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Title: High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: A comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development

Abstract

Background: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). Results: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratiomore » in a diverse consortium of feedstocks. Conclusion: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks.« less

Authors:
 [1];  [2];  [3];  [4];  [5];  [6];  [7]
  1. Univ. of Queensland, Lucias (Australia); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States)
  4. Univ. of the Sunshine Coast and Queensland Dept. of Agriculture, Maroochydore, QLD (Australia)
  5. Southern Cross Univ., East Lismore, NSW (Australia)
  6. Univ. of Queensland, Lucias, QLD (Australia); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  7. Univ. of Queensland, Lucias, QLD (Australia)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23). Biological Systems Science Division
OSTI Identifier:
1511400
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Biotechnology for Biofuels
Additional Journal Information:
Journal Volume: 7; Journal Issue: 1; Journal ID: ISSN 1754-6834
Publisher:
BioMed Central
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; 59 BASIC BIOLOGICAL SCIENCES; 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; Biomass; Raman spectroscopy; Near-infrared spectroscopy; Fourier-transform infrared spectroscopy; High-throughput; Multivariate analysis; Lignin S/G

Citation Formats

Lupoi, Jason S., Singh, Seema, Davis, Mark, Lee, David J., Shepherd, Merv, Simmons, Blake A., and Henry, Robert J. High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: A comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development. United States: N. p., 2014. Web. doi:10.1186/1754-6834-7-93.
Lupoi, Jason S., Singh, Seema, Davis, Mark, Lee, David J., Shepherd, Merv, Simmons, Blake A., & Henry, Robert J. High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: A comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development. United States. doi:10.1186/1754-6834-7-93.
Lupoi, Jason S., Singh, Seema, Davis, Mark, Lee, David J., Shepherd, Merv, Simmons, Blake A., and Henry, Robert J. Tue . "High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: A comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development". United States. doi:10.1186/1754-6834-7-93. https://www.osti.gov/servlets/purl/1511400.
@article{osti_1511400,
title = {High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: A comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development},
author = {Lupoi, Jason S. and Singh, Seema and Davis, Mark and Lee, David J. and Shepherd, Merv and Simmons, Blake A. and Henry, Robert J.},
abstractNote = {Background: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). Results: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. Conclusion: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks.},
doi = {10.1186/1754-6834-7-93},
journal = {Biotechnology for Biofuels},
issn = {1754-6834},
number = 1,
volume = 7,
place = {United States},
year = {2014},
month = {6}
}

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Works referenced in this record:

Lignin content in natural Populus variants affects sugar release
journal, March 2011

  • Studer, M. H.; DeMartini, J. D.; Davis, M. F.
  • Proceedings of the National Academy of Sciences, Vol. 108, Issue 15, p. 6300-6305
  • DOI: 10.1073/pnas.1009252108

An overview of second generation biofuel technologies
journal, March 2010