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Author |
Wittner, N.; Gergely, S.; Slezsák, J.; Broos, W.; Vlaeminck, S.E.; Cornet, I. |
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Title |
Follow-up of solid-state fungal wood pretreatment by a novel near-infrared spectroscopy-based lignin calibration model |
Type |
A1 Journal article |
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Year  |
2023 |
Publication |
Journal of microbiological methods |
Abbreviated Journal |
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Volume |
208 |
Issue |
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Pages |
106725-106727 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Sustainable Energy, Air and Water Technology (DuEL); Biochemical Wastewater Valorization & Engineering (BioWaVE) |
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Abstract |
Lignin removal plays a crucial role in the efficient bioconversion of lignocellulose to fermentable sugars. As a delignification process, fungal pretreatment has gained great interest due to its environmental friendliness and low energy consumption. In our previous study, a positive linear correlation between acid-insoluble lignin degradation and the achievable enzymatic saccharification yield has been found, hereby highlighting the importance of the close follow-up of lignin degradation during the solid-state fungal pretreatment process. However, the standard quantification of lignin, which relies on the two-step acid hydrolysis of the biomass, is highly laborious and time-consuming. Vibrational spectroscopy has been proven as a fast and easy alternative; however, it has not been extensively researched on lignocellulose subjected to solid-state fungal pretreatment. Therefore, the present study examined the suitability of near-infrared spectroscopy (NIR) for the rapid and easy assessment of lignin content in poplar wood pretreated with Phanerochaete chrysosporium. Furthermore, the predictive power of the obtained calibration model and the recently published ATR-FTIR spectroscopy-based model were compared for the first time using the same fungus-treated wood data set. PLSR was used to correlate the NIR spectra to the acid-insoluble lignin contents (19.9%-27.1%) of pretreated wood. After normalization and second derivation, a PLSR model with a good coefficient of determination (RCV2 = 0.89) and a low root mean square error (RMSECV = 0.55%) were obtained despite the heterogeneous nature of the fungal solid-state fermentation. The performance of this PLSR model was comparably good to the one obtained by ATR-FTIR (RCV2 = 0.87) while it required more extensive spectral pre-processing. In conclusion, both methods will be highly useful for the high-throughput and user-friendly monitoring of lignin degradation in a solid-state fungal pretreatment-based biorefinery concept. |
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Wos |
000983287400001 |
Publication Date |
2023-04-13 |
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ISSN |
0167-7012 |
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Additional Links |
UA library record; WoS full record |
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Open Access |
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no |
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Call Number |
UA @ admin @ c:irua:195814 |
Serial |
9038 |
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Author |
Wittner, N.; Slezsák, J.; Broos, W.; Geerts, J.; Gergely, S.; Vlaeminck, S.E.; Cornet, I. |
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Title |
Rapid lignin quantification for fungal wood pretreatment by ATR-FTIR spectroscopy |
Type |
A1 Journal article |
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Year |
2023 |
Publication |
Spectrochimica acta: part A: molecular and biomolecular spectroscopy |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
121912 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Sustainable Energy, Air and Water Technology (DuEL); Biochemical Wastewater Valorization & Engineering (BioWaVE) |
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Abstract |
Lignin determination in lignocellulose with the conventional two-step acid hydrolysis method is highly laborious and time-consuming. However, its quantification is crucial to monitor fungal pretreatment of wood, as the increase of acid-insoluble lignin (AIL) degradation linearly correlates with the achievable enzymatic saccharification yield. Therefore, in this study, a new attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy method was developed to track fungal delignification in an easy and rapid manner. Partial least square regression (PLSR) with cross-validation (CV) was applied to correlate the ATR-FTIR spectra with the AIL content (19.9%–27.1%). After variable selection and normalization, a PLSR model with a high coefficient of determination ( |
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Wos |
000985309100010 |
Publication Date |
2022-09-22 |
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Series Volume |
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Edition |
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ISSN |
1386-1425 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
4.4 |
Times cited |
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Open Access |
OpenAccess |
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Notes |
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Approved |
Most recent IF: 4.4; 2023 IF: 2.536 |
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Call Number |
UA @ admin @ c:irua:190328 |
Serial |
7201 |
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