Measurement of key compositional parameters in two species of energy grass by Fourier transform infrared spectroscopy

Gordon G. Allison, Catherine Morris, Edward Hodgson, Jenny Jones, Michal Kubacki, Tim Barraclough, Nicola Yates, Ian Shield, Anthony V. Bridgwater, Iain S. Donnison

Research output: Contribution to journalArticlepeer-review

Abstract

Two energy grass species, switch grass, a North American tuft grass, and reed canary grass, a European native, are likely to be important sources of biomass in Western Europe for the production of biorenewable energy. Matching chemical composition to conversion efficiency is a primary goal for improvement programmes and for determining the quality of biomass feed-stocks prior to use and there is a need for methods which allow cost effective characterisation of chemical composition at high rates of sample through-put. In this paper we demonstrate that nitrogen content and alkali index, parameters greatly influencing thermal conversion efficiency, can be accurately predicted in dried samples of these species grown under a range of agronomic conditions by partial least square regression of Fourier transform infrared spectra (R2 values for plots of predicted vs. measured values of 0.938 and 0.937, respectively). We also discuss the prediction of carbon and ash content in these samples and the application of infrared based predictive methods for the breeding improvement of energy grasses.
Original languageEnglish
Pages (from-to)6428-6433
Number of pages6
JournalBioresource Technology
Volume100
Issue number24
DOIs
Publication statusPublished - Dec 2009

Keywords

  • ash content
  • nitrogen content
  • alkali index
  • energy grasses
  • FTIR
  • bioenergy
  • chemical engineering

Fingerprint

Dive into the research topics of 'Measurement of key compositional parameters in two species of energy grass by Fourier transform infrared spectroscopy'. Together they form a unique fingerprint.

Cite this