence homology and synteny, especially those associated with flooding tolerance. In total, 10 QTL and 66 candidate genes for partial submergence tolerance were identified (including many for ethylene signalling), a first report for Miscanthus . Notably, none of the Miscanthus candidates were orthologs of rice Sub1A, SK1 or SK2 , yet the ‘PF30022’ parent exhibited a snorkeling phenotype, indicating convergent evolution. This study will facilitate breeding of climate-resiliant Mxg.

abiotic stress tolerance↗

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↗

Data for Physiological Controls on Carbon Fluxes and Biomass Production in Miscanthus: Insights From a Process- Based Agroecosystem Model

Biomass crops serve as essential feedstocks for renewable energy and bioproducts and play a critical role in achieving lower emissions in the transportation sector. However, dedicated perennial biomass crops such as Miscanthus × giganteus (Miscanthus) remain underrepresented in process- based agroecosystem models, limiting robust evaluation of their economic and environmental performance. In this study, we developed a data- constrained representation of the sterile triploid Miscanthus (IL clone) within the process- based model ecosys, integrating global sensitivity analysis, ensemble simulation, and parameter calibration. Planting, harvesting, and fertilization practices consistent with field management were incorporated, and phenology was constrained using PhenoCam- derived Green Chromatic Coordinate (GCC) data. Using the Morris global sensitivity analysis method, we identified 11 key physiological parameters governing plant carbon, water, and nutrient relations, particularly processes associated with CO2 assimilation. We then conducted ensemble simulations by perturbing these parameters and calibrated the model against eddy covariance fluxes and field- measured biomass. Building on the calibrated operating state, parameter- response analyses show that different photosynthetic processes influence productivity in different ways. Protein allocation determines whether productivity increases toward a higher level, whereas electron transport capacity controls additional gains once protein allocation approaches saturation. These findings demonstrate that parameter importance depends on physiological context and on which photosynthetic processes remain limiting. Calibration and validation against observations show that ecosys can reliably reproduce carbon and water fluxes, as well as both above- and belowground biomass, with post- calibration GPP R2 improving from 0.67 to 0.95 during the calibration period and remaining high during validation (R2 = 0.95). These results provide a mechanistic foundation for regional simulations and sustainable bioenergy assessments.

Carbon↗

Yield From Iowa's First Commercial Miscanthus Fields: Implications of Spatial Variability for Productivity and Sustainability Beyond Research Plots

The cultivation of sterile giant miscanthus (Miscanthus × giganteus, M × g) for bioenergy and bioproducts has expanded into grain-cropped land in the United States (US) as local markets developed for this high-yielding perennial grass (10–30 Mg DM ha −1 ). However, the magnitude of spatial and temporal variability in yield within US Corn Belt fields, along with impacts on economic return and sustainable land management, is poorly understood. This study established a diagnostic model relating remote sensing-derived vegetation indices to ground truth data from 105 hand-harvested stem biomass samples, which were strategically selected to represent the full range of vegetation index observations. The high-resolution satellite-sensed vegetation indices captured > 90% of the yield variation measured within fields. This model was then used to predict yield variability and assess economic performance across four of the first commercial M × g fields in the Corn Belt state of Iowa, US. Significant spatial variability in biomass dry matter (DM) yields (9.3–18.1 Mg DM ha −1 ) and net profits ($\$$83 to $\$$1211.5 ha −1 ) was observed. All fields were profitable in all site-years. When low profit occurred, it was explained by limited management experience of the crop in Iowa. The breakeven yield at a selling price of $\$$130 Mg −1 varied from 9.0–12.1 Mg ha −1 at 15% moisture content (7.6–10.3 Mg DM ha −1 ). Breakeven prices ranged from $\$$73 to $\$$122.4 Mg −1 , matching ranges used in the Department of Energy Billion Ton Report (US Department of Energy, 2023). Notably, M × g yield and profits were commensurate with grain crops particularly with favorable precipitation. This study provides insight on the M × g management “learning curve”, performance on marginal land and in drought conditions, and demonstrates that addressing yield gaps, reducing costs, and implementing precision agriculture strategies can enhance profitability. These findings emphasize the value of remote sensing technologies in guiding sustainable and competitive commercial-scale M × g production.

