Multivariable Analysis Reveals the Key Variables Related to Lignocellulosic Biomass Type and Pretreatment before Enzymolysis

In this study, partial least square (PLS), a multivariable analysis, was used to simultaneously quantitatively evaluate the effects of variables related to three pretreatments (alkaline, hot water and acid) and the biomass properties of poplar, salix and corncob. The results showed that biomass type...

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Veröffentlicht in:Catalysts 2022-10, Vol.12 (10), p.1142
Hauptverfasser: Wang, Xiujun, Fan, Deliang, Han, Yutong, Xu, Jifei
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Sprache:eng
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Zusammenfassung:In this study, partial least square (PLS), a multivariable analysis, was used to simultaneously quantitatively evaluate the effects of variables related to three pretreatments (alkaline, hot water and acid) and the biomass properties of poplar, salix and corncob. The results showed that biomass type was the most important variable influencing enzymolysis reducing sugar yield (ERSY). The biomass compositions affected the ERSY more than the pretreatment conditions, among which hemicellulose and lignin played vital roles. The alkaline pretreatment had a more positive effect on the ERSY than the acid and hot water pretreatments, in which alkaline content had more influence than temperature. This work provides a deeper understanding of the material properties and the pretreatment conditions in different complex systems before enzymolysis, which might be a guidance to future study.
ISSN:2073-4344
2073-4344
DOI:10.3390/catal12101142