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基于新型近红外光谱木质素校准模型对固态真菌木材预处理的后续研究。

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

机构信息

Research group of Biochemical Wastewater Valorization and Engineering, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerpen, Belgium.

Department of Applied Biotechnology and Food Science, Faculty of Chemical Technology and Biotechnology, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary.

出版信息

J Microbiol Methods. 2023 May;208:106725. doi: 10.1016/j.mimet.2023.106725. Epub 2023 Apr 13.

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 (R = 0.89) and a low root mean square error (RMSE = 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 (R = 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.

摘要

木质素去除在木质纤维素高效转化为可发酵糖的过程中起着至关重要的作用。作为一种脱木质素过程,真菌预处理因其环保和低能耗而受到极大关注。在我们之前的研究中,已经发现酸不溶木质素降解与可实现的酶解糖化产率之间存在正线性相关性,因此强调了在固态真菌预处理过程中密切跟踪木质素降解的重要性。然而,木质素的标准量化依赖于生物质的两步酸水解,这是非常费力和耗时的。振动光谱已被证明是一种快速简便的替代方法;然而,它在固态真菌预处理的木质纤维素上的研究还不够广泛。因此,本研究考察了近红外光谱(NIR)在快速、轻松评估用黄孢原毛平革菌预处理的杨树木质素含量方面的适用性。此外,首次使用相同的真菌处理木材数据集比较了获得的校准模型和最近发表的基于衰减全反射傅里叶变换红外光谱(ATR-FTIR)的模型的预测能力。偏最小二乘法(PLSR)用于将 NIR 光谱与预处理木材的酸不溶木质素含量(19.9%-27.1%)相关联。经过归一化和二阶导数处理后,尽管真菌固态发酵具有不均匀性,但仍获得了具有良好决定系数(R = 0.89)和低均方根误差(RMSE = 0.55%)的 PLSR 模型。该 PLSR 模型的性能与通过 ATR-FTIR 获得的模型相当(R = 0.87),而它需要更广泛的光谱预处理。总之,这两种方法都将非常有助于在基于固态真菌预处理的生物炼制概念中进行高通量和用户友好的木质素降解监测。

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