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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

Bioenergy and Climate Change in Ukraine: How climate can impact the sustainability of bioenergy production

The Russian invasion has exacerbated Ukraine’s energy security issues, prompting a shift toward diversifying energy supply sources. Additionally, strategic documents aim to align Ukraine’s energy system with EU climate requirements, focusing on reducing reliance on fossil fuels and advancing decarbonization efforts. This report focuses on the expansion of bioenergy as an alternative source of energy in Ukraine. Current assessments suggest that Ukraine has substantial bioenergy potential, primarily from agricultural residues and energy crops. However, the challenges posed by climate change and the ongoing war might impact the outcome of these projections. This report highlights the importance of integrating climate factors into energy modeling using tools like the integrated assessment models to provide a comprehensive understanding of Ukraine’s bioenergy potential under various climate scenarios. It also emphasizes the need for climate-smart agriculture and forestry practices to mitigate risks, enhance energy efficiency, and support resilient crop supplies. Recommendations for stakeholders include diversification of the energy supply sources, developing adaptation strategies, diversifying bioenergy feedstocks, and ensuring robust decision-making to navigate the impacts of climate change on Ukraine’s energy system.

09 BIOMASS FUELS↗
DOE OSTI2026

The U.S. Agrivoltaic Shading Tool: A National-Scale Interface for Modeling Light and Shade Patterns in Ten Common Agrivoltaic Configurations

Agrivoltaic systems are dual-use configurations that co-locate agriculture and photovoltaic (PV) infrastructure and require careful design to balance crop performance and energy generation. A critical element of agrivoltaic design is the spatial and temporal distribution of irradiance and shade within and around PV arrays. To support research, planning, and stakeholder decision-making, we introduce the U.S. Agrivoltaic Shading Tool, a novel web-based application that delivers high-resolution irradiance and photosynthetically active radiation (PAR) modeling for ten standardized PV configurations across the conterminous United States. The tool leverages the National Laboratory of the Rockies (NLR) System Advisor Model (SAM) to perform detailed irradiance simulations, using meteorological data from the National Solar Radiation Database (NSRDB). Outputs include seasonal, monthly, weekly, and diurnal patterns of available sunlight, amount of shade, irradiance, and PAR at ground level within agrivoltaic system footprints. For a user's selected location, these results are visualized through interactive visualizations, heatmaps, and time-series plots, designed to be accessible to both technical and non-technical users. In addition to facilitating rapid spatial exploration of agrivoltaic light environments, the tool will offer seamless integration with the InSPIRE Agrivoltaics Design and Analysis Model (ADAM). This optional workflow will allow users to port selected site and configuration parameters into a more advanced modeling environment for further customization of structural layouts, crop-system compatibility, power generation, and technoeconomic performance. Finally, to promote open science, the entire dataset will be hosted and available for open access through the OpenEI platform. By standardizing and disseminating high-quality irradiance data and design tools, the U.S. Agrivoltaic Shading Tool supports a wide range of users, including researchers, landowners, energy developers, and policymakers, in evaluating the agronomic and energetic feasibility of agrivoltaic systems across the United States.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

