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http://dx.doi.org/10.5658/WOOD.2015.43.3.304

Development of Moisture Content Prediction Model for Larix kaempferi Sawdust Using Near Infrared Spectroscopy  

Chang, Yoon-Seong (Department Forest Science, College of Agriculture and Life Sciences, Seoul National University)
Yang, Sang-Yun (Department Forest Science, College of Agriculture and Life Sciences, Seoul National University)
Chung, Hyunwoo (Department Forest Science, College of Agriculture and Life Sciences, Seoul National University)
Kang, Kyu-Young (Department of Biological and Environmental Science, College of Life Science and Biotechnology, Dongguk University)
Choi, Joon-Weon (Graduate School of International Agricultural Technology, Seoul National University)
Choi, In-Gyu (Department Forest Science, College of Agriculture and Life Sciences, Seoul National University)
Yeo, Hwanmyeong (Department Forest Science, College of Agriculture and Life Sciences, Seoul National University)
Publication Information
Journal of the Korean Wood Science and Technology / v.43, no.3, 2015 , pp. 304-310 More about this Journal
Abstract
The moisture content of sawdust must be measured accurately and controlled appropriately during storage and transportation because biological degradation could be caused by improper moisture. In this study, to measure the moisture contents of Larix kaempferi sawdust, the near-infrared reflectance spectra (Wavelength 1000-2400 nm) of sawdust were used as detection parameter. After acquiring the NIR reflection spectrum of specimens which were humidified at each relative humidity condition ($25^{\circ}C$, RH 30~99%), moisture content prediction model was developed using mathematical preprocessings (e.g. smoothing, standard normal variate) and partial least squares (PLS) analysis with the acquired spectrum data. High reliability of the MC regression model with NIR spectroscopy was verified by cross validation test ($R^2$ = 0.94, RMSEP = 1.544). The results of this study show that NIR spectroscopy could be used as a convenient and accurate method for the nondestructive determination of moisture content of sawdust, which could lead to optimize wood utilization.
Keywords
near infrared spectroscopy; sawdust; Larix kaempferi; moisture content; partial least squares regression;
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Times Cited By KSCI : 2  (Citation Analysis)
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