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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.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Engineering temporal accumulation of a low recalcitrance polysaccharide leads to increased C6 sugar content in plant cell walls

Reduced cell wall recalcitrance and increased C6 monosaccharide content are desirable traits for future biofuel crops, as long as these biomass modifications do not significantly alter normal growth and development. Mixed-linkage glucan (MLG), a cell wall polysaccharide only present in grasses and related species among flowering plants, is comprised of glucose monomers linked by both β-1,3 and β-1,4 bonds. Previous data have shown that constitutive production of MLG in barley (Hordeum vulgare) severely compromises growth and development. Here, we used spatio-temporal strategies to engineer Arabidopsis thaliana plants to accumulate significant amounts of MLG in the cell wall by expressing the rice CslF6 MLG synthase using secondary cell wall and senescence-associated promoters. Results using secondary wall promoters were suboptimal. When the rice MLG synthase was expressed under the control of a senescence-associated promoter, we obtained up to four times more glucose in the matrix cell wall fraction and up to a 42% increase in saccharification compared to control lines. Importantly, these plants grew and developed normally. The induction of MLG deposition at senescence correlated with an increase of gluconic acid in cell wall extracts of transgenic plants in contrast to the other approaches presented in this study. MLG produced in Arabidopsis has an altered structure compared to the grass glucan, which likely affects its solubility, while its molecular size is unaffected. The induction of cell wall polysaccharide biosynthesis in senescing tissues offers a novel engineering alternative to enhance cell wall properties of lignocellulosic biofuel crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Convergent evolution of hetero-oligomeric cellulose synthesis complexes in mosses and seed plants

In seed plants, cellulose is synthesized by rosette-shaped Cellulose Synthesis Complexes (CSCs) that are obligate hetero-oligomeric, comprising three non-interchangeable Cellulose Synthase (CESA) isoforms. The moss Physcomitrella patens has rosette CSCs and seven CESAs, but its common ancestor with seed plants had rosette CSCs and a single CESA gene. Thus, if P. patens CSCs are hetero-oligomeric, then CSCs of this type evolved convergently in mosses and seed plants. Previous gene knockout and promoter swap experiments showed that PpCESAs from class A (PpCESA3 and PpCESA8) and class B (PpCESA6 and PpCESA7) have non-redundant functions in secondary cell wall cellulose deposition in leaf midribs, whereas the two members of each class are redundant. Based on these observations, we proposed the hypothesis that the secondary class A and class B PpCESAs associate to form hetero-oligomeric CSCs. Here we show that transcription of secondary class A PpCESAs is reduced when secondary class B PpCESAs are knocked out and vice versa, as expected for genes encoding isoforms that occupy distinct positions within the same CSC. The class A and class B isoforms co-accumulate in developing gametophores and co-immunoprecipitate, suggesting that they interact to form a complex in planta. Finally, secondary PpCESAs interact with each other, whereas three of four fail to self interact when expressed in two different heterologous systems. These results are consistent with the hypothesis that obligate hetero-oligomeric CSCs evolved independently in mosses and seed plants and we propose the constructive neutral evolution hypothesis as a plausible explanation for convergent evolution of hetero-oligomeric CSCs. This article is protected by copyright. All rights reserved.

biofuels (including algae and biomass), bio-inspir↗
DOE OSTI2020

Architecture of a catalytically active homotrimeric plant cellulose synthase complex

Cellulose is an essential plant cell wall component and represents the most abundant biopolymer on Earth. Supramolecular plant cellulose synthase complexes organize multiple linear glucose polymers into microfibrils as load-bearing wall components. We determined the structure of a poplar cellulose synthase CesA homotrimer that suggests a molecular basis for cellulose microfibril formation. This complex, stabilized by cytosolic plant-conserved regions and helical exchange within the transmembrane segments, forms three channels occupied by nascent cellulose polymers. Secretion steers the polymers toward a common exit point, which could facilitate protofibril formation. CesA’s N-terminal domains assemble into a cytosolic stalk that interacts with a microtubule-tethering protein and may thus be involved in CesA localization. Here, our data suggest how cellulose synthase complexes assemble and provide the molecular basis for plant cell wall engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

WPGNN and PLayGen (Wind Plant Graph Neural Network and Plant Layout Generator) [SWR-21-90]

