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

Abstract

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.

Authors:
 [1];  [1];  [2];  [3]
  1. University of Tennessee, Knoxville (UTK)
  2. University of Tennessee
  3. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
988247
DOE Contract Number:  
DE-AC05-00OR22725
Resource Type:
Journal Article
Journal Name:
Carbohydrate Polymers
Additional Journal Information:
Journal Volume: 81; Journal Issue: 2010; Journal ID: ISSN 0144-8617
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; AGRICULTURAL WASTES; BIOMASS; CHEMICAL COMPOSITION; FORECASTING; HYPOTHESIS; LIGNIN; MAIZE; MULTIVARIATE ANALYSIS; SPECTROSCOPY; STRAW; VALIDATION; WHEAT; Biomass; Chemical composition; FT-NIR; Corn stover; Switchgrass; Wheat straw; Broad-based model

Citation Formats

Liu, Lu, Ye, Philip, Womac, A R, and Sokhansanj, Shahabaddine. Variability of biomass chemical composition and rapid analysis using FT-NIR techniques. United States: N. p., 2010. Web. doi:10.1016/j.carbpol.2010.03.058.
Liu, Lu, Ye, Philip, Womac, A R, & Sokhansanj, Shahabaddine. Variability of biomass chemical composition and rapid analysis using FT-NIR techniques. United States. https://doi.org/10.1016/j.carbpol.2010.03.058
Liu, Lu, Ye, Philip, Womac, A R, and Sokhansanj, Shahabaddine. 2010. "Variability of biomass chemical composition and rapid analysis using FT-NIR techniques". United States. https://doi.org/10.1016/j.carbpol.2010.03.058.
@article{osti_988247,
title = {Variability of biomass chemical composition and rapid analysis using FT-NIR techniques},
author = {Liu, Lu and Ye, Philip and Womac, A R and Sokhansanj, Shahabaddine},
abstractNote = {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.},
doi = {10.1016/j.carbpol.2010.03.058},
url = {https://www.osti.gov/biblio/988247}, journal = {Carbohydrate Polymers},
issn = {0144-8617},
number = 2010,
volume = 81,
place = {United States},
year = {Thu Apr 01 00:00:00 EDT 2010},
month = {Thu Apr 01 00:00:00 EDT 2010}
}