California Price Response Potential Study

California's energy landscape is undergoing a significant transformation, driven by the increasing integration of renewable energy sources, the increased adoption of distributed energy resources, the electrification of end-use loads, and the growing need for grid efficiency. To address these challenges, recent revisions to the State’s Load Management Standards (LMS) require all of California’s large utilities and community choice aggregators (CCAs) to offer dynamic electricity pricing options to customers by 2027. Dynamic pricing, which involves varying electricity rates based on real-time supply and demand conditions, offers a promising solution for optimizing grid operations, reducing costs, and incentivizing efficient use of grid capacity. Effective implementation of dynamic pricing requires understanding the potential impacts on customer bills, system load, and the cost-effectiveness of automation technologies. This study aims to evaluate the load response of various end-use devices to hourly dynamic prices. The end-uses studied here are space cooling, space heating, water heating, crop irrigation, pool and spa pumps, and electric vehicle (EV) charging, all for both residential and commercial applications, except for crop irrigation. In 2030, these end uses are forecasted to account for 18% of annual electricity demand in the state, but 40% of demand in the peak net load hour. By modeling possible price-responsive load dispatch algorithms and assessing the resulting impacts on both individual bills and the overall grid, we seek to inform policymakers and utilities about the potential benefits and challenges associated with dynamic pricing, and considerations for the design of dynamic pricing tariffs. Additionally, we will explore the cost effectiveness of adopting automation technologies to enable devices to respond more effectively to real-time price signals. This study considers a range of price profiles, accounting for differences across utilities and customer classes, and presents scenarios for dynamic price design via variation in the percentage of total customer electric costs that are allocated dynamically (versus constituting a fixed portion of the hourly volumetric price). We present results focused primarily on 2030, forecasting electricity prices under both low and high-cost scenarios, to inform longer-term tariff design considerations. We design tariffs by starting with 2019 prices that were calculated according to CalFUSE guidance (CPUC, 2022) and that have been used in recent studies; these prices are all-in volumetric rates that vary by utility and are revenue-neutral to each customer class. They are developed by considering six electricity cost components that are allocated hourly based on system load indicators (gross and net load, and wholesale prices). These prices are forecasted to 2030 for low and high cost scenarios, considering recent trends in total electricity costs with and without years of substantial wildfire mitigation investments. These tariffs, which allocate all costs on an hourly basis, are considered our “Full” dynamic tariff design scenario, while two additional scenarios explore allocating a portion of costs as a flat volumetric charge: the “Medium” scenario allocates 50% of revenue dynamically (and keeps 50% flat), while the “Mild” scenario allocates 20% of revenue dynamically. The 20% dynamic allocation on the Mild scenario aims to represent a case where only the marginal operating costs of the grid are included in the dynamic price.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

A KBase Case Study on Genome-wide Transcriptomics and Plant Primary Metabolism in Sorghum

A better understanding of the genetic and metabolic mechanisms that confer stress resistance and tolerance in plants is key to engineering new crops through advanced breeding technologies. This requires a systems biology approach that builds on a genome-wide understanding of the regulation of gene expression, plant metabolism, physiology and growth. In this study, we examine the response to drought stress in Sorghum, as we leverage the tools for transcriptomics and plant metabolic modeling we have implemented at the U.S. Department of Energy Systems Biology Knowledgebase (KBase). KBase enables researchers worldwide to collaborate and advance research by allowing them to upload private or public data into the KBase Narrative Interface, empowering them to analyze this data using a rich, extensible array of computational and data-analytics tools, and allows them to securely share scientific workflows and conclusions. We demonstrate how to use the current RNA-seq tools in KBase, applicable to both plants and microbes, to assemble and quantify long transcripts and identify differentially expressed genes effectively. More specifically, we demonstrate the utility of the platform by identifying key genes that are differentially expressed during drought-stress in Sorghum bicolor, which is an important sustainable production crop plant. We then show how to use KBase tools to predict the membership of genes in metabolic pathways and examine expression data in the context of metabolic subsystems. We demonstrate the power of the platform by making the data analysis and interpretation available to the biologists in the reproducible, re-usable, point-and-click format of a KBase Narrative thus promoting FAIR (Findable, Accessible, Interoperable and Reusable) guiding principles for scientific data management and stewardship.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Soil nutrients affect biomass allocation at the individual tree level in Populus_deltoides

