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

Xiaoli Jin, Xiaoling Chen, Chunhai Shi, Mei Li, Yajing Guan, Chang Yeon Yu, Toshihiko Yamada, Erik J. Sacks, Junhua Peng

Research output: Contribution to journalArticle

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 languageEnglish (US)
Pages (from-to)603-609
Number of pages7
JournalBioresource Technology
Volume241
DOIs
StatePublished - 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

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