WPGNN is the graph neural network machine learning based surrogate model and software that provides a streamlined approximation of wind plant wake models. It can rapidly estimate the energy production of the plant and turbines for any arbitrarily sized wind plant and layout under any inflow condition. Associated tools include graphing and visualization capabilities as well as a wind plant generator capable of creating randomized realizations of canonical wind plant layouts. The WPGNN architecture and application is extendable to multiple wake models, turbine technologies and features, and supports downstream optimizations of wind plant layouts and control strategies. In addition to the WPGNN, we include the code for the plant layout generator (PLayGen) playgen.py. This generator can produce random realizations of realistic wind plant layouts from one of the four canonical styles: cluster, single string, multiple string, or parallel string. The PLayGen_demo.ipynb notebook provides a demonstration of how to use the generator tool.

Harrison-Atlas, Dylan↗
DOE OSTI2015

Enrichment and Broad Representation of Plant Biomass-Degrading Enzymes in the Specialized Hyphal Swellings of Leucoagaricus gongylophorus, the Fungal Symbiont of Leaf-Cutter Ants

Leaf-cutter ants are prolific and conspicuous Neotropical herbivores that derive energy from specialized fungus gardens they cultivate using foliar biomass. The basidiomycetous cultivar of the ants, Leucoagaricus gongylophorus, produces specialized hyphal swellings called gongylidia that serve as the primary food source of ant colonies. Gongylidia also contain lignocellulases that become concentrated in ant digestive tracts and are deposited within fecal droplets onto fresh foliar material as it is foraged by the ants. Although the enzymes concentrated by L. gongylophorus within gongylidia are thought to be critical to the initial degradation of plant biomass, only a few enzymes present in these hyphal swellings have been identified. Here we use proteomic methods to identify proteins present in the gongylidia of three Atta cephalotes colonies. Our results demonstrate that a diverse but consistent set of enzymes is present in gongylidia, including numerous lignocellulases likely involved in the degradation of polysaccharides, plant toxins, and proteins. Overall, gongylidia contained over three-quarters of all lignocellulases identified in the L. gongylophorus genome, demonstrating that the majority of the enzymes produced by this fungus for biomass breakdown are ingested by the ants. We also identify a set of 23 lignocellulases enriched in gongylidia compared to whole fungus garden samples, suggesting that certain enzymes may be particularly important in the initial degradation of foliar material. Our work sheds light on the complex interplay between leaf-cutter ants and their fungal symbiont that allows for the host insects to occupy an herbivorous niche by indirectly deriving energy from plant biomass.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2025

HydroFish: freshwater fish co-occurrence with hydropower plants and non-powered dams in conterminous United States sub-basins

The HydroFish dataset lists all existing hydropower plants (EHAs) and non-powered dams (NPDs; ≥ 0.001 MW potential nominal capacity), delineates the hydrologic sub-basins in which they are situated, and then lists all freshwater fish species reported to occur in those sub-basins. This dataset was compiled using the HydroBio dataset (https://hydrosource.ornl.gov/data/datasets/hydrobio/) and contains 24 total variables that describe hydrologic sub-basins, each unique EHA (plant ID and name, geographic coordinates, permit type, capacity, etc.) and NPD (ID value, known names, geographic coordinates, and estimated potential nominal capacity), and freshwater fish species in the sub-basin (common and scientific name, origin, and migratory and threat status). The HydroBio dataset was built using Oak Ridge National Laboratory’s Existing Hydropower Assets Dataset (2024 version) and Non-powered Dam Technical Potential Dataset (2024 version), and NatureServe’s fish species distribution dataset (2023 version). The dataset also contains summary variables that report the unique number of EHAs, NPDs, and freshwater fish species per sub-basin. The HydroFish dataset contains two unique data files: 1) a .csv metadata file describing the dataset variables, and 2) a .csv data file containing the actual dataset. Note that there may be many rows per unique existing hydropower plant or non-powered dam given that distinct species are listed per existing plant or NPD per sub-basin. The dataset is downloadable as a zip file containing the metadata and dataset files.

