Comparison of carbohydrate composition in lignocellulosic biomass by high performance liquid chromatography and gas chromatography analysis

The carbohydrate composition (glucose, xylose, mannose, galactose, and arabinose) of lignocellulosic biomass Liriodendron tulipifera, Populus nigra × maximowiczii, alba glandulosa, euramericana, Salix alba, Quercus variabilis, Robinia pseudoacacia, Zelkova serrata, Abies holophylla, Pinus rigida, rice straw, peanut hull was investigated based on high-performance liquid chromatography (HPLC) gas (GC) analyses derived from ASTM NREL methods. glucose content higher in HPLC than GC analysis, the arabinose contents were analysis. difference noticeable glucose, holophylla this affected by species. A decision tree, as a data mining artificial intelligence method, is reliable simple variable selection tool. This technique used for analysis classification. Accordingly, 432 monosaccharide reading methods model checking. It found that most important splitting other monosaccharides did not influence assay decision. However, determination method each sample should be considered comprehensively future studies.