TY - JOUR
T1 - Analysis of the lignocellulosic components of peat samples with development of near infrared spectroscopy models for rapid quantitative predictions
AU - Hayes, D. J.M.
AU - Hayes, M. H.B.
AU - Leahy, J. J.
N1 - Publisher Copyright:
© 2015 Elsevier Ltd.
PY - 2015/6/15
Y1 - 2015/6/15
N2 - Analytical data and quantitative near infrared (NIR) spectroscopy models for various lignocellulosic components (including Klason lignin and the constituent sugars glucose, xylose, mannose, arabinose, galactose, and rhamnose), moisture, and ash were obtained for 53 peat samples. These included samples with high, medium, and low degrees of humification. Klason lignin was the main constituent and was greatest in the samples classified as being highly humified, with structural sugars the lowest in this class. The total sugars contents of all samples were considered to be insufficient to allow for their use in biorefining hydrolysis processes for the production of chemicals and biofuels. NIR models were developed for spectral datasets obtained from the samples in their unprocessed (wet), dry and unground, and dry and ground states. Typically the most accurate models were based on the spectra of dry and ground samples. However the NIR models for the wet samples still offered reasonable predictive capabilities. All models were suitable at least for sample screening, with the models for total sugars, glucose, xylose, galactose, and moisture suitable for quantitative analyses.
AB - Analytical data and quantitative near infrared (NIR) spectroscopy models for various lignocellulosic components (including Klason lignin and the constituent sugars glucose, xylose, mannose, arabinose, galactose, and rhamnose), moisture, and ash were obtained for 53 peat samples. These included samples with high, medium, and low degrees of humification. Klason lignin was the main constituent and was greatest in the samples classified as being highly humified, with structural sugars the lowest in this class. The total sugars contents of all samples were considered to be insufficient to allow for their use in biorefining hydrolysis processes for the production of chemicals and biofuels. NIR models were developed for spectral datasets obtained from the samples in their unprocessed (wet), dry and unground, and dry and ground states. Typically the most accurate models were based on the spectra of dry and ground samples. However the NIR models for the wet samples still offered reasonable predictive capabilities. All models were suitable at least for sample screening, with the models for total sugars, glucose, xylose, galactose, and moisture suitable for quantitative analyses.
KW - Biorefining
KW - Cellulose
KW - Lignin
KW - Near infrared
KW - Peat
KW - Rapid analysis
UR - http://www.scopus.com/inward/record.url?scp=84923778328&partnerID=8YFLogxK
U2 - 10.1016/j.fuel.2015.01.094
DO - 10.1016/j.fuel.2015.01.094
M3 - Article
AN - SCOPUS:84923778328
SN - 0016-2361
VL - 150
SP - 261
EP - 268
JO - Fuel
JF - Fuel
ER -