Bozeman, Bryan [Oak Ridge National Laboratory (ORN↗
NASA NTRS2019

Plant Microbiomes May Provide Vital Information to Plant Success

Plant associated microbiomes, the rhizosphere and phyllosphere, are composed of communities of bacteria and fungi that may be mutualistic or pathogenic. These communities have the potential to influence plant health and development and can affect plant growth. Crop plants are being investigated as a fresh and safe supplement to astronauts’ diet and it is critical to understand and characterize these microbial communities. Multi-species crops, Mizuna mustard (Brassica rapa var japonica), ‘Outredgeous’ red romaine lettuce (Lactuca sativa), and Waldman’s Green lettuce (Lactuca sativa) were grown in two Veggie units on the International Space Station (ISS) for three grow outs in various combinations of plant types. Upon harvest, plant and pillow samples were frozen and returned to Earth for analysis. Bacterial and fungal community analyses for plant leaf and root, as well as pillow components, wick and media, were completed using next generation sequencing with the goal of surveying the composition of the entire community and identifying any potential pathogens. Bacteria were identified using the 16S rRNA gene whereas, fungi were identified with the internal transcribed spacer (ITS). The community composition for these three crops was compared between crop types and between plant tissue types. It is vital to mission success for the short term and long term to add nutritious, safe to eat vegetables providing a supplement to the crew members’ dietary requirements as well as to develop planning for deep space missions as we reach for the moon and on to Mars. Veggie technology validation tests were supported by NASA’s Space Biology Program.

Khodadad, Christina L.↗
DOE OSTI2018

PlantSEED enables automated annotation and reconstruction of plant primary metabolism with improved compartmentalization and comparative consistency

Genome-scale metabolic reconstructions help us to understand and engineer metabolism. Next-generation sequencing technologies are delivering genomes and transcriptomes for an ever-widening range of plants. While such omic data can, in principle, be used to compare metabolic reconstructions in different species, organs and environmental conditions, these comparisons require a standardized framework for the reconstruction of metabolic networks from transcript data. We previously introduced PlantSEED as a framework covering primary metabolism for 10 species. We have now expanded PlantSEED to include 39 species and provide tools that enable automated annotation and metabolic reconstruction from transcriptome data. The algorithm for automated annotation in PlantSEED propagates annotations using a set of signature k-mers (short amino acid sequences characteristic of particular proteins) that identify metabolic enzymes with an accuracy of about 97%. PlantSEED reconstructions are built from a curated template that includes consistent compartmentalization for more than 100 primary metabolic subsystems. Together, the annotation and reconstruction algorithms produce reconstructions without gaps and with more accurate compartmentalization than existing resources. These tools are available via the PlantSEED web interface at , which enables users to upload, annotate and reconstruct from private transcript data and simulate metabolic activity under various conditions using flux balance analysis. We demonstrate the ability to compare these metabolic reconstructions with a case study involving growth on several nitrogen sources in roots of four species.

Flux Balance Analysis↗
DOE OSTI2020

Ectomycorrhizal fungal diversity interacts with soil nutrients to predict plant growth despite weak plant-soil feedbacks

Background and aims Plant-soil feedbacks are the result of multiple abiotic and biotic mechanisms. However, few studies have addressed how feedbacks vary based on abiotic context or attempted to identify microbiota responsible for feedbacks. In this work, we investigated whether plant-soil feedbacks of an ectomycorrhizal tree (Quercus macrocarpa) varied based on soil nutrient status and whether fungal community composition and diversity could explain feedback patterns. Furthermore, we inoculated Q. macrocarpa seedlings with field-sampled soils taken from five soil origins – including heterospecific and conspecific trees and an old field – which were profiled using fungal DNA metabarcoding.Results Despite finding that soils associated with different hosts harbored distinct fungal communities and that fungal communities were predictive of plant growth, we did not find any significant plant-soil feedbacks regardless of fertilization status. We did find that the growth promotive effect associated with ectomycorrhizal OTU diversity was weakened with fertilization, suggesting context-dependent relations between plant growth and a guild of fungal mutualists. Our results demonstrate that the host-specific accumulation of functionally important soil microbes is not always sufficient to drive observable plant-soil feedbacks. Our data provide support for a role for ECM fungal diversity in mediating plant growth responses, though it is unclear whether this effect is direct or indirect.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Predicting plant attractiveness to coccinellids with plant trait profiling, citizen science, and common garden surveys