60 APPLIED LIFE SCIENCES↗

Rapid Evaluation of Amine-Functionalized Solvents for Biomass Deconstruction Using High-Throughput Screening and One-Pot Enzymatic Saccharification

Efficient and sustainable pretreatment of lignocellulosic biomass is critical for biofuel and biochemical production, yet its optimization is often hindered by slow, labor-intensive experimental methods. Here, we report the first demonstration of a custom-built, miniaturized, high-throughput screening platform integrated with one-pot enzymatic saccharification, enabling parallel evaluation of solvent type, feedstock, and temperature with minimal material use and high reproducibility. As a proof-of-concept, the HTX platform was used to screen five amine-functionalized solvents, including isopropanolamine, butylamine, N-methylbutylamine, ethanolamine, and ethanolamine acetate across three bioenergy crops (sorghum, poplar, and switchgrass) and pretreatment temperatures ranging from 80 to 140 °C. Vacuum drying successfully removed more than 99% of the solvents from the pretreated biomass, eliminating the need for water washing prior to saccharification. Isopropanolamine and N-methylbutylamine yielded the highest glucose (70–80%) and xylose (58–67%) release, with trends reflecting feedstock recalcitrance. The produced hydrolysates supported robust growth of an engineered strain of the yeast Rhodosporidium toruloides, confirming biocompatibility. This high-throughput platform provides a scalable, feedstock-agnostic framework for rapid pretreatment screening, accelerating solvent–feedstock pairing and process optimization. Its ability to integrate pretreatment, solvent removal, saccharification, and microbial conversion in a miniaturized format offers significant advantages for cost-competitive biorefinery development.

Biomass↗

Supporting Information for manuscript: “A latitudinal gradient in S/G lignin monomer ratio driven by laccase in natural poplar variants”

Lignin composition plays a crucial role in plant structural integrity and environmental adaptation. However, the genetic and molecular mechanisms underlying natural variation in lignin composition remain poorly understood. This study investigates the syringyl-to-guaiacyl (S/G) lignin monomer ratio across a natural population of Populus trichocarpa spanning a latitudinal gradient along the Northwest coast of North America. By integrating biochemical, genomic, and geographic analysis, we identify key gene variants associated with S/G ratio differences. These datasets provide valuable insights into the evolutionary and functional genomics of lignin composition and serve as a resource for developing poplar variants optimized for forestry and bioenergy applications.

Poplar, lignin composition, laccases, latitude, ad↗

Transgenic Sugarcane–Oilcane: An Alternative Feedstock for the Production of Drop-in Fuel and Value-Added Bioproducts

The utilization of plants and other agricultural produce can partly offset petroleum dependency for energy requirements and can potentially provide sustainable solutions to global environmental problems. To this end, synthetic biology has shown great potential in developing transgenic bioenergy grasses such as sugarcane, sorghum, miscanthus, and energy cane that hyperaccumulate energy-rich lipid molecules in their vegetative tissues, such as leaves, stems, and roots. These perennial high-biomass transgenic C4 grasses are not targeted to grow on prime agricultural land and can be dedicatedly used to produce biofuels and other value-added bioproducts. Recently, sugarcane has been metabolically engineered to sequestrate carbon from juice towards biosynthesis of lipid molecules in the vegetative tissues. Transgenic sugarcane is referred to as “oilcane.” Transgenic sugarcane–oilcane has improved energy density due to an elevated lipid content in the vegetative tissues. Transgenic bioenergy crops cater to both cellulosic sugars and vegetative lipids, hence resulting in higher biofuel yield (biodiesel/renewable diesel and bioethanol) per unit area of cultivable land. In this book chapter, the genetic engineering of sugarcane and its bioprocessing are discussed to illustrate its development and use as an alternative feedstock for the production of biofuels (bio-jet fuel, biodiesel, and bioethanol) and value-added bioproducts.

Maitra, Shraddha↗

Leveraging hyperspectral phenotyping for accurate, non-destructive prediction of metabolite profiles in poplar under drought stress

Accurately predicting drought tolerance in woody perennial bioenergy crops is critical for sustainable biomass production under fluctuating precipitation. Hyperspectral imaging (HSI) in the visible-near-infrared (VNIR) and shortwave-infrared (SWIR) ranges offers a promising approach for predicting plant biochemical traits, yet its application in metabolite profiling remains underexplored. We integrated VNIR+SWIR HSI with untargeted metabolomics to investigate drought-induced metabolic shifts in Populus leaves from eight Populus genotypes. Metabolite profiling identified 127 compounds, with 73 showing significant drought responses spanning amino acids (AA), carbohydrates (CHO), phenolic glycosides (PG), organic acids (OA), fatty acids and alcohols (FA), terpenes (T), phenolic metabolites (P), and unclassified metabolites. Spectral analysis revealed consistently higher reflectance across VNIR and SWIR wavelengths in drought-stressed plants, corresponding with increased accumulation of AA and reduced CHO and PG levels. Least absolute shrinkage and selection operator (LASSO) regression modeling identified robust spectral predictors of metabolite concentrations, associating VNIR wavelengths (500–700 nm) predominantly with AA and P, whereas SWIR wavelengths (1680–1700 nm) reliably predicted CHO, OA, and T. Several stable spectral-metabolite associations persisted across the two watering regimes (drought vs. well-watered), highlighting their potential as spectral biomarkers for non-destructive stress monitoring. Minimal genotype-specific variation suggests that observed spectral and metabolic responses were driven primarily by environmental factors, likely reflecting limited genetic diversity among the commercial Populus genotypes examined. This work establishes VNIR+SWIR hyperspectral imaging as a powerful, non-destructive phenotyping tool for precision monitoring and targeted improvement of drought resilience in bioenergy crops.

