Determination of Cellulose Crystallinity of Banana Residues Using Near Infrared Spectroscopy and Multivariate Analysis

Crystallinity is an important property of lignocellulosic biomass due to its significant effect on acid/enzymatic hydrolysis. Normally, physicochemical analysis, such as powder X-ray diffraction and nuclear magnetic resonance, is used to reveal the crystallinity content. However, these analytical methods are expensive and laborious. In this context, methods that rapidly predict the crystallinity are important, even if used only for screening calibration. Thus, we intend to show the potential of near-infrared spectroscopy (NIRS) and chemometrics to replace reference methods in crystallinity determination. The results show that NIRS can be used to determine crystallinity in banana residues by the use of partial least squares regression, providing good coefficients of determination (R-cal, pred(2) > 0.82), low relative errors (< 14%) and good range error ratio (>= 7.7). The interpretation of the regression coefficients, multivariate figures of merit and external validation results indicate a strong relationship between the NIR spectrum and crystallinity in banana samples.