Compositional Analysis of Biomass Feedstocks by Near Infrared Reflectance Spectroscopy

Near infrared reflectance spectroscopy (NIRS) has been used extensively in lignocellulose analysis of forages and should be useful in predicting the chemical composition of biomass feedstocks. We determined the chemical composition of several woody and herbaceous feedstocks (121 samples in total) in the laboratory and used these data to calibrate an NIR spectrometer. Samples were analysed for ethanol extractives, ash, lignin, uronic acids, arabinose, xylose, mannose, galactose, glucose, C, H, N and O. A modified partial-least-squares statistical technique was used to develop calibration equations. Twenty samples not used in the calibration were used for independent validation of the prediction equations. Calibration equations were developed successfully for concentrations of all constituents except H and O. When the equations were applied to the 20 validation samples, only extractives, lignin and arabinose had validation statistics within the control limits. Mannose, galactose, C, H and O could not be predicted with any precision or accuracy. These results indicate that NIRS can be used to predict the chemical composition of a broad range of biomass feedstocks. Increasing the population size for calibration and (or) developing more narrowly based calibrations may improve prediction ability and result in a technique that should be useful in rapid analysis of biomass feedstocks for research and industry.