Rapid characterization of biomass using fluorescence spectroscopy coupled with multivariate data analysis. I. Yellow poplar (Liriodendron tulipifera L.)

JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY(2010)

引用 14|浏览1
暂无评分
摘要
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 (R-2). 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. (c) 2010 American Institute of Physics. [doi:10.1063/1.3290749]
更多
查看译文
关键词
near infrared,multivariate data analysis,infrared spectra,coefficient of determination,fluorescence spectroscopy,chemical properties,prediction model
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要