Biochemical trait prediction↗

Impact of low-chemical storage pretreatment of loblolly pine bark on biochar from microwave pyrolysis

Forest product residues such as bark represent a low-cost, abundant feedstock for bioenergy, but their high ash and alkali and alkaline earth metal (AAEM) content limit thermochemical conversion efficiency. This study evaluates the use of low-severity chemical pretreatments during anaerobic storage to improve the performance of microwave pyrolysis for loblolly pine bark. Bark was treated with dilute sulfuric acid (0.1% and 1%, w/w) or sodium hydroxide (4%, w/w) and incubated anaerobically for one or two weeks to simulate in-pile biorefinery storage. The most effective treatment—1% H2SO4 for two weeks—reduced AAEM content by 35.7% and increased bio-oil yield by 11% compared to untreated controls, while also reducing pyrolysis gas production. In contrast, alkali treatment did not reduce AAEM levels and led to decreased bio-oil yields with increased gas formation. Although biochar yields were relatively stable across treatments, their physicochemical characteristics varied significantly. Acid-treated bark yielded biochars with higher carbon content, lower O/C and H/C ratios, greater surface area, and enhanced heating values. These improvements suggest that chemical pretreatment during storage can tailor biochar quality for specific end uses. Biochars produced under optimized conditions exhibited properties suitable for soil amendment, carbon sequestration, and solid fuel applications. This integrated approach—combining storage, mild chemical conditioning, and microwave pyrolysis—provides a viable pathway to enhance the value and sustainability of bark-derived bioenergy products.

09 - BIOMASS FUELS↗

Biomass to bio-energy supply chain: Economic viability, case studies, challenges and policy implications in India

Biomass supply chain (BSC) management is an integral part of renewable energy projects, which include biomass-harvesting, collection, storage, processing and transportation to the bio-energy plants. The sustainability concept identifies economy, environment, and society as the three principal pillars of bioenergy. With an effective BSC implemented, all three dimensions of sustainability can be attained. Although, there’s been extensive research on the environmental sustainability of BSC, the economic aspects are under-represented in existing literature. So, an elaborate analysis on the economic viability of BSCs developed worldwide and those in India is critical, and needs to be studied. This review conducts a detailed accounting of the economic aspects of a BSC which includes the existing challenges in designing an environmental-cum-economically efficient BSC and strategies to address the issues. The Indian context has been studied on the BSC models, highlighting their shortcomings, while encapsulating the essential insights from global BSC models for a cost-effective BSC-to-bioenergy in India. Here, this review also emphasizes the policies supporting the BSC in India and forecasts the future biomass demand and supply. This review will provide stakeholders with critical insights on BSC and related challenges and assist them to investigate and devise strategies for successful implementation of BSCs in India.

Biomass↗

Hemicellulose Modulates Nanoscale Lignin Architecture in Synthetic Plant Cell Walls

Cellulose, hemicellulose, and lignin─the most abundant biopolymers on Earth─compose the structural matrix of plant biomass, providing renewable resources critical to bioenergy and sustainable materials. Despite their importance, the nanoscale mechanochemical processes underlying lignocellulose assembly during plant secondary cell wall formation remain poorly understood, hindering advancements in biomass conversion technologies. Here, in this study, we synthesize a biomimetic model system comprising cellulose–hemicellulose nanofibrils (CHN) to examine guaiacyl lignin polymerization in a physiologically relevant context. Using advanced nanocharacterization─scattering-type scanning near-field optical microscopy (s-SNOM) with infrared nanospectroscopy coupled to solid-state nuclear magnetic resonance (NMR)─we reveal that hemicellulose presence considerably modulates lignin deposition and alters its interunit bond distribution. Specifically, hemicellulose-rich environments dramatically reduce lignin deposition by approximately 50% and yield highly condensed lignin structures characterized by severely reduced β–O–4′ linkages (<2%) and suppressed β–β′ linkages. Conversely, cellulose-alone scaffolds support notably higher β–O–4′ content (∼10%), resulting in a more uniform nanoscale lignin coating. Our work helps explain how accessible hemicellulose sites, both sterically and chemically, direct radical coupling during lignification, fundamentally reshaping lignin’s nanoscale architecture. These findings deepen our mechanistic understanding of plant cell wall biosynthesis and inform strategies aimed at enhancing biomass deconstruction efficiency for sustainable bioenergy applications.

NMR↗