Characterisation of structure-dependent functional properties of lignin with infrared spectroscopy
Open accessAbstract
Fourier-transformed infrared spectroscopy (FT-IR) was evaluated as an analytical technique for the estimation of the chemical composition and functional properties of lignin. A sample set containing various non-wood, hardwood and softwood lignins isolated by different processing technologies was used. The lignin samples were characterised by both conventional chemical analysis and non-destructive methods, such as diffuse reflectance FT-IR. Principal component analysis (PCA) based on the IR-fingerprint spectral region allowed classification of lignins according to origin and processing conditions. The antioxidative properties of each lignin sample in both aqueous and micellar systems were determined. All lignin samples showed radical scavenging activity, with sisal and abaca lignin being the most effective radical scavengers. The radical scavenging efficiency of the most efficient lignin was about 20% of that of BHT and tocopherol (based on weight), compounds that are commonly used in food and cosmetic industries. Multivariate analysis was applied to correlate chemical composition and antioxidative properties of lignins with the FT-IR spectral data. Partial least squares (PLS) models were able to predict the major components' concentrations and radical scavenging activity at the 99% confidence level presenting r2 values higher than 0.80 in most cases.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
New method for quantitative determination of uronic acids
Blumenkrantz, N., & Asboe-Hansen, G. (1973) · Analytical Biochemistry · doi:10.1016/0003-2697(73)90377-1 · Cited by 7,140 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Mahmood, N., Yuan, Z., Schmidt, J., & Xu, C. (. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.01.037 · Cited by 487 · see citing works
Lancefield, C. S., Wienk, H. L. J., Boelens, R., Weckhuysen, B. M., & Bruijnincx, P. C. A. (2018) · Chemical Science · doi:10.1039/c8sc02000k · Cited by 210 · see citing works
Deep Eutectic Solvents (DESs) for the Isolation of Willow Lignin (Salix matsudana cv. Zhuliu)
Li, T., Lyu, G., Liu, Y., Lou, R., Lucia, L., Yang, G., Chen, J., & Saeed, H. (2017) · International Journal of Molecular Sciences · doi:10.3390/ijms18112266 · Cited by 149 · see citing works
Kinetic and thermodynamic studies on methylene blue biosorption using corn-husk
Paşka, O. M., Păcurariu, C., & Muntean, S. G. (2014) · RSC Adv. · doi:10.1039/c4ra10504d · Cited by 115 · see citing works
Phenols and aromatics from fast pyrolysis of variously prepared lignins from hard- and softwoods
Custodis, V. B. F., Bährle, C., Vogel, F., & van Bokhoven, J. A. (2015) · Journal of Analytical and Applied Pyrolysis · doi:10.1016/j.jaap.2015.07.018 · Cited by 103 · see citing works
Rashid, T., Gnanasundaram, N., Appusamy, A., Kait, C. F., & Thanabalan, M. (2018) · Industrial Crops and Products · doi:10.1016/j.indcrop.2018.02.056 · Cited by 95 · see citing works
Glodowska, M., Stopelli, E., Schneider, M., Lightfoot, A., Rathi, B., Straub, D., Patzner, M., Duyen, V. T., AdvectAs Team Members, Berg, M., et al. (2020) · Environmental Science & Technology · doi:10.1021/acs.est.9b07183 · Cited by 91 · see citing works
Ramakoti, B., Dhanagopal, H., Deepa, K., Rajesh, M., Ramaswamy, S., & Tamilarasan, K. (2019) · Bioresource Technology Reports · doi:10.1016/j.biteb.2019.100293 · Cited by 61 · see citing works
Kumar, A., Kumar, A., Kumar, J., & Bhaskar, T. (2019) · Bioresource Technology · doi:10.1016/j.biortech.2019.121822 · Cited by 57 · see citing works
Dalle Vacche, S., Karunakaran, V., Patrucco, A., Zoccola, M., Douard, L., Ronchetti, S., Gallo, M., Schreier, A., Leterrier, Y., Bras, J., et al. (2021) · Molecules · doi:10.3390/molecules26164723 · Cited by 32 · see citing works
Low-Temperature Deoxidization of Lignin and Its Impact on Liquid Products from Pyrolysis
Mei, Y., Zhang, S., Wang, H., Jing, S., Hou, T., & Pang, S. (2020) · Energy & Fuels · doi:10.1021/acs.energyfuels.0c00202 · Cited by 15 · see citing works
- Authors
- Boeriu, C. G., Bravo, D., Gosselink, R. J. A., & van Dam, J. E. G.
- Affiliations
- Wageningen University & Research (NL)
- Corresponding author
- Boeriu, Carmen G.
- Venue
- Industrial Crops and Products
- Publisher
- Elsevier BV
- Published
- 2004-09
- Volume
- 20
- Issue
- 2
- Pages
- 205-218
- ISSN
- 0926-6690 (ISSN-L)
- OpenAlex
- W2021916337
- Cited by
- 1,002
- References
- 1
- Citations by year
- 2026: 93 · 2025: 97 · 2024: 90 · 2023: 70 · 2022: 74 · 2021: 66 · 2020: 77 · 2019: 72 · 2018: 50 · 2017: 46 · 2016: 37 · 2015: 66 · 2014: 43 · 2013: 41 · 2012: 19
- FWCI
- 3.10
- Type
- journal article
- Language
- en
- Open access
- green
- research.wur.nl
- Locations
- Industrial Crops and Products (publishedVersion)
- Socio-Environmental Systems Modeling (acceptedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Lignin and Wood Chemistry
- Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
- Health Sciences › Medicine › Biochemistry › Phytochemicals and Antioxidant Activities
- Keywords
- lignin, FTIR spectroscopy, lignin chemical composition, free radical scavenging, antioxidant activity, softwood lignin, hardwood lignin, partial least squares regression, principal component analysis, micellar systems
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review