Economic impact of yield and composition variation in bioenergy crops: Populus trichocarpa

Renee M. Happs; Andrew W. Bartling; Crissa Doeppke; Anne E. Harman-Ware; Robin Clark; Erin G. Webb; Mary J. Biddy; Jin Gui Chen; Gerald A. Tuskan; Mark F. Davis; Wellington Muchero; Brian H. Davison

doi:10.1002/bbb.2148

Economic impact of yield and composition variation in bioenergy crops: Populus trichocarpa

Renee M. Happs, Andrew W. Bartling, Crissa Doeppke, Anne E. Harman-Ware, Robin Clark, Erin G. Webb, Mary J. Biddy, Jin Gui Chen, Gerald A. Tuskan, Mark F. Davis, Wellington Muchero, Brian H. Davison

Research output: Contribution to journal › Article › peer-review

17 Scopus citations

Abstract

To achieve a bio-based economy, it is necessary to consider variability within a feedstock population. We must understand the range of key phenotypic characteristics when selecting economically advantageous genotypes for domestication in an optimized supply chain. In this analysis we measured cell-wall composition traits in a large natural variant population of Populus trichocarpa. The results were combined with agronomic growth data from the matching genotype to conduct various techno-economic analyses, evaluating the impacts of physical and compositional variability and determining the ultimate phenotypic drivers for yield and economic metrics. Here we show that, although ethanol yield per land area per year and minimum fuel selling price were most strongly impacted by tree size, when considering the largest 25% of trees, size and carbohydrate content were nearly identical influences on minimal fuel selling price, highlighting the need to focus on both size and carbohydrate content in selecting economically optimal feedstocks.

Original language	English
Pages (from-to)	176-188
Number of pages	13
Journal	Biofuels, Bioproducts and Biorefining
Volume	15
Issue number	1
DOIs	https://doi.org/10.1002/bbb.2148
State	Published - Jan 1 2021

Funding

This work was authored in part by the Alliance for Sustainable Energy, LLC, the manager and operator of the National Renewable Energy Laboratory for the US Department of Energy (DOE) under contract no. DE-AC36-08GO28308 and by Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy under contract no. DE-AC05-00OR22725. Support at NREL and ORNL was provided in part by the BioEnergy Science Center (BESC) and the Center for Bioenergy Innovation (CBI) from the US Department of Energy Bioenergy Research Centers (BER) supported by the Office of Biological and Environmental Research in the DOE Office of Science. We appreciated the assistance of Stan Martin in posting the dataset. The views expressed in the article do not necessarily represent the views of the DOE or the US government. The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for US government purposes. This work was authored in part by the Alliance for Sustainable Energy, LLC, the manager and operator of the National Renewable Energy Laboratory for the US Department of Energy (DOE) under contract no. DE‐AC36‐08GO28308 and by Oak Ridge National Laboratory, managed by UT‐Battelle, LLC, for the US Department of Energy under contract no. DE‐AC05‐00OR22725. Support at NREL and ORNL was provided in part by the BioEnergy Science Center (BESC) and the Center for Bioenergy Innovation (CBI) from the US Department of Energy Bioenergy Research Centers (BER) supported by the Office of Biological and Environmental Research in the DOE Office of Science. We appreciated the assistance of Stan Martin in posting the dataset. The views expressed in the article do not necessarily represent the views of the DOE or the US government. The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid‐up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for US government purposes.

Keywords

bioethanol
feedstock variability
high-throughput compositional analysis
minimum fuel selling price
techno-economic analysis

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10.1002/bbb.2148

Cite this

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title = "Economic impact of yield and composition variation in bioenergy crops: Populus trichocarpa",

abstract = "To achieve a bio-based economy, it is necessary to consider variability within a feedstock population. We must understand the range of key phenotypic characteristics when selecting economically advantageous genotypes for domestication in an optimized supply chain. In this analysis we measured cell-wall composition traits in a large natural variant population of Populus trichocarpa. The results were combined with agronomic growth data from the matching genotype to conduct various techno-economic analyses, evaluating the impacts of physical and compositional variability and determining the ultimate phenotypic drivers for yield and economic metrics. Here we show that, although ethanol yield per land area per year and minimum fuel selling price were most strongly impacted by tree size, when considering the largest 25\% of trees, size and carbohydrate content were nearly identical influences on minimal fuel selling price, highlighting the need to focus on both size and carbohydrate content in selecting economically optimal feedstocks.",

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AU - Doeppke, Crissa

AU - Harman-Ware, Anne E.

AU - Clark, Robin

AU - Webb, Erin G.

AU - Biddy, Mary J.

AU - Chen, Jin Gui

AU - Tuskan, Gerald A.

AU - Davis, Mark F.

AU - Muchero, Wellington

AU - Davison, Brian H.

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Economic impact of yield and composition variation in bioenergy crops: Populus trichocarpa

Abstract

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Keywords

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Corresponding Standard Reference Material Data used in Partial Least Squares Regression Models for Sugar Composition Estimates in Biomass in: Economic Impact of Yield and Composition Variation in Bioenergy Crops: Populus trichocarpa

Economic impact of yield and compositions variation in bioenergy crops: Populus trichocarpa

Cite this

Economic impact of yield and composition variation in bioenergy crops: Populus trichocarpa

Abstract

Funding

Keywords

Access to Document

Other files and links

Fingerprint

Datasets

Corresponding Standard Reference Material Data used in Partial Least Squares Regression Models for Sugar Composition Estimates in Biomass in: Economic Impact of Yield and Composition Variation in Bioenergy Crops: Populus trichocarpa

Economic impact of yield and compositions variation in bioenergy crops: Populus trichocarpa

Cite this