Application of Py-GC/MS coupled with PARAFAC2 and PLS-DA to study fast pyrolysis of genetically engineered poplars
(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)
- author
- 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.
- organization
- publishing date
- 2018-01-01
- 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}}, }