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Switchgrass varieties grown under various environments were investi-gated by dispersive and Fourier Transform Near-Infrared (NIR) spectro-meters. The collected NIR spectra were analyzed using multivariate approaches. More specifically, principal component analysis (PCA) and projection to latent structures (PLS) regression techniques were employed to classify and predict characteristics of the switchgrass samples. The multivariate results were compared to reflectance indices that are commonly used to study the physiological performance of plants. From near infrared spectra, discrimination between the two growth locations was successfully achieved by PCA. Separation based on the ecotype and the rate of fertilizer applied to the field was also possible by the multivariable analysis of the spectral data. For the classification/ discrimination of the switchgrass samples, the near infrared spectra collected by the dispersive and the Fourier Transform spectrometers provided similar results. From the two near infrared data sets robust models were developed to predict non-structural carbohydrates content and the rate of nitrogen applied to the field. However, the spectra collected by the dispersive spectrometer resulted in more accurate models for these samples.

A new simple and safe method for quantifying lignin content in lignocellulosic biomass is described. The approach consists of measuring the absorbance of a solution of whole biomass dissolved in the ionic liquid 1-n-butyl-3-methyl imidazolium chloride, [Bmim][Cl], at 440 nm via ultraviolet- (UV-) visible spectrophotometry. An extinction coefficient for a lignin standard, highly pure lignin isolated from biomass through an organosolv process, is used in conjunction with the Beer-Lambert Law to calculate the lignin concentration. Principal component analysis (PCA) of Fourier Transform-Infrared (FTIR) spectra collected for several different lignin standards was performed to understand the differences in their chemical structure and composition (e.g., the relative amounts of syringyl and guaiacyl units). A rapid FTIR analysis of the whole biomass sample with unknown lignin content is required to assist in the proper selection of the lignin standard for the subsequent spectrophotometric analysis. The proposed method was tested and validated on two biomass types: Yellow poplar and Southern pine. The spectrophotometric approach yielded lignin contents for Yellow poplar and Southern pine of 25.7 ± 1.1% and 26.7 ± 0.7%, respectively, which are comparable to the values obtained by a standard wet chemical protocol, 25.1% ± 0.7 and 26.6 ± 0.4%, respectively.