The allocation of carbon (C) to tree roots has implication for forest productivity and soil C storage. Here, we elucidated the factors affecting absolute and relative production of resource-acquiring absorptive fine roots (AFR) and other tree organs. We assessed soil properties, leaf (Leaves), stem and branch (Stem-Br), coarse root (CR), transport fine root (TFR), and AFR biomass, production, and allocation and leaf litterfall and AFR and TFR turnover for 12 trees in a youngPopulus deltoides plantation. On a biomass basis, standing crop of AFRs was significantly related to that of TFRs, but both were independent of biomass of leaves, CRs and Stem-Brs. Production (standing crop + turnover) as a proportion of total biomass (allocation) highlighted significant relationships between AFR%, TFR%, and tree and soil characteristics. AFR% and TFR% were negatively correlated with Stem-Br%, Leaf%, and total tree production. Spatial variation in soil nutrient gradients altered allocation withinP. deltoides.AFR% and TFR% were negatively correlated with CEC, N, and Ca but positively correlated with soil P, Fe, and Na. Stem-Br% was positively correlated with CEC and soil N but negatively correlated with P. AFR and TFR growth and death are tightly coupled at the individual tree level. AFR allocation, but not standing biomass, is highly correlated with allocation to leaves, suggesting tight regulation of the growth of these two resource-acquiring organs. Lower soil N and Ca increased allocation to AFRs at the cost of leaves, whereas allocation to AFRs and leaves increased with soil P. Such changes in response to soil P may control whole-tree production in the current study.

Biomass allocation↗
DOE OSTI2021

SLOPE daily and 250 m gross primary productivity (GPP) for the CONUS, 2000-2019, Carbon Monitoring System (CMS)

The SatelLite Only Photosynthesis Estimation (SLOPE) GPP product is a daily, 250 m GPP dataset covering the Contiguous United States (CONUS) from 2000 to present with 1 day latency. 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. This product has been developed to address this critical gap, leveraging a number of MODIS land and atmosphere products. There are three distinct features of the SLOPE GPP production algorithm. (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 Crop Data Layer (CDL) product to predict dynamic C4 crop fraction. PAR, SANIRv and C4 fraction are used to drive a parsimonious model with only two slope parameters to estimate GPP along with a quantitative uncertainty on a per-pixel and daily basis. The slope GPP product has a R2 = 0.84 and a root-mean-square error (RMSE) of 1.65 gC m-2 d-1, evaluated against from 50 AmeriFlux eddy covariance sites (332 site-years). Archived data from 2000 to 2019 are publicly available at the NASA's Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC). Data from 2020 are available from the authors upon request. All data are projected in the standard MODIS Land Integerized Sinusoidal tile map projection. Each processing tile is in size of 4800 pixels by 4800 pixels, representing approximately 1200 km by 1200 km land region. In addition to the GPP product, SLOPE PAR, SANIRV, and C4 fraction, along with their uncertainties, are also released.

Jiang, Chongya↗
DOE OSTI2026

CRISPR/Cas9-Mediated Multi-Allelic Gene Targeting in Sugarcane Confers Herbicide Tolerance

Sugarcane is the source of 80% of the sugar and 26% of the bioethanol produced globally. However, its complex, highly polyploid genome (2n = 100 – 120) impedes crop improvement. Here, we report efficient and reproducible gene targeting (GT) in sugarcane, enabling precise co-editing of multiple alleles via template-mediated and homology-directed repair (HDR) of DNA double strand breaks induced by the programmable nuclease CRISPR/Cas9. The evaluation of 146 independently transformed plants from five independent experiments revealed a targeted nucleotide replacement that resulted in both targeted amino acid substitutions W574L and S653I in the acetolactate synthase (ALS) in 11 lines in addition to single, targeted amino acid substitutions W574L or S653I in 25 or 18 lines, respectively. Co-editing of up to three ALS copies/alleles that confer herbicide tolerance was confirmed by Sanger sequencing of cloned long polymerase chain reaction (PCR) amplicons. This work will enable crop improvement by conversion of inferior alleles to superior alleles through targeted nucleotide substitutions.

Altpeter, Fredy (ORCID:0000000208944976)↗
DOE OSTI2021

Revisiting “Additional Carbon”: Tracking Atmosphere–Ecosystem Carbon Exchange to Establish Mitigation and Negative Emissions From Bio-Based Systems

