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Follow-up of solid-state fungal wood pretreatment by a novel near-infrared spectroscopy-based lignin calibration model

木质素 校准 光谱学 红外光谱学 红外线的 固态 化学 材料科学 植物 分析化学(期刊) 生物 有机化学 光学 物理 物理化学 量子力学
作者
Nikolett Wittner,Szilveszter Gergely,János Slezsák,Waut Broos,Siegfried E. Vlaeminck,I. Cornet
出处
期刊:Journal of Microbiological Methods [Elsevier BV]
卷期号:208: 106725-106725 被引量:1
标识
DOI:10.1016/j.mimet.2023.106725
摘要

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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