Multivariate data analysis applied in alkali-based pretreatment of corn stover

- Pulp Refining Instrument (PFI) refining assisted alkaline pretreatment and hydrolysis saccharification of corn stover were analyzed.
- The Principle Component Analysis (PCA) and Partial Least Square (PLS) were used to investigate the detail relationships of the key process variables.
- Multivariate data analysis of alkali-based pretreatment of corn stover was studied.

In this paper, variables of Pulp Refining Instrument (PFI) refining assisted alkaline pretreatment and hydrolysis saccharification of corn stover were analyzed. The process parameters were characterized by multivariate data analysis methods including Principle Component Analysis and Partial Least Square (PCA and PLS) to investigate the specific relationships of primary variables in alkali-based pretreatment of biomass. In this paper, pretreatment system was multivariate and the variables were inter-related to each other. Total alkaline charge and removal rate of lignin had greatest impact on the pretreatment and enzymatic hydrolysis.