Yield, chemistry, and TEA/LCA data for 84 switchgrass (Panicum virgatum L.) variants

Happs, Renee; Hanes, Rebecca; Bartling, Andrew; Field, John; Harmon-Ware, Anne; Clark, Robin; Pendergast, Thomas; Devos, Katrien; Webb, Erin; Missaoui, Ali; Yaping, Xu; Makaju, Shiva; Shrestha, Vivek; Mazarei, Mitra; Stewart, Charles; Millwood, Reginald; Davison, Brian

doi:10.25983/2217356

Title: Yield, chemistry, and TEA/LCA data for 84 switchgrass (Panicum virgatum L.) variants

Dataset
Other Related Research

Abstract

Switchgrass yield, chemistry, technoeconomic assessment (TEA), and life cycle assessment (LCA) data referenced in the manuscript "Economics and Sustainability impacts of yield and composition variation in bioenergy crops: Panicum virgatum L.", Happs, et. al. (manuscript in revision at ACS Sustainable Chemistry & Engineering). These results are based on analysis of yield data generated from a set of switchgrass common garden experiments established by the Center for Bioenergy Innovation (CBI; https://cbi.ornl.gov/). These data include estimates of commercial-scale yields and characterization of biomass chemistry (fermentable carbohydrate fraction) for 84 different switchgrass variants from a genome-wide association study population, as well as estimates of minimum fuel selling price and various life-cycle footprint metrics for cellulosic ethanol produced from that switchgrass biomass.

Authors:

Happs, Renee; Hanes, Rebecca; Bartling, Andrew; Field, John; Harmon-Ware, Anne; Clark, Robin; Pendergast, Thomas; Devos, Katrien; Webb, Erin; Missaoui, Ali; Yaping, Xu; Makaju, Shiva; Shrestha, Vivek; Mazarei, Mitra; Stewart, Charles; Millwood, Reginald; Davison, Brian

National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
University of Georgia, Athens
University of Tennessee, Knoxville
University of Tennesee, Knoxville

Publication Date:: Mon Nov 20 23:00:00 EST 2023

DOE Contract Number:: AC05-00OR22725

Research Org.:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Subject:: switchgrass, biofuels

OSTI Identifier:: 2217356

DOI:: https://doi.org/10.25983/2217356

Citation Formats


                    Happs, Renee, Hanes, Rebecca, Bartling, Andrew, Field, John, Harmon-Ware, Anne, Clark, Robin, Pendergast, Thomas, Devos, Katrien, Webb, Erin, Missaoui, Ali, Yaping, Xu, Makaju, Shiva, Shrestha, Vivek, Mazarei, Mitra, Stewart, Charles, Millwood, Reginald, and Davison, Brian. Yield, chemistry, and TEA/LCA data for 84 switchgrass (Panicum virgatum L.) variants.  United States: N. p., 2023. 
        Web.  doi:10.25983/2217356.

Copy to clipboard


                    Happs, Renee, Hanes, Rebecca, Bartling, Andrew, Field, John, Harmon-Ware, Anne, Clark, Robin, Pendergast, Thomas, Devos, Katrien, Webb, Erin, Missaoui, Ali, Yaping, Xu, Makaju, Shiva, Shrestha, Vivek, Mazarei, Mitra, Stewart, Charles, Millwood, Reginald, & Davison, Brian. Yield, chemistry, and TEA/LCA data for 84 switchgrass (Panicum virgatum L.) variants.  United States.  doi:https://doi.org/10.25983/2217356

Copy to clipboard


                    Happs, Renee, Hanes, Rebecca, Bartling, Andrew, Field, John, Harmon-Ware, Anne, Clark, Robin, Pendergast, Thomas, Devos, Katrien, Webb, Erin, Missaoui, Ali, Yaping, Xu, Makaju, Shiva, Shrestha, Vivek, Mazarei, Mitra, Stewart, Charles, Millwood, Reginald, and Davison, Brian. 2023.  
"Yield, chemistry, and TEA/LCA data for 84 switchgrass (Panicum virgatum L.) variants".  United States.  doi:https://doi.org/10.25983/2217356.  https://www.osti.gov/servlets/purl/2217356. Pub date:Mon Nov 20 23:00:00 EST 2023

