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Title: High Throughput Screening Technologies in Biomass Characterization

Abstract

Biomass analysis is a slow and tedious process and not solely due to the long generation time for most plant species. Screening large numbers of plant variants for various geno-, pheno-, and chemo-types, whether naturally occurring or engineered in the lab, has multiple challenges. Plant cell walls are complex, heterogeneous networks that are difficult to deconstruct and analyze. Macroheterogeneity from tissue types, age, and environmental factors makes representative sampling a challenge and natural variability generates a significant range in data. Using high throughput (HTP) methodologies allows for large sample sets and replicates to be examined, narrowing in on more precise data for various analyses. This review provides a comprehensive survey of high throughput screening as applied to biomass characterization, from compositional analysis of cell walls by NIR, NMR, mass spectrometry, and wet chemistry to functional screening of changes in recalcitrance via HTP thermochemical pretreatment coupled to enzyme hydrolysis and microscale fermentation. The advancements and development of most high-throughput methods have been achieved through utilization of state-of-the art equipment and robotics, rapid detection methods, as well as reduction in sample size and preparation procedures. The computational analysis of the large amount of data generated using high throughput analytical techniques has recentlymore » become more sophisticated, faster and economically viable, enabling a more comprehensive understanding of biomass genomics, structure, composition, and properties. Therefore, methodology for analyzing large datasets generated by the various analytical techniques is also covered.« less

Authors:
 [1];  [1];  [1];  [1]; ORCiD logo [2];  [2];  [3]; ORCiD logo [4]; ORCiD logo [5];  [5]; ORCiD logo [5]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States). Biosciences Center
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Biosciences Division
  3. Morgan State Univ., Baltimore, MD (United States). Dept. of Civil Engineering
  4. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Biosciences Divisionv
  5. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Biosciences Division; Univ. of Tennessee, Knoxville, TN (United States). Bredesen Center for Interdisciplinary Research and Graduate Education
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1493117
DOE Contract Number:  
AC05-00OR22725; AC02-05CH11231
Resource Type:
Journal Article
Journal Name:
Frontiers in Energy Research
Additional Journal Information:
Journal Volume: 6; Journal ID: ISSN 2296-598X
Publisher:
Frontiers Research Foundation
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; biomass recalcitrance, biomass compositional analysis, high throughput analysis, neural networks, biomass conversion

Citation Formats

Decker, Stephen R., Harman-Ware, Anne E., Happs, Renee M., Wolfrum, Edward J., Tuskan, Gerald A., Kainer, David, Oguntimein, Gbekeloluwa B., Rodriguez, Miguel, Weighill, Deborah, Jones, Piet, and Jacobson, Daniel A. High Throughput Screening Technologies in Biomass Characterization. United States: N. p., 2018. Web. doi:10.3389/fenrg.2018.00120.
Decker, Stephen R., Harman-Ware, Anne E., Happs, Renee M., Wolfrum, Edward J., Tuskan, Gerald A., Kainer, David, Oguntimein, Gbekeloluwa B., Rodriguez, Miguel, Weighill, Deborah, Jones, Piet, & Jacobson, Daniel A. High Throughput Screening Technologies in Biomass Characterization. United States. doi:10.3389/fenrg.2018.00120.
Decker, Stephen R., Harman-Ware, Anne E., Happs, Renee M., Wolfrum, Edward J., Tuskan, Gerald A., Kainer, David, Oguntimein, Gbekeloluwa B., Rodriguez, Miguel, Weighill, Deborah, Jones, Piet, and Jacobson, Daniel A. Tue . "High Throughput Screening Technologies in Biomass Characterization". United States. doi:10.3389/fenrg.2018.00120. https://www.osti.gov/servlets/purl/1493117.
@article{osti_1493117,
title = {High Throughput Screening Technologies in Biomass Characterization},
author = {Decker, Stephen R. and Harman-Ware, Anne E. and Happs, Renee M. and Wolfrum, Edward J. and Tuskan, Gerald A. and Kainer, David and Oguntimein, Gbekeloluwa B. and Rodriguez, Miguel and Weighill, Deborah and Jones, Piet and Jacobson, Daniel A.},
abstractNote = {Biomass analysis is a slow and tedious process and not solely due to the long generation time for most plant species. Screening large numbers of plant variants for various geno-, pheno-, and chemo-types, whether naturally occurring or engineered in the lab, has multiple challenges. Plant cell walls are complex, heterogeneous networks that are difficult to deconstruct and analyze. Macroheterogeneity from tissue types, age, and environmental factors makes representative sampling a challenge and natural variability generates a significant range in data. Using high throughput (HTP) methodologies allows for large sample sets and replicates to be examined, narrowing in on more precise data for various analyses. This review provides a comprehensive survey of high throughput screening as applied to biomass characterization, from compositional analysis of cell walls by NIR, NMR, mass spectrometry, and wet chemistry to functional screening of changes in recalcitrance via HTP thermochemical pretreatment coupled to enzyme hydrolysis and microscale fermentation. The advancements and development of most high-throughput methods have been achieved through utilization of state-of-the art equipment and robotics, rapid detection methods, as well as reduction in sample size and preparation procedures. The computational analysis of the large amount of data generated using high throughput analytical techniques has recently become more sophisticated, faster and economically viable, enabling a more comprehensive understanding of biomass genomics, structure, composition, and properties. Therefore, methodology for analyzing large datasets generated by the various analytical techniques is also covered.},
doi = {10.3389/fenrg.2018.00120},
journal = {Frontiers in Energy Research},
issn = {2296-598X},
number = ,
volume = 6,
place = {United States},
year = {2018},
month = {11}
}