Journal
HOLZFORSCHUNG
Volume 67, Issue 3, Pages 307-314Publisher
WALTER DE GRUYTER GMBH
DOI: 10.1515/hf-2012-0054
Keywords
hyperspectral imaging; moisture content (MC); Vis-NIR spectroscopy
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Funding
- Japan Society for the Promotion of Science [20-7335]
- Research and Development Projects for Application in Promoting New Policy of Agriculture, Forestry and Fisheries, Japan [22003]
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Visible-near-infrared hyperspectral imaging was tested for its suitability for monitoring the moisture content (MC) of wood samples during natural drying. Partial least-squares regression (PLSR) prediction of MC was performed on the basis of average reflectance spectra obtained from hyperspectral images. The validation showed high prediction accuracy. The results were compared concerning the PLSR prediction of MC mapping from raw spectra and standard normal variate (SNV) treatment. SNV pretreatment leads to the best results for visualizing the MC distribution in wood. Hyperspectral imaging has a high potential for monitoring the water distribution of wood.
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