Kobori Hikaru, Gorretta Nathalie, Rabatel Gilles, Bellon-Maurel Véronique, Chaix Gilles, Roger Jean-Michel, Tsuchikawa Satoru. 2013. Applicability of Vis-NIR hyperspectral imaging for monitoring wood moisture content (MC). Holzforschung, 67 (3) : 307-314.
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Quartile : Q1, Sujet : MATERIALS SCIENCE, PAPER & WOOD / Quartile : Q1, Sujet : FORESTRY
Résumé : 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.
Mots-clés Agrovoc : bois, teneur en eau, Fagus sylvatica, Pinus sylvestris, imagerie, spectroscopie infrarouge
Classification Agris : K50 - Technologie des produits forestiers
U30 - Méthodes de recherche
F60 - Physiologie et biochimie végétale
Champ stratégique Cirad : Hors axes (2005-2013)
Auteurs et affiliations
- Kobori Hikaru, Nagoya University (JPN)
- Gorretta Nathalie, IRSTEA (FRA)
- Rabatel Gilles, IRSTEA (FRA)
- Bellon-Maurel Véronique, IRSTEA (FRA)
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Chaix Gilles, CIRAD-BIOS-UMR AGAP (FRA)
ORCID: 0000-0003-2015-0551
- Roger Jean-Michel, IRSTEA (FRA)
- Tsuchikawa Satoru, Nagoya University (JPN)
Source : Cirad - Agritrop (https://agritrop.cirad.fr/569014/)
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