Lady beetles are key predators in agricultural systems and their impact can be enhanced by plant resources. Facilitation of lady beetles is a potentially effective pest management strategy but a lack of data on which plant species attract and nurture them limits implementation. Here we investigate which plant species might optimize lady beetle impact by developing a profile of plant characteristics most likely to attract lady beetles and testing if the subset of “potentially preferred” plant families exhibiting those characteristics are significantly more attractive to lady beetles than other families. This testing encompassed a combination of observations submitted to a citizen science program, the Lost Ladybug Project, and two repeated site surveys. Traits reported to be most attractive to lady beetles included the presence of trichomes that provide protection from predation, nutritional resources such as nectar or prey, and visual or chemical cues associated with those traits. Significantly more lady beetles were observed on the three plant families which most often exhibit these traits, Apiaceae, Asteraceae, and Rosaceae, than on other families. Furthermore, strategies for incorporating plants from these families into production systems to attract lady beetles and limit pest damage are discussed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Large-Eddy Simulation of Wind-Plant Aerodynamics

In this work, we present results of a large-eddy simulation of the 48 multi-megawatt turbines composing the Lillgrund wind plant. Turbulent inflow wind is created by performing an atmospheric boundary layer precursor simulation, and turbines are modeled using a rotating, variable-speed actuator line representation. The motivation for this work is that few others have done large-eddy simulations of wind plants with a substantial number of turbines, and the methods for carrying out the simulations are varied. We wish to draw upon the strengths of the existing simulations and our growing atmospheric large-eddy simulation capability to create a sound methodology for performing this type of simulation. We used the OpenFOAM CFD toolbox to create our solver. The simulated time-averaged power production of the turbines in the plant agrees well with field observations, except with the sixth turbine and beyond in each wind-aligned. The power produced by each of those turbines is overpredicted by 25-40%. A direct comparison between simulated and field data is difficult because we simulate one wind direction with a speed and turbulence intensity characteristic of Lillgrund, but the field observations were taken over a year of varying conditions. The simulation shows the significant 60-70% decrease in the performance of the turbines behind the front row in this plant that has a spacing of 4.3 rotor diameters in this direction. The overall plant efficiency is well predicted. This work shows the importance of using local grid refinement to simultaneously capture the meter-scale details of the turbine wake and the kilometer-scale turbulent atmospheric structures. Although this work illustrates the power of large-eddy simulation in producing a time-accurate solution, it required about one million processor-hours, showing the significant cost of large-eddy simulation.

17 WIND ENERGY↗
DOE OSTI2019

The Plant Ontology Facilitates Comparisons of Plant Development Stages Across Species

The Plant Ontology (PO) is a community resource consisting of standardized terms, definitions, and logical relations describing plant structures and development stages, augmented by a large database of annotations from genomic and phenomic studies. This paper describes the structure of the ontology and the design principles we used in constructing PO terms for plant development stages. It also provides details of the methodology and rationale behind our revision and expansion of the PO to cover development stages for all plants, particularly the land plants (bryophytes through angiosperms). As a case study to illustrate the general approach, we examine variation in gene expression across embryo development stages in Arabidopsis and maize, demonstrating how the PO can be used to compare patterns of expression across stages and in developmentally different species. Although many genes appear to be active throughout embryo development, we identified a small set of uniquely expressed genes for each stage of embryo development and also between the two species. Evaluating the different sets of genes expressed during embryo development in Arabidopsis or maize may inform future studies of the divergent developmental pathways observed in monocotyledonous versus dicotyledonous species. The PO and its annotation database (http://www.planteome.org) make plant data for any species more discoverable and accessible through common formats, thus providing support for applications in plant pathology, image analysis, and comparative development and evolution.

Plant Sciences↗
DOE OSTI2023

Stressing the importance of plant specialized metabolites: omics-based approaches for discovering specialized metabolism in plant stress responses

Plants produce a diverse range of specialized metabolites that play pivotal roles in mediating environmental interactions and stress adaptation. These unique chemical compounds also hold significant agricultural, medicinal, and industrial values. Despite the expanding knowledge of their functions in plant stress interactions, understanding the intricate biosynthetic pathways of these natural products remains challenging due to gene and pathway redundancy, multifunctionality of proteins, and the activity of enzymes with broad substrate specificity. In the past decade, substantial progress in genomics, transcriptomics, metabolomics, and proteomics has made the exploration of plant specialized metabolism more feasible than ever before. Notably, recent advances in integrative multi-omics and computational approaches, along with other technologies, are accelerating the discovery of plant specialized metabolism. In this review, we present a summary of the recent progress in the discovery of plant stress-related specialized metabolites. Emphasis is placed on the application of advanced omics-based approaches and other techniques in studying plant stress-related specialized metabolism. Additionally, we discuss the high-throughput methods for gene functional characterization. These advances hold great promise for harnessing the potential of specialized metabolites to enhance plant stress resilience in the future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

