Wood extractives, the non-cell wall components that can be removed by solvents, can play an important role in the protection of the living tree as well as derived wood products. On the other hand they can be detrimental for pulp and paper, paint and varnish films and adhesives. The objective of this work was to develop near infrared-based partial least squares regression models for the prediction of wood extractives. The developed models are well suited for screening of the ethanol and total extractives content of Eucalyptus globulus wood. The models for the prediction of ethanol extractives with residual prediction deviations above 5 are also suited for quality control. It is shown that samples with high extractives content always have a more intense OH combination band than the samples with low extractives content and that near infrared can be used for a rough estimation of the relative performance of the reference methods.

Item Type:	Refereed Article
Keywords:	Eucalyptus globulus extractives NIR near-infra-red spectroscopy
Research Division:	Agricultural, Veterinary and Food Sciences
Research Group:	Forestry sciences
Research Field:	Tree improvement (incl. selection and breeding)
Objective Division:	Plant Production and Plant Primary Products
Objective Group:	Forestry
Objective Field:	Hardwood plantations
UTAS Author:	Potts, BM (Professor Brad Potts)
ID Code:	82211
Year Published:	2012
Funding Support:	Australian Research Council (LP0884001)
Web of Science® Times Cited:	22
Deposited By:	Plant Science
Deposited On:	2013-01-21
Last Modified:	2014-12-12
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