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Licensed Unlicensed Requires Authentication Published by De Gruyter September 28, 2012

Applicability of Vis-NIR hyperspectral imaging for monitoring wood moisture content (MC)

Hikaru Kobori, Nathalie Gorretta, Gilles Rabatel, Véronique Bellon-Maurel, Gilles Chaix, Jean-Michel Roger and Satoru Tsuchikawa
From the journal Holzforschung

Abstract

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.


Corresponding author: Hikaru Kobori, Graduate School of Bioagricultural Sciences, Nagoya University, Furo-cho, Chikusa, Aichi 464-8601, Japan

Received: 2012-3-30
Accepted: 2012-9-3
Published Online: 2012-09-28
Published in Print: 2013-04-01

©2013 by Walter de Gruyter Berlin Boston