Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 603-609 |
| Number of pages | 7 |
| Journal | Bioresource Technology |
| Volume | 241 |
| DOIs | |
| State | Published - Jan 1 2017 |
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Keywords
- Bioenergy crop
- Cellulose
- Hemicellulose
- Lignin
- Miscanthus sinensis
- VIS/NIR spectroscopy
ASJC Scopus subject areas
- Bioengineering
- Environmental Engineering
- Renewable Energy, Sustainability and the Environment
- Waste Management and Disposal
Cite this
Determination of hemicellulose, cellulose and lignin content using visible and near infrared spectroscopy in Miscanthus sinensis. / Jin, Xiaoli; Chen, Xiaoling; Shi, Chunhai; Li, Mei; Guan, Yajing; Yu, Chang Yeon; Yamada, Toshihiko; Sacks, Erik J.; Peng, Junhua.
In: Bioresource Technology, Vol. 241, 01.01.2017, p. 603-609.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Determination of hemicellulose, cellulose and lignin content using visible and near infrared spectroscopy in Miscanthus sinensis
AU - Jin, Xiaoli
AU - Chen, Xiaoling
AU - Shi, Chunhai
AU - Li, Mei
AU - Guan, Yajing
AU - Yu, Chang Yeon
AU - Yamada, Toshihiko
AU - Sacks, Erik J.
AU - Peng, Junhua
PY - 2017/1/1
Y1 - 2017/1/1
N2 - 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.
AB - 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.
KW - Bioenergy crop
KW - Cellulose
KW - Hemicellulose
KW - Lignin
KW - Miscanthus sinensis
KW - VIS/NIR spectroscopy
UR - http://www.scopus.com/inward/record.url?scp=85020294083&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85020294083&partnerID=8YFLogxK
U2 - 10.1016/j.biortech.2017.05.047
DO - 10.1016/j.biortech.2017.05.047
M3 - Article
C2 - 28601778
AN - SCOPUS:85020294083
VL - 241
SP - 603
EP - 609
JO - Bioresource Technology
JF - Bioresource Technology
SN - 0960-8524
ER -