Journal
BIORESOURCE TECHNOLOGY
Volume 241, Issue -, Pages 603-609Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.biortech.2017.05.047
Keywords
VIS/NIR spectroscopy; Miscanthus sinensis; Hemicellulose; Cellulose; Lignin; Bioenergy crop
Funding
- DOE Office of Science, Office of Biological and Environmental Research (BER), United States [DE-SC0006634, DE-SC0012379]
- U.S. Department of Energy (DOE) [DE-SC0006634, DE-SC0012379] Funding Source: U.S. Department of Energy (DOE)
- Grants-in-Aid for Scientific Research [17H04615] Funding Source: KAKEN
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Lignocellulosic components including hemicellulose, cellulose and lignin are the three major components of plant cell walls, and their proportions in biomass crops, such as Miscanthus sinensis, greatly impact feed stock conversion to liquid fuels or bio-products. In this study, the feasibility of using visible and near infrared (VIS/NIR) spectroscopy to rapidly quantify hemicellulose, cellulose and lignin in M. sinensis was investigated. Initially, prediction models were established using partial least squares (PLS), least squares support vector machine regression (LSSVR), and radial basis function neural network (RBF_NN) based on whole wavelengths. Subsequently, 23, 25 and 27 characteristic wavelengths for hemicellulose, cellulose and lignin, respectively, were found to show significant contribution to calibration models. Three determination models were eventually built by PLS, LS-SVM and ANN based on the characteristic wavelengths. Calibration models for lignocellulosic components were successfully developed, and can now be applied to assessment of lignocellulose contents in M. sinensis. (C) 2017 Elsevier Ltd. All rights reserved.
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