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Rapid determination of biochar energy quality is fundamental for the purpose of biomass efficient utilization. In this work, visible and near-infrared spectroscopy was used to measure ash, volatile matter, fixed carbon content and calorific value of biochar samples produced at different pyrolysis temperatures from agricultural biomass feedstocks. Biochar samples were detected by a USB4000 spectrometer with 400-1000nm reflectance spectra recorded for investigation. The spectra were transformed by Savitzky-Golay smoothing followed by baseline offset correction (BOC). The BOC-transformed spectra of calibration set were subjected to a partial least squares regression (PLSR) algorithm for obtaining a PLSR calibration model for each biochar property. Prediction result shows that the PLSR models developed for 400-1000nm spectra achieve good prediction performance with coefficient of determination (R2) of 0.85, 0.86, 0.87 and residual prediction deviation (RPD) of 2.61, 2.64, 2.85 for ash, volatile matter and fixed carbon content, respectively. For the prediction of biochar calorific value, the PLSR model developed for 400-780nm spectra performs better with R2 of 0.82 and RPD of 2.51 compared with the 400-1000nm spectra. It is suggested that biochar energy quality can be rapidly measured with acceptable accuracy based on a 400-1000nm spectrum which can be obtained by a low-cost spectrometer

Rapid Determination of Biochar Energy Quality Based on Visible and Near-infrared Spectroscopy (400-1000nm)