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20.08.2016 | Original Paper

Assessing dilute acid pretreatment of different lignocellulosic biomasses for enhanced sugar production

verfasst von: Zhanying Zhang, Tony Vancov, Shane Mackintosh, Biswajit Basu, Arvinal Lali, Guangren Qian, Philip Hobson, William O. S. Doherty

Erschienen in: Cellulose | Ausgabe 6/2016

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Abstract

In this study, dilute acid pretreatment of five biomass feedstocks viz., sugarcane trash, sugarcane bagasse, rice straw, corn stover and palm empty fruit bunch were compared at a given combined severity factor (CSF) range of 1.4–3.2 and were characterised using an alternative Simons’ staining dye—Direct Yellow 11 fraction (DY 11, molecular weight >100,000) to better understand the correlations of pretreatment effectiveness with biomass physicochemical properties and pretreatment conditions. Good polynomial correlations (n = 2) of CSF were obtained with hemicellulose removal, cellulose digestibility and glucose yield resulting in R² > 0.95. The results show that the total contents of extractives and ash have negative impacts on dilute acid pretreatment. Simons’ staining results show that DY 11 can also be used to estimate cellulose accessibility to cellulase enzymes. Good linear correlations of maximum adsorption capacity of DY 11 with CSF (R² = 0.87–0.99) and cellulose digestibility (R² = 0.91–0.99) were observed for most of the pretreated biomass samples.

Vorheriger Artikel Layer-by-layer assembly of graphene oxide on viscose fibers for the fabrication of flexible conductive devices

Nächster Artikel Functionalization of cellulose with hyperbranched polyethylenimine for selective dye adsorption and separation

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Titel: Assessing dilute acid pretreatment of different lignocellulosic biomasses for enhanced sugar production
verfasst von: Zhanying Zhang
Tony Vancov
Shane Mackintosh
Biswajit Basu
Arvinal Lali
Guangren Qian
Philip Hobson
William O. S. Doherty
Publikationsdatum: 20.08.2016
Verlag: Springer Netherlands
Erschienen in: Cellulose / Ausgabe 6/2016
Print ISSN: 0969-0239
Elektronische ISSN: 1572-882X
DOI: https://doi.org/10.1007/s10570-016-1043-6

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