A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Rapid characterization of biomass using fluorescence spectroscopy coupled with multivariate data analysis. I. Yellow poplar (Liriodendron tulipifera L.)
This is the first of a two-paper series that reports on the use of fluorescence spectroscopy coupled with multivariate data analysis as a potential process analytical tool to develop calibration and prediction models for some physical and chemical properties of yellow poplar (Liriodendron tulipifera L.). Waste streams emanating from the processing of this wood species may potentially serve as feedstock for biofuels and biochemicals With the exception of holocellulose content, all the properties considered in the study were predicted with moderate to strong coefficient of determination (R2). Fluorescence spectra-based prediction model for each property considered in this study was compared with near infrared (NIR) spectra-based prediction models of similar properties from a previous study using the same population. The NIR-based prediction models exhibited slightly superior model strength over the fluorescence spectra-based prediction models of similar properties.
Rapid characterization of biomass using fluorescence spectroscopy coupled with multivariate data analysis. I. Yellow poplar (Liriodendron tulipifera L.)
This is the first of a two-paper series that reports on the use of fluorescence spectroscopy coupled with multivariate data analysis as a potential process analytical tool to develop calibration and prediction models for some physical and chemical properties of yellow poplar (Liriodendron tulipifera L.). Waste streams emanating from the processing of this wood species may potentially serve as feedstock for biofuels and biochemicals With the exception of holocellulose content, all the properties considered in the study were predicted with moderate to strong coefficient of determination (R2). Fluorescence spectra-based prediction model for each property considered in this study was compared with near infrared (NIR) spectra-based prediction models of similar properties from a previous study using the same population. The NIR-based prediction models exhibited slightly superior model strength over the fluorescence spectra-based prediction models of similar properties.
Rapid characterization of biomass using fluorescence spectroscopy coupled with multivariate data analysis. I. Yellow poplar (Liriodendron tulipifera L.)
Nkansah, K. (author) / Dawson-Andoh, B. (author)
Journal of Renewable and Sustainable Energy ; 2 ; 023103-
2010-03-01
12 pages
Article (Journal)
Electronic Resource
English
| British Library Online Contents | 2015
| American Institute of Physics | 2010