Jin XL*, Chen XL, Shi CH, Li M, Guan YJ, Yu CY, Yamada T, Sacks EJ, Peng JH.(2017) Determination of hemicellulose, cellulose and lignin content using visible and near-infrared spectroscopy in Miscanthus sinensis. Bioresource technology. 241: 603-609

编辑: 时间:2017-06-20 访问次数:76

Determination of hemicellulose, cellulose and lignin content using visible and near infrared spectroscopy in Miscanthus sinensis

Xiaoli Jin a,⇑,1, Xiaoling Chen a,1, Chunhai Shi a, Mei Li a, Yajing Guan a, Chang Yeon Yu b, Toshihiko Yamada c, Erik J. Sacks d, Junhua Peng e
a Department of Agronomy & The Key Laboratory of Crop Germplasm Resource of Zhejiang Province, Zhejiang University, Hangzhou, Zhejiang 310058, China
b Kangwon National University, Chuncheon, Gangwon 200-701, South Korea
c Field Science Center for Northern Biosphere, Hokkaido University, Sapporo, Hokkaido 060-0810, Japan
d Department of Crop Sciences, University of Illinois, Urbana-Champaign, Urbana, IL 61801, USA
e College of Agriculture, Guangdong Ocean University, Zhanjiang, Guangdong 524088, China


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.

Bioresource Technology 241 (2017) 603–609

⇑ Corresponding author.
E-mail address: jinxl@zju.edu.cn (X. Jin).
1 Authors contributed equally to the work.