Climate stabilization plans rely heavily on advanced bioenergy and bioproducts for substitution of fossil-based energy sources and materials, and increasingly, for negative emissions via the direct sequestration of biogenic carbon. Yet, there remain persistent, largely unresolved critiques of bioenergy assessment methodology, particularly in the areas of land use and biogenic carbon accounting. The concept of “additional carbon” calls for evaluating the climate performance of bio-based systems by whether feedstock production creates measurable new local agro-ecosystem uptake of carbon from the atmosphere. This concept is challenging to operationalize for first-generation biofuels, and has largely been advanced as a negative critique. However, carbon additionality is more straightforward to establish—and less critical to overall system mitigation performance—in advanced bioenergy systems. In this Perspective, I review the additional carbon critique, and why it is analytically challenging to address in first-generation biofuel systems based on conventional food crops with large existing markets. Next, I make a case that carbon additionality (1) is more readily achievable with cellulosic feedstocks, (2) is more directly observable for dedicated biomass crops, and (3) is not a strict requirement for achieving net mitigation in carbon-negative bio-based systems. I end by discussing how centering atmosphere–ecosystem carbon exchanges in bio-based system assessment could create new opportunities for enterprise-scale performance monitoring and verification, augmenting and diversifying the current reliance on model-based life-cycle assessment approaches.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Are long-term climate projections useful for on-farm adaptation decisions?

The current literature on climate services for farmers predominantly focuses on seasonal forecasts, with an assumption that longer-term climate projections may not be suitable for informing farming decisions. In this paper, we explore whether certain types of long-term climate projections may be useful for some specific types of farming decisions. Through interviews with almond tree crop farmers and farm advisors in California, we examine how farmers perceive the utility and accuracy levels of long-term climate projections and identify the types of projections that they may find useful. The interviews revealed that farmers often perceive long-term climate projections as an extension of weather forecasts, which can lead to their initial skepticism of the utility of such information. However, we also found that when farmers were presented with long-term trends or shifts in crop-specific agroclimatic metrics (such as chill hours or summer heat), they immediately perceived these as valuable for their decision-making. Hence, the manner in which long-term projections are framed, presented, and discussed with farmers can heavily influence their perception of the potential utility of such projections. The iterative conversations as part of the exploratory interview questions, served as a tool for “ joint construction of meaning” of complex and ambiguous terms such as “long-term climate projections,” “long-term decisions” and “uncertainty.” This in-turn supported a joint identification (and understanding) of the types of information that can potentially be useful for on-farm adaptive decisions, where the farmer and the interviewer both improvise and iterate to find the best types of projections that fit specific decision-contexts. Overall, this research identifies both the types of long-term climate information that farmers may consider useful, and the engagement processes that are able to effectively elicit farmers' long-term information needs.

Jagannathan, Kripa↗
DOE OSTI2022

Editorial: Exogenous carbon-based materials in soil ecosystems

Various exogenous carbon-based materials (ECMs) such as crop straw, biochar, carbon-based nano-fertilizer, and microplastics have accumulated in soil ecosystems. These ECMs may cause direct and indirect impacts on soil properties, processes, productivity, and health, thus potentially changing the function and stability of soil ecosystems. However, large knowledge gaps still exist on ECMs in soil ecosystems, including their accumulation, interactions with soil components, and potential ecological impacts and risks. Therefore, more efforts are needed to further understand the impacts especially the long-term effects of ECMs in soil ecosystems. By generating new knowledge, this Research Topic aims to improve the understanding of the effects of ECMs on soil ecosystems, including soil quality, nutrient cycling, microbial ecology, crop growth, environmental health and ecological risk.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

CRISPR/Cas9-Mediated Multi-Allelic Gene Targeting in Sugarcane Confers Herbicide Tolerance

Sugarcane is the source of 80% of the sugar and 26% of the bioethanol produced globally. However, its complex, highly polyploid genome (2 n = 100 – 120) impedes crop improvement. Here, we report efficient and reproducible gene targeting (GT) in sugarcane, enabling precise co-editing of multiple alleles via template-mediated and homology-directed repair (HDR) of DNA double strand breaks induced by the programmable nuclease CRISPR/Cas9. The evaluation of 146 independently transformed plants from five independent experiments revealed a targeted nucleotide replacement that resulted in both targeted amino acid substitutions W574L and S653I in the acetolactate synthase (ALS) in 11 lines in addition to single, targeted amino acid substitutions W574L or S653I in 25 or 18 lines, respectively. Co-editing of up to three ALS copies/alleles that confer herbicide tolerance was confirmed by Sanger sequencing of cloned long polymerase chain reaction (PCR) amplicons. This work will enable crop improvement by conversion of inferior alleles to superior alleles through targeted nucleotide substitutions.

