Yield optimization and rational function modelling of enzymatic hydrolysis of wheat straw pretreated by NaOH-delignification, autohydrolysis and their combination

A thorough efficacy assessment was performed on three wheat straw saccharification processes including NaOH-delignification, autohydrolysis and their combination, with subsequent enzymatic hydrolysis. Instead of optimizing the process for maximal sugar yield from straw, a novel perspective is provid...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Green chemistry : an international journal and green chemistry resource : GC 2015-01, Vol.17 (3), p.1683-1691
Hauptverfasser: Pihlajaniemi, Ville, Sipponen, Mika Henrikki, Pastinen, Ossi, Lehtomäki, Ilkka, Laakso, Simo
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:A thorough efficacy assessment was performed on three wheat straw saccharification processes including NaOH-delignification, autohydrolysis and their combination, with subsequent enzymatic hydrolysis. Instead of optimizing the process for maximal sugar yield from straw, a novel perspective is provided, allowing optimization of the overall yield against enzyme consumption and reaction volume. At total sugar yields above 60%, NaOH-delignification was the most efficient in terms of enzymatic and volumetric productivity, whereas at lower yields, autohydrolysis showed a comparable enzymatic and a higher volumetric productivity. The double treatment led to improved hydrolysability compared to autohydrolysis, but was the least productive due to reduced solid yields. A threshold in the delignification efficiency between 3% and 6% NaOH-loadings per straw DM resulted from the depletion of alkalinity by the released organic acids. A novel rational function model was developed for the total sugar yield, which is generally superior for describing asymptotic behaviour compared to conventional polynomial models in response surface modelling.
ISSN:1463-9262
1463-9270
DOI:10.1039/C4GC02218A