Biomass representing different classes of bioenergy feedstocks, including woody and herbaceous species, was measured with 1064 nm Raman spectroscopy. Pine, oak, poplar, kenaf, miscanthus, pampas grass, switchgrass, alfalfa, orchard grass, and red clover were included in this study. Spectral differences have been identified with an emphasis on lignin guaiacyl and syringyl monomer content and carotenoid compounds. The interpretation of the Raman spectra was correlated with (13)C-nuclear magnetic resonance cross-polarization/magic-angle spinning spectra of select biomass samples. Thioacidolysis quantification of guaiacyl and syringyl monomer composition and the library of Raman spectra were used as a training set to develop a principal component analysis model for classifying plant samples and a principal component regression model for quantifying lignin guaiacyl and syringyl composition. Raman spectroscopy with 1064 nm excitation offers advantages over alternative techniques for biomass characterization, including low spectral backgrounds, higher spectral resolution, short analysis times, and nondestructive analyses.