(Saccharum hybrid complex)↗
DOE OSTI2025

Scaffolded and annotated nuclear and organelle genomes of the North American brown alga Saccharina latissima

Increasing the genomic resources of emerging aquaculture crop targets can expedite breeding processes as seen in molecular breeding advances in agriculture. High quality annotated reference genomes are essential to implement this relatively new molecular breeding scheme and benefit research areas such as population genetics, gene discovery, and gene mechanics by providing a tool for standard comparison. The brown macroalga Saccharina latissima (sugar kelp) is an ecologically and economically important kelp that is found in both the northern Pacific and Atlantic Oceans. Cultivation of Saccharina latissima for human consumption has increased significantly this century in both North America and Europe, and its single blade morphology allows for dense seeding practices used in the cultivation of its Asian sister species, Saccharina japonica. While Saccharina latissima has potential as a human food crop, insufficient information from genetic resources has limited molecular breeding in sugar kelp aquaculture. We present scaffolded and annotated Saccharina latissima nuclear and organelle genomes from a female gametophyte collected from Black Ledge, Groton, Connecticut. This Saccharina latissima genome compares well with other published kelp genomes and contains 218 scaffolds with a scaffold N50 of 1.35 Mb, a GC content of 49.84%, and 25,012 predicted genes. We also validated this genome by comparing the synteny and completeness of this Saccharina latissima genome to other kelp genomes. Our team has successfully performed initial genomic selection trials with sugar kelp using a draft version of this genome. This Saccharina latissima genome expands the genetic toolkit for the economically and ecologically important sugar kelp and will be a fundamental resource for future foundational science, breeding, and conservation efforts.

DeWeese, Kelly↗
DOE OSTI2020

The Utility of Satellites and Autonomous Remote Sensing Platforms for Monitoring Offshore Aquaculture Farms: A Case Study for Canopy Forming Kelps

The emerging sector of offshore kelp aquaculture represents an opportunity to produce biofuel feedstock to help meet growing energy demand. Giant kelp represents an attractive aquaculture crop due to its rapid growth and production, however precision farming over large scales is required to make this crop economically viable. These demands necessitate high frequency monitoring to ensure outplant success, maximum production, and optimum quality of harvested biomass, while the long distance from shore and large necessary scales of production makes in person monitoring impractical. Remote sensing offers a practical monitoring solution and nascent imaging technologies could be leveraged to provide daily products of the kelp canopy and subsurface structures over unprecedented spatial scales. Here, we evaluate the efficacy of remote sensing from satellites and aerial and underwater autonomous vehicles as potential monitoring platforms for offshore kelp aquaculture farms. Decadal-scale analyses of the Southern California Bight showed that high offshore summertime cloud cover restricts the ability of satellite sensors to provide high frequency direct monitoring of these farms. By contrast, daily monitoring of offshore farms using sensors mounted to aerial and underwater drones seems promising. Small Unoccupied Aircraft Systems (sUAS) carrying lightweight optical sensors can provide estimates of canopy area, density, and tissue nitrogen content on the time and space scales necessary for observing changes in this highly dynamic species. Underwater color imagery can be rapidly classified using deep learning models to identify kelp outplants on a longline farm and high acoustic returns of kelp pneumatocysts from side scan sonar imagery signal an ability to monitor the subsurface development of kelp fronds. Current sensing technologies can be used to develop additional machine learning and spectral algorithms to monitor outplant health and canopy macromolecular content, however future developments in vehicle and infrastructure technologies are necessary to reduce costs and transcend operational limitations for continuous deployment in an offshore setting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Molecular mechanism of Rubisco activase: Dynamic assembly and Rubisco remodeling

