Variability of biomass chemical composition and rapid analysis using FT-NIR techniques

被引:103
|
作者
Liu, Lu [1 ]
Ye, X. Philip [1 ]
Womac, Alvin R. [1 ]
Sokhansanj, Shahab [2 ]
机构
[1] Univ Tennessee, Dept Biosyst Engn & Soil Sci, Knoxville, TN 37996 USA
[2] Univ British Columbia, Dept Chem & Biol Engn, Vancouver, BC V6T 1Z3, Canada
关键词
Biomass; Chemical composition; FT-NIR; Corn stover; Switchgrass; Wheat straw; Broad-based model; NEAR-INFRARED SPECTROSCOPY; SWITCHGRASS PANICUM-VIRGATUM; REFLECTANCE SPECTROSCOPY; CORN STOVER; QUALITY; POPULATIONS; MOISTURE; PROTEIN; YIELD; CLASSIFICATION;
D O I
10.1016/j.carbpol.2010.03.058
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
A quick method for analyzing the chemical composition of renewable energy biomass feedstock was developed by using Fourier transform near-infrared (FT-NIR) spectroscopy coupled with multivariate analysis. The study presents the broad-based model hypothesis that a single FT-NIR predictive model can be developed to analyze multiple types of biomass feedstock. The two most important biomass feedstocks - corn stover and switchgrass - were evaluated for the variability in their concentrations of the following components: glucan, xylan, galactan, arabinan, mannan, lignin, and ash. A hypothesis test was developed based upon these two species. Both cross-validation and independent validation results showed that the broad-based model developed is promising for future chemical prediction of both biomass species; in addition, the results also showed the method's prediction potential for wheat straw. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:820 / 829
页数:10
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