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http://dx.doi.org/10.5658/WOOD.2010.38.6.526

Evaluation of Surface Moisture Content of Liriodendron tulipifera Wood in the Hygroscopic Range Using NIR Spectroscopy  

Eom, Chang-Deuk (Dept. of Forest Sciences, College of Agriculture and Life Science, Seoul National University)
Han, Yeon-Jung (Dept. of Forest Sciences, College of Agriculture and Life Science, Seoul National University)
Chang, Yoon-Sung (Dept. of Forest Sciences, College of Agriculture and Life Science, Seoul National University)
Park, Jun-Ho (Dept. of Forest Sciences, College of Agriculture and Life Science, Seoul National University)
Choi, Joon-Weon (Dept. of Forest Sciences, College of Agriculture and Life Science, Seoul National University)
Choi, In-Gyu (Dept. of Forest Sciences, College of Agriculture and Life Science, Seoul National University)
Yeo, Hwan-Myeong (Dept. of Forest Sciences, College of Agriculture and Life Science, Seoul National University)
Publication Information
Journal of the Korean Wood Science and Technology / v.38, no.6, 2010 , pp. 526-531 More about this Journal
Abstract
For efficient use of wood, it is important to control moisture of wood in processing wood. Near-infrared (NIR) spectroscopy can be used to estimate the physical and chemical properties of materials quickly and nondestructively. In this study, it was intended to measure the moisture contents on the surface of wood using NIR spectroscopy coupled with multivariate analytic statistical techniques. Because NIR spectroscopy is affected by the chemical components of the specimens and contains signal noise, a regression model for detecting moisture content of wood was established after carrying out several numerical pretreatments such as Smoothing, Derivative and Normalization in this study. It shows that the regression model using NIR absorbance in the range of 750~2,500 nm predicts the actual surface moisture content very well. Near-infrared spectroscopy technique developed in this study is expected to improve a technology to control moisture content of wood in using and drying process.
Keywords
NIR spectroscopy; surface moisture content; numerical pretreatment; signal noise;
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