Ribulose-1,5-bisphosphate (RuBP) carboxylase-oxygenase (Rubisco) enzyme is the limiting step of photosynthetic carbon fixation, and its activation is regulated by its co-evolved chaperone, Rubisco activase (Rca). Rca removes the intrinsic sugar phosphate inhibitors occupying the Rubisco active site, allowing RuBP to split into two 3-phosphoglycerate (3PGA) molecules. This review summarizes the evolution, structure, and function of Rca and describes the recent findings regarding the mechanistic model of Rubisco activation by Rca. New knowledge in these areas can significantly enhance crop engineering techniques used to improve crop productivity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Drought Drives Spatial Variation in the Millet Root Microbiome

Efforts to boost crop yield and meet global food demands while striving to reach sustainability goals are hindered by the increasingly severe impacts of abiotic stress, such as drought. One strategy for alleviating drought stress in crops is to utilize rootassociated bacteria, yet knowledge concerning the relationship between plant hosts and their microbiomes during drought remain under-studied. One broad pattern that has recently been reported in a variety of monocot and dicot species from both native and agricultural environments, is the enrichment of Actinobacteria within the drought-stressed root microbiome. In order to better understand the causes of this phenomenon, we performed a series of experiments in millet plants to explore the roles of drought severity, drought localization, and root development in provoking Actinobacteria enrichment within the root endosphere. Through 16S rRNA ampliconbased sequencing, we demonstrate that the degree of drought is correlated with levels of Actinobacterial enrichment in four species of millet. Additionally, we demonstrate that the observed drought-induced enrichment of Actinobacteria occurs along the length of the root, but the response is localized to portions of the root experiencing drought. Finally, we demonstrate that Actinobacteria are depleted in the dead root tissue of Japanese millet, suggesting saprophytic activity is not the main cause of observed shifts in drought-treated root microbiome structure. Collectively, these results help narrow the list of potential causes of drought-induced Actinobacterial enrichment in plant roots by showing that enrichment is dependent upon localized drought responses but not root developmental stage or root death.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Silencing Folylpolyglutamate Synthetase1 (FPGS1) in Switchgrass (Panicum virgatum L.) Improves Lignocellulosic Biofuel Production

Switchgrass (Panicum virgatum L.) is a lignocellulosic perennial grass with great potential in bioenergy field. Lignocellulosic bioenergy crops are mostly resistant to cell wall deconstruction, and therefore yield suboptimal levels of biofuel. The one-carbon pathway (also known as C1 metabolism) is critical for polymer methylation, including that of lignin and hemicelluloses in cell walls. Folylpolyglutamate synthetase (FPGS) catalyzes a biochemical reaction that leads to the formation of folylpolyglutamate, an important cofactor for many enzymes in the C1 pathway. In this study, the putatively novel switchgrass PvFPGS1 gene was identified and its functional role in cell wall composition and biofuel production was examined by RNAi knockdown analysis. The PvFPGS1-downregulated plants were analyzed in the field over three growing seasons. Transgenic plants with the highest reduction in PvFPGS1 expression grew slower and produced lower end-of-season biomass. Transgenic plants with low-to-moderate reduction in PvFPGS1 transcript levels produced equivalent biomass as controls. There were no significant differences observed for lignin content and syringyl/guaiacyl lignin monomer ratio in the low-to-moderately reduced PvFPGS1 transgenic lines compared with the controls. Similarly, sugar release efficiency was also not significantly different in these transgenic lines compared with the control lines. However, transgenic plants produced up to 18% more ethanol while maintaining congruent growth and biomass as non-transgenic controls. Severity of rust disease among transgenic and control lines were not different during the time course of the field experiments. Altogether, the unchanged lignin content and composition in the low-to-moderate PvFPGS1-downregulated lines may suggest that partial downregulation of PvFPGS1 expression did not impact lignin biosynthesis in switchgrass. In conclusion, the manipulation of PvFPGS1 expression in bioenergy crops may be useful to increase biofuel potential with no growth penalty or increased susceptibility to rust in feedstock.

59 BASIC BIOLOGICAL SCIENCES↗