Multivariate Statistical Analysis of X-Ray Spectra From Cellulose: A New Method to Determine Degree of Crystallinity and Predict Hydrolysis Rates

Enzymatic hydrolysis of cellulose by cellulases is one of the major steps in the production of bioethanol from lignocellulosics. However, biomass is not very susceptible to enzymatic attack and crystallinity of substrates is one key property that determines the hydrolysis rates. In this work, by quantifying the contributions of amorphous and crystalline cellulose to the X-ray spectra of cellulose with intermediate degrees of crystallinity, a new method to obtain consistent crystallinity numbers has been developed. Multivariate statistical analysis was applied to spectra from cellulose of various origins and crystallinity indices to reduce their dimensionality. The method has been validated by predicting the crystallinities of samples presenting various ratios of commercial crystalline cellulose and amorphous cellulose, both with known crystallinity index. The crystallinity indices obtained from our method were linearly related with the hydrolysis rates. Hydrolysis rates of various cellulose samples could be predicted by performing regression after dimensionality reduction of the spectra. Since the method has been tested for cellulose of different origins, we believe that it can be generalized to accurately obtain the degree of crystallinity of a wide range of varieties of cellulose, possibly lignocellulose.