An easy and reliable method for syringyl: guaiacyl ratio measurement
Source abstract
Abstract
Lignin structure elucidation is one of the main targets for biorefinery related research. Because of its complexity, obtaining reproducible results in a straight-forward way is very important. One of the values that is used to compare different lignins is the syringyl:guaiacyl (S/G) ratio, which has been measured in different ways. The most reliable result is obtained for nitrobenzene oxidation, but this involves a complex process. In this work, the S/G ratios measured by pyrolysis-gas chromatography mass spectrometry (py-GCMS) and heteronuclear single quantum coherence-nuclear magnetic resonance (HSQC-NMR) spectroscopy were compared with attenuated total reflection infrared (ATR-IR) spectroscopy results to establish a reliable, quick, and simple method for the measurement. To achieve this, two mathematical models were applied with multivariate data analysis software. A partial least squares regression model for py-GCMS gave the best result.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Lignin and Wood Chemistry · Fermentation and Sensory Analysis · Biochemical and biochemical processes
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (19)
Show source-provided references
1. Toledano, A., Serrano, L., and Labidi., J., J. Taiwan Inst. Chem. Eng. 44(4): 552(2013).10.1016/j.jtice.2013.01.009 ↗
2. Vanholme, R., Demedts, B., Morreel, K., et al., Plant Physiol. 153(3): 895(2010).10.1104/pp.110.155119 ↗
3. Kumar, P., Barret, D.M., Delwiche, M.J., et al., Ind. Eng. Chem. Res. 48(8): 3713(2009).10.1021/ie801542g ↗
4. Erdocia, X., Prado, R., Corcuera, M.A., et al., J. Ind. Eng. Chem. 20(3): 1103(2014)10.1016/j.jiec.2013.06.048 ↗
5. Prado, R., Erdocia, X., and Labidi, J., J. Chem. Technol. Biotechnol. 88(7): 1248(2013).10.1002/jctb.3965 ↗
6. Lanzalunga, O. and Bietti. M., J. Photochem. Photobiol., B 56(2-3): 85(2000).10.1016/S1011-1344(00)00054-3 ↗
7. Ona, T., Sonoda, T., Itoh, K., et al., Holzforschung 51(5): 396(1997).10.1515/hfsg.1997.51.5.396 ↗
8. Reeves, J.B., J. Dairy Sci. 69(1): 71(1986).10.3168/jds.S0022-0302(86)80371-X ↗
9. Sun, R., Lawther, J.M., and Banks, W.B., Ind. Crops Prod. 4(4): 241(1995).10.1016/0926-6690(95)00038-0 ↗
10. Martínez, A.T., Almendros, G., González-Vila, F.J., et al., Solid State NMR 15(1): 41(1999).10.1016/S0926-2040(99)00045-4 ↗
11. Sette, M., Wechselberger, R., and Crestini. C., Chem. – Eur. J. 17(34): 9529(2011).10.1002/chem.201003045 ↗
12. Nunes, C.A., Lima, C.F., Barbosa, L.C.A., et al., Bioresour. Technol. 101(11): 4056(2010).10.1016/j.biortech.2010.01.012 ↗
13. Otto, M., Chemometrics: Statistics and Computer Application in Analytical Chemistry, Wiley-VCH, Weinheim, Germany, 2007.
14. Wold, S., Sjöström, M., and Eriksson. L., Chemom. Intell. Lab. Syst. 58(2): 109(2001).10.1016/S0169-7439(01)00155-1 ↗
15. Mevik, B.H. and Wehrens, R., J. Stat. Software. 18(2): 1(2007).10.18637/jss.v018.i02 ↗
16. Depczynski, U., Frost, V.J., and Molt. K., Anal. Chim. Acta 420(2): 217(2000).10.1016/S0003-2670(00)00893-X ↗
17. Skoog, D.A., Hooler, F.J., and Nieman, T.A., Principles of Instrumental Analysis, McGraw-Hill, Madrid, Spain, 2001.
18. Yuan, T.Q., Sun, S.N., and Xu, F., et al., J. Agric. Food. Chem. 59(19): 10604(2011).10.1021/jf2031549 ↗
19. Wen, J.L., Sun, S.L., Xue, B.L., et al., Materials 6(1): 356(2013).10.3390/ma6010359 ↗