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Application of Py-GC/MS coupled with PARAFAC2 and PLS-DA to study fast pyrolysis of genetically engineered poplars

Toraman, Hilal E. ; Abrahamsson, Victor LU ; Vanholme, Ruben ; Van Acker, Rebecca ; Ronsse, Frederik ; Pilate, Gilles ; Boerjan, Wout ; Van Geem, Kevin M. and Marin, Guy B. (2018) In Journal of Analytical and Applied Pyrolysis 129. p.101-111
Abstract

Field-grown genetically engineered and wild-type poplars were pyrolyzed in a micro-pyrolysis (Py-GC/MS) setup under fast pyrolysis conditions. Poplars (Populus tremula x P. alba) down-regulated for cinnamoyl-CoA reductase (CCR), which catalyzes the first step of the monolignol-specific branch of the phenylpropanoid biosynthetic pathway, were grown in field trials in France and harvested after a full rotation of 2 years. The effect of small compositional differences, specifically small shifts in lignin composition and their impact on the bio-oil composition, could not be identified using principal component analysis (PCA), necessitating the use of more advanced analysis techniques. The combination of parallel factor analysis 2 (PARAFAC2)... (More)

Field-grown genetically engineered and wild-type poplars were pyrolyzed in a micro-pyrolysis (Py-GC/MS) setup under fast pyrolysis conditions. Poplars (Populus tremula x P. alba) down-regulated for cinnamoyl-CoA reductase (CCR), which catalyzes the first step of the monolignol-specific branch of the phenylpropanoid biosynthetic pathway, were grown in field trials in France and harvested after a full rotation of 2 years. The effect of small compositional differences, specifically small shifts in lignin composition and their impact on the bio-oil composition, could not be identified using principal component analysis (PCA), necessitating the use of more advanced analysis techniques. The combination of parallel factor analysis 2 (PARAFAC2) and partial least squares-discriminant analysis (PLS-DA) for detailed characterization and classification of the pyrolysis data enabled the classification of the poplars with a success rate above 99% using the PARAFAC2 scores. This methodology proved to be extremely valuable to identify subtle information in complex datasets, such as the one used in this study. The obtained PLS-DA models were validated by cross-validation, jackknifing and permutation tests in order to ensure that the model was not overfitting the data. PLS-DA showed that down-regulation of CCR disfavored the relative amount of both guaiacyl and syringyl lignin-derived compounds. This study shows that lignin engineering can be a promising strategy to alter the lignin composition of the biomass for the production of high value-added phenolic compounds.

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author
; ; ; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Field-grown transgenic plants, PARAFAC2, Phenolic compounds, PLS-DA, Pyrolysis
in
Journal of Analytical and Applied Pyrolysis
volume
129
pages
11 pages
publisher
Elsevier
external identifiers
  • scopus:85041292807
ISSN
0165-2370
DOI
10.1016/j.jaap.2017.11.022
language
English
LU publication?
yes
id
0270dade-672e-4e4a-ad30-e8b9c3873da5
date added to LUP
2018-02-12 13:33:30
date last changed
2022-03-09 08:59:59
@article{0270dade-672e-4e4a-ad30-e8b9c3873da5,
  abstract     = {{<p>Field-grown genetically engineered and wild-type poplars were pyrolyzed in a micro-pyrolysis (Py-GC/MS) setup under fast pyrolysis conditions. Poplars (Populus tremula x P. alba) down-regulated for cinnamoyl-CoA reductase (CCR), which catalyzes the first step of the monolignol-specific branch of the phenylpropanoid biosynthetic pathway, were grown in field trials in France and harvested after a full rotation of 2 years. The effect of small compositional differences, specifically small shifts in lignin composition and their impact on the bio-oil composition, could not be identified using principal component analysis (PCA), necessitating the use of more advanced analysis techniques. The combination of parallel factor analysis 2 (PARAFAC2) and partial least squares-discriminant analysis (PLS-DA) for detailed characterization and classification of the pyrolysis data enabled the classification of the poplars with a success rate above 99% using the PARAFAC2 scores. This methodology proved to be extremely valuable to identify subtle information in complex datasets, such as the one used in this study. The obtained PLS-DA models were validated by cross-validation, jackknifing and permutation tests in order to ensure that the model was not overfitting the data. PLS-DA showed that down-regulation of CCR disfavored the relative amount of both guaiacyl and syringyl lignin-derived compounds. This study shows that lignin engineering can be a promising strategy to alter the lignin composition of the biomass for the production of high value-added phenolic compounds.</p>}},
  author       = {{Toraman, Hilal E. and Abrahamsson, Victor and Vanholme, Ruben and Van Acker, Rebecca and Ronsse, Frederik and Pilate, Gilles and Boerjan, Wout and Van Geem, Kevin M. and Marin, Guy B.}},
  issn         = {{0165-2370}},
  keywords     = {{Field-grown transgenic plants; PARAFAC2; Phenolic compounds; PLS-DA; Pyrolysis}},
  language     = {{eng}},
  month        = {{01}},
  pages        = {{101--111}},
  publisher    = {{Elsevier}},
  series       = {{Journal of Analytical and Applied Pyrolysis}},
  title        = {{Application of Py-GC/MS coupled with PARAFAC2 and PLS-DA to study fast pyrolysis of genetically engineered poplars}},
  url          = {{http://dx.doi.org/10.1016/j.jaap.2017.11.022}},
  doi          = {{10.1016/j.jaap.2017.11.022}},
  volume       = {{129}},
  year         = {{2018}},
}