Copy to clipboard


                    
@article{osti_2217356,

  title        = {Yield, chemistry, and TEA/LCA data for 84 switchgrass (Panicum virgatum L.) variants},

  author       = {Happs, Renee and Hanes, Rebecca and Bartling, Andrew and Field, John and Harmon-Ware, Anne and Clark, Robin and Pendergast, Thomas and Devos, Katrien and Webb, Erin and Missaoui, Ali and Yaping, Xu and Makaju, Shiva and Shrestha, Vivek and Mazarei, Mitra and Stewart, Charles and Millwood, Reginald and Davison, Brian},

  abstractNote = {Switchgrass yield, chemistry, technoeconomic assessment (TEA), and life cycle assessment (LCA) data referenced in the manuscript "Economics and Sustainability impacts of yield and composition variation in bioenergy crops: Panicum virgatum L.", Happs, et. al. (manuscript in revision at ACS Sustainable Chemistry & Engineering). These results are based on analysis of yield data generated from a set of switchgrass common garden experiments established by the Center for Bioenergy Innovation (CBI; https://cbi.ornl.gov/). These data include estimates of commercial-scale yields and characterization of biomass chemistry (fermentable carbohydrate fraction) for 84 different switchgrass variants from a genome-wide association study population, as well as estimates of minimum fuel selling price and various life-cycle footprint metrics for cellulosic ethanol produced from that switchgrass biomass.},

  doi          = {10.25983/2217356},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Mon Nov 20 23:00:00 EST 2023},

  month        = {Mon Nov 20 23:00:00 EST 2023}

}

Copy to clipboard

Dataset:

View Dataset

DOI: https://doi.org/10.25983/2217356

Save / Share:

Export Metadata

Save to My Library

Similar records in DOE Data Explorer and OSTI.GOV collections:

Data from: Candidate variants for additive and interactive effects on bioenergy traits in switchgrass (Panicum virgatum L.) identified by genome-wide association analyses

Dataset Ramstein, Guillaume P. ; Evans, Joseph ; Nandety, Aruna ; ...

Switchgrass is a promising herbaceous energy crop, but further gains in biomass yield and quality must be achieved to enable a viable bioenergy industry. Developing DNA markers can contribute to such progress, but depiction of genetic bases should be reliable, involving not only simple additive marker effects but also interactions with genetic backgrounds, e.g., ecotypes, or synergies with other markers. We analyzed plant height, carbon content, nitrogen content, and mineral concentration in a diverse panel consisting of 512 genotypes of upland and lowland ecotype. We performed association analyses based on exome capture sequencing and tested 439,170 markers for marginal effects,more »« less
Exploring natural genetic diversity in switchgrass (Panicum virgatum) and its microbiome

Dataset Juenger, Thomas
Data from: Associative nitrogen fixation (ANF) in switchgrass (Panicum virgatum) across a nitrogen input gradient

Dataset Roley, Sarah S. ; Duncan, David S. ; Liang, Di ; ...

Associative N fixation (ANF), the process by which dinitrogen gas is converted to ammonia by bacteria in casual association with plants, has not been well-studied in temperate ecosystems. We examined the ANF potential of switchgrass (Panicum virgatum L.), a North American prairie grass whose productivity is often unresponsive to N fertilizer addition, via separate short-term 15N2 incubations of rhizosphere soils and excised roots four times during the growing season. Measurements occurred along N fertilization gradients at two sites with contrasting soil fertility (Wisconsin, USA Mollisols and Michigan, USA Alfisols). In general, we found that ANF potentials declined with long-term Nmore »« less
Data from: Identification of anti-fungal bioactive terpenoids from the bioenergy crop switchgrass (Panicum virgatum)

Dataset Li, Xingxing ; Last, Robert L.

To identify specific fungal growth-modulating metabolites, we tested fractions from root extracts on three ecologically important fungal isolates – Linnemania elongata, Trichoderma sp. and Fusarium sp.
Sustainability Trait Modeling of Field-Grown Switchgrass (Panicum virgatum) Using UAV-Based Imagery

Dataset Yaping, Xu ; Yaping, Xu ; Shrestha, Vivek ; ...

Unmanned aerial vehicles (UAVs) provide an intermediate scale of spatial and spectral data collection that yields increased accuracy and consistency in data collection for morphological and physiological traits than satellites and expanded flexibility and high-throughput compared to ground-based data collection. In this project, we used UAV-based multispectral imagery collected from MicaSense RedEdge-M on a DJI Matrice 600 Pro for automated phenotyping of field-grown switchgrass (Panicum virgatum), a leading bioenergy feedstock. The raw images were processed with Pix4D Mapper to create the reflectance data, and vegetation indices were calculated from a UAV-based multispectral camera. Statistical models were developed for rust diseasemore »« less

Similar Records