Neosinocalamus affinis Keng is widely grown in south-western China for pulp and paper production. Rapid assessment of the chemical properties of N. affinis is necessary for both bamboo breeding and industrial utilization. This study was performed to investigate the abilities of Fourier transform near-infrared spectroscopy in the diffuse reflectance mode (FT-NIR-DR) and Fourier transform infrared attenuated total reflectance (FT-IR-ATR) spectroscopy to predict the contents of holocellulose, a-cellulose, Klason lignin, and NaOH extractives in N. affinis. Partial least squares regression models based on the raw and preprocessed spectra, including multiplicative scatter correction (MSC) and Savitzky-Golay 1st and 2nd derivative spectra, were developed for the chemical components of bamboo. The NIR-based calibrations displayed better performance than those using FT-IR-ATR spectra. The best calibrations developed by both methods for properties all had satisfactory correlations, with coefficient of determination (R 2 c ) values ranging from 0.81 (Klason lignin by FT-IR and MSC) to 0.98 (a-cellulose by FT-NIR and 2nd derivative), and root mean standard error of calibration between 0.50 and 1.47%. When applied to prediction sets, the correlations were good, with R 2 p above 0.68. The results demonstrate that both spectroscopic methods, combined with chemometric strategies, could rapidly predict the chemical composition of bamboo.