The human factors verification at plant startup for the AP1000 Plant - 173

The Human Factors (HF) verification at plant startup is the final HF assessment for the AP1000{sup R} HF program and is performed using the as-built plant design. This HF verification has been implemented for the China AP1000 Standard Plant. The scope and objectives of the HF verification at plant startup met the requirements for Verification and Validation (V and V) as described in NUREG-0711, 'Human Factors Engineering Program Review Model'. The majority of the verifications have been completed. Overall, the results confirmed the adequacy of the China AP1000 Standard Plant operating procedures and operator training. A number of design issues were identified and were categorized as safety issues, operability and maintainability issues or minor issues. These issues are being addressed and tracked as site test deficiencies. Based on the current results, it can be concluded that the China AP1000 Standard Plant is safe, operable and maintainable, pending completion of the outstanding verifications and resolution of the identified issues. This paper will describe the overall strategy and discuss the lessons learned in respect to providing HF support to the startup activities for the AP1000 plant. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Techno-Economic Analysis of an Intensified Integrated Gasification Combined Cycle (IGCC) Power Plant Featuring a Combined Membrane Reactor - Adsorptive Reactor (MR-AR) System

In this work, the novel concept of a combined membrane-adsorptive reactor sequence (MRAR) is developed and implemented in an Integrated Gasification Combined Cycle (IGCC) plant. This novel MR-AR IGCC plant is subsequently analyzed from an economic viewpoint through a techno-economic analysis (TEA) of the proposed plant. This novel design can achieve over 90% carbon capture without the use of a Dual-Stage Selexol unit. The resultant intensified design is more efficient from both an economic and power production perspective than the traditional IGCC plants with pre-combustion Carbon-Capture Storage (CCS) technology. The COMSOL software package is utilized to simulate the MR-AR sequence proposed in this work, and the UNISIM software (HoneywellTM) is used to create an intensified process flowsheet of the proposed MR-AR IGCC plant, which is subsequently heat-integrated. The TEA developed for the MR-AR IGCC power plant will be used to identify the extent of process intensification the proposed design has over the traditional IGCC plants with pre-combustion CCS. Furthermore, the results demonstrate a reduction in both the cost-of-electricity (COE) and in the capital cost of the proposed design over the baseline case.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Advanced genetic tools for plant biotechnology

Basic research has provided a much better understanding of the genetic networks and regulatory hierarchies in plants. To meet the challenges of agriculture, we must be able to rapidly translate this knowledge into generating improved plants. Therefore, in this Review, we discuss advanced tools that are currently available for use in plant biotechnology to produce new products in plants and to generate plants with new functions. These tools include synthetic promoters, 'tunable' transcription factors, genome-editing tools and site-specific recombinases. We also review some tools with the potential to enable crop improvement, such as methods for the assembly and synthesis of large DNA molecules, plant transformation with linked multigenes and plant artificial chromosomes. These genetic technologies should be integrated to realize their potential for applications to pressing agricultural and environmental problems.

Liu, WS↗
DOE OSTI2019

Plant density and enhanced plant vigor estimation for high-resolution images v1

The package contains algorithms for the estimation of sprout/plant density and the corresponding enhanced plant vigor from remotely sensed (RS) images. These algorithms aim to improve the plant characterization and monitoring in the early season when the soil component is significant compared to the plant spatial coverage. In such a scenario, the identification of sprouts (or plants) and the estimation of plant vegetation indexes can be performed only using UAV-acquired images. Additionally, because of the extremely high resolution, gridding becomes necessary to improve visualization and provide more informative maps. However, to capture the real range of values of the VIs, it is important to avoid the inclusion of those pixels belonging to the soil component. The sprout/plant density estimation algorithm takes in input a classification map and uses the vegetation class to estimates the plant density within a user-defined grid using a floating window. Similarly, the enhanced plant vigor algorithm takes in input the vegetation index and the classification map. The enhanced vegetation index is computed for each pixel as the average value among those pixels that belong to the vegetation class within a floating window. The software is developed for the MATLAB environment.

Falco, Nicola↗