Advanced

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.

(Less)
Please use this url to cite or link to this publication:
author
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
2018-05-29 11:08:56
@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},
  keyword      = {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},
  volume       = {129},
  year         = {2018},
}