Dataset Information

Infrared and Raman spectra of lignin substructures: Dibenzodioxocin.

ABSTRACT: Vibrational spectroscopy is a very suitable tool for investigating the plant cell wall in situ with almost no sample preparation. The structural information of all different constituents is contained in a single spectrum. Interpretation therefore heavily relies on reference spectra and understanding of the vibrational behavior of the components under study. For the first time, we show infrared (IR) and Raman spectra of dibenzodioxocin (DBDO), an important lignin substructure. A detailed vibrational assignment of the molecule, based on quantum chemical computations, is given in the Supporting Information; the main results are found in the paper. Furthermore, we show IR and Raman spectra of synthetic guaiacyl lignin (dehydrogenation polymer-G-DHP). Raman spectra of DBDO and G-DHP both differ with respect to the excitation wavelength and therefore reveal different features of the substructure/polymer. This study confirms the idea previously put forward that Raman at 532 nm selectively probes end groups of lignin, whereas Raman at 785 nm and IR seem to represent the majority of lignin substructures.

SUBMITTER: Bock P

PROVIDER: S-EPMC7079546 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Infrared and Raman spectra of lignin substructures: Dibenzodioxocin.

Bock Peter P Nousiainen Paula P Elder Thomas T Blaukopf Markus M Amer Hassan H Zirbs Ronald R Potthast Antje A Gierlinger Notburga N

Journal of Raman spectroscopy : JRS 20200103 3

Vibrational spectroscopy is a very suitable tool for investigating the plant cell wall in situ with almost no sample preparation. The structural information of all different constituents is contained in a single spectrum. Interpretation therefore heavily relies on reference spectra and understanding of the vibrational behavior of the components under study. For the first time, we show infrared (IR) and Raman spectra of dibenzodioxocin (DBDO), an important lignin substructure. A detailed vibratio ...[more]

PMID: 32214622

Similar Datasets

Project description:BackgroundIn 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).ResultsThe 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.ConclusionEucalypts 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.

Dataset Information

Infrared and Raman spectra of lignin substructures: Dibenzodioxocin.

Publications

Infrared and Raman spectra of lignin substructures: Dibenzodioxocin.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets