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Title: Harmonization of experimental approach and data collection to streamline analysis of biomass composition from algae in an inter-laboratory setting

Abstract

In order to establish and design long-term algae cultivation experiments, inter-laboratory projects need to harmonize the requirements of techno-economic and life-cycle analysis models, with standardized data inputs. In order to provide a consistent foundation and allow for integration and analysis of the results in computational technical and resource analysis models, we implemented closely coordinated, harmonized and objective analytical protocols along with a common language for measuring growth and productivity for the major algal components. We describe here the process by which we developed a harmonization framework for analysis across five geographically diverse testbed sites. Our goal was to align analytical procedures to ensure consistent reporting on biomass and lipid content, quality and yields to eliminate measurement variability as a source of uncertainty in production data. Developing standards for analysis that streamline reporting on composition and expected fuel yields from biomass is one of the major outcomes of this work and this provides a starting place for further advanced characterization of algae to support the techno-economical process analyses and account for the mass balance accounting of algal biomass. Initial analysis of data obtained from field studies shows trends in compositional shifts of lipid and protein content of the biomass that aremore » in support of the physiological experiments demonstrated in the first geographically distributed unified outdoor cultivation trials.« less

Authors:
 [1];  [1];  [1];  [2];  [3]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  2. Harmon Consulting, Kamuela, HI (United States)
  3. Arizona State Univ., Mesa, AZ (United States)
Publication Date:
Research Org.:
National Renewable Energy Laboratory (NREL), Golden, CO (United States); Arizona State Univ., Tempe, AZ (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Transportation Office. Bioenergy Technologies Office; USDOE
OSTI Identifier:
1373264
Alternate Identifier(s):
OSTI ID: 1550511; OSTI ID: 1785543
Report Number(s):
NREL/JA-5100-68598
Journal ID: ISSN 2211-9264
Grant/Contract Number:  
AC36-08GO28308; EE0005996; AC36-08-GO28308
Resource Type:
Accepted Manuscript
Journal Name:
Algal Research
Additional Journal Information:
Journal Volume: 25; Journal Issue: C; Journal ID: ISSN 2211-9264
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; algae; biomass; composition; lipids; carbohydrates; protein; harmonization; Algae, Biomass, Composition, Lipids, Carbohydrates, Protein, Harmonization

Citation Formats

Laurens, Lieve M. L., Van Wychen, Stefanie, Pienkos, Philip T., Harmon, Valerie L., and McGowen, John. Harmonization of experimental approach and data collection to streamline analysis of biomass composition from algae in an inter-laboratory setting. United States: N. p., 2017. Web. doi:10.1016/j.algal.2017.03.029.
Laurens, Lieve M. L., Van Wychen, Stefanie, Pienkos, Philip T., Harmon, Valerie L., & McGowen, John. Harmonization of experimental approach and data collection to streamline analysis of biomass composition from algae in an inter-laboratory setting. United States. https://doi.org/10.1016/j.algal.2017.03.029
Laurens, Lieve M. L., Van Wychen, Stefanie, Pienkos, Philip T., Harmon, Valerie L., and McGowen, John. Wed . "Harmonization of experimental approach and data collection to streamline analysis of biomass composition from algae in an inter-laboratory setting". United States. https://doi.org/10.1016/j.algal.2017.03.029. https://www.osti.gov/servlets/purl/1373264.
@article{osti_1373264,
title = {Harmonization of experimental approach and data collection to streamline analysis of biomass composition from algae in an inter-laboratory setting},
author = {Laurens, Lieve M. L. and Van Wychen, Stefanie and Pienkos, Philip T. and Harmon, Valerie L. and McGowen, John},
abstractNote = {In order to establish and design long-term algae cultivation experiments, inter-laboratory projects need to harmonize the requirements of techno-economic and life-cycle analysis models, with standardized data inputs. In order to provide a consistent foundation and allow for integration and analysis of the results in computational technical and resource analysis models, we implemented closely coordinated, harmonized and objective analytical protocols along with a common language for measuring growth and productivity for the major algal components. We describe here the process by which we developed a harmonization framework for analysis across five geographically diverse testbed sites. Our goal was to align analytical procedures to ensure consistent reporting on biomass and lipid content, quality and yields to eliminate measurement variability as a source of uncertainty in production data. Developing standards for analysis that streamline reporting on composition and expected fuel yields from biomass is one of the major outcomes of this work and this provides a starting place for further advanced characterization of algae to support the techno-economical process analyses and account for the mass balance accounting of algal biomass. Initial analysis of data obtained from field studies shows trends in compositional shifts of lipid and protein content of the biomass that are in support of the physiological experiments demonstrated in the first geographically distributed unified outdoor cultivation trials.},
doi = {10.1016/j.algal.2017.03.029},
journal = {Algal Research},
number = C,
volume = 25,
place = {United States},
year = {Wed Apr 26 00:00:00 EDT 2017},
month = {Wed Apr 26 00:00:00 EDT 2017}
}

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Cited by: 15 works
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Works referencing / citing this record:

Unified field studies of the algae testbed public-private partnership as the benchmark for algae agronomics
journal, November 2018

  • Knoshaug, Eric P.; Wolfrum, Ed; Laurens, Lieve M. L.
  • Scientific Data, Vol. 5, Issue 1
  • DOI: 10.1038/sdata.2018.267