Evidence map›Paper›PMID 40078379›Full record

ArticleAnalytical science advances2025

Chemometric Model for Rapid Determination of Syringyl/Guaiacyl Ratio in Non-Wood by FT-NIR Spectroscopic Data.

M Nashir Uddin, Taslima Ferdous, Yangcan Jin, M Mostafizur Rahman, M Sarwar Jahan

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Article in Analytical science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

M Nashir UddinBCSIR Laboratories Bangladesh Council of Scientific and Industrial Research (BCSIR) Dhaka Bangladesh.
Taslima FerdousDepartment of Applied Chemistry and Chemical Engineering University of Dhaka Dhaka Bangladesh.
Yangcan JinJiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources Jiangsu Key Lab of Pulp and Paper Science and Technology Nanjing Forestry University Nanjing China.
M Mostafizur RahmanBCSIR Laboratories Bangladesh Council of Scientific and Industrial Research (BCSIR) Dhaka Bangladesh.
M Sarwar JahanBCSIR Laboratories Bangladesh Council of Scientific and Industrial Research (BCSIR) Dhaka Bangladesh.ORCID https://orcid.org/0000-0002-9371-2562

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study is to develop a cost-effective, non-destructive and rapid method for quantification of syringyl/guaiacyl (S/G) ratio content in non-wood lignin, which is based on FT-NIR spectroscopic data and chemometric modelling techniques. The S/G ratio in 22 non-wood lignins was determined by wet chemical method. Then the same samples were run with FT-NIR, and the spectroscopic data were pre-processed with Savitzky-Golay (S-G) on their 1st and 2nd derivatives. As chemometric models, principal component regression (PCR) and partial least square regression (PLSR) were assessed for quantification of S/G ratio in non-wood lignin with raw and pre-treated FT-NIR spectral data. Finally, for quantification of S/G ratio, PLSR showed the best predictive results (

Indexed as

chemometric modellingmultispecies of non‐woodsyringyl/guaiacyl ratio

Identifiers

PMID40078379
PMCPMC11896878

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