Visible-Near Infrared Spectral Sensing Coupled with Chemometric Analysis as a Method for on-line Prediction of Milled Biomass Composition Pre-Pelletising
Restricted accessResearch articleFirst published online June, 2012
Visible-Near Infrared Spectral Sensing Coupled with Chemometric Analysis as a Method for on-line Prediction of Milled Biomass Composition Pre-Pelletising
Chemical composition of biomass is critical to conversion efficiency during pelletisation. Visible-near infrared (vis–NIR) spectral sensing is a rapid and non-destructive sensing technology. The potential of on-line vis–NIR spectral sensing, in conjunction with chemometrics, to predict moisture, carbon and ash contents of milled Miscanthus and two short rotation coppice willow varieties was assessed. Spectroscopic information within the vis–NIR waveband of 400–1000 nm was analysed. Principal component analysis was successfully used to distinguish between the three varieties of biomass. Partial least squares regression validation models for moisture prediction over a range of 1.9–37.0% gave a coefficient of determination (r2) of 0.95 with a root mean square error of prediction of 2.5%. Carbon and ash cross-validation models achieved r2 = 0.85 and 0.50, respectively. These results were for a multiple biomass variety sample set. Results demonstrate on-line vis–NIR spectral sensing combined with chemometrics has the potential to be employed in an integrated pelletising management system.
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