In this work, multivariate data analysis was employed to correlate variables of pretreatment process of lignocellulosic biomass. Principal component analysis and partial least square methods were performed to get the inner-relationship and data interpretation between the crystallinity and other parameters of mechanical refining-assisted sodium hydroxide pretreatment followed by enzymatic saccharification of corn stover. The PCA and PLS models showed that Sodium hydroxide dosage, mechanical refining treatment, lignin removal rate and crystallinity had close inner-related relationship with the efficiency of pretreatment and enzymolysis. Alkaline reaction and mechanical refining treatment had strong influence on the crystallinity. Multivariate data analysis revealed that pretreated corn stover samples with lower crystallinity were more easily hydrolyzed by enzyme and could get more final reducing sugar. This work could offer a new methodology to get further understanding of effect of crystallinity on the crop residue lignocellulosic biomass conversion process.
- Principle component analysis (PCA)
- Partial least square (PLS)
- Lignocellulosic biomass