Rapid evaluation of moisture content in bamboo chips using diode array near infrared spectroscopy

Abstract

Moisture in biomass plays important role during storage, combustion and pelletization. In order to measure moisture content in bamboo chips, two diode array near-infrared instruments, NIR-Gun (600-1100 nm at 2 nm intervals) and Micro-NIR (1150-2150 nm at 7 nm intervals), were used for scanning bamboo chips. Total number of samples used for developing model after removing outliers was 252. The circumference and moisture content of bamboos used were in the range between 16-39 cm and 39-86% wet basis (wb) respectively. Partial least squares regression technique was used to develop the model to predict the moisture content in bamboo chips. The R2, SECV, SEP, bias and RPD of optimum model of NIR-Gun were found to be 0.924, 2.871% wb, 2.385% wb, -0.250% wb and 3.656, while for Micro-NIR model the values were found to be 0.743, 4.349% wb, 4.499% wb, 0.026% wb and 1.972 respectively. In prediction of moisture content in bamboo chip, both models show the effect of different constituents of bamboo more than moisture. This study indicates that the results are suitable for screening the moisture content in bamboo chips. This would be helpful for process controlling using the moisture parameter during drying, pelletization and thermochemical conversion.