文献类型：期刊文献

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

作者：Jin, Xiaoli[1,2];Chen, Xiaoling[1,2];Shi, Chunhai[1,2];Li, Mei[1,2];Guan, Yajing[1,2];Yu, Chang Yeon[3];Yamada, Toshihiko[4];Sacks, Erik J.[5];Peng, Junhua[6]

机构：[1]Zhejiang Univ, Dept Agron, Hangzhou 310058, Zhejiang, Peoples R China;[2]Zhejiang Univ, Key Lab Crop Germplasm Resource Zhejiang Prov, Hangzhou 310058, Zhejiang, Peoples R China;[3]Kangwon Natl Univ, Chunchon 200701, Gangwon, South Korea;[4]Hokkaido Univ, Field Sci Ctr Northern Biosphere, Sapporo, Hokkaido 0600810, Japan;[5]Univ Illinois, Dept Crop Sci, Urbana, IL 61801 USA;[6]Guangdong Ocean Univ, Coll Agr, Zhanjiang 524088, Guangdong, Peoples R China

年份：2017

卷号：241

起止页码：603

外文期刊名：BIORESOURCE TECHNOLOGY

收录：SCI-EXPANDED(收录号：WOS:000405502400072)、、WOS

基金：This research was supported by the DOE Office of Science, Office of Biological and Environmental Research (BER), United States, grant Nos. DE-SC0006634 and DE-SC0012379.

语种：英文

外文关键词：VIS/NIR spectroscopy; Miscanthus sinensis; Hemicellulose; Cellulose; Lignin; Bioenergy crop

外文摘要：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.