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Wednesday 11 October 2017

Calibration of SilviScan data of Cryptomeria japonica wood concerning density and microfibril angles with NIR hyperspectral imaging with high spatial resolution

Author
Te Ma / Tetsuya Inagaki / Satoru Tsuchikawa
Published Online: 2017-01-13 | DOI: https://doi.org/10.1515/hf-2016-0153

Abstract

Wood density and microfibril angle (MFA) are strongly correlated with wood stiffness, swelling/shrinkage, and its anisotropy. Understanding the spatial distribution of these data is critical for solid timber applications. In this study, near-infrared (NIR) hyperspectral imaging has been calibrated for evaluation of wood density and MFA in an effective manner. Briefly, five wood samples collected from both normal wood (NW) and compression wood (CW) moieties of two different Cryptomeria japonica trees were analyzed. Partial least squares (PLS) regression analysis was performed to determine the relationship between X-ray densitometry data obtained by SilviScan and NIR spectra, and cross-validation (leave-one-out) approach served for prediction performances. The validation coefficient of determination (r2) between the predicted densities by the NIR technique and the X-ray data was 0.83 with a root mean squared error of cross-validation (RMSECV) of 105.2 kg m−3. Regarding MFA, the r2was 0.77 and RMSECV 5.36°. Wood density was successfully maped as well as the MFA at a high spatial resolution. As a result, the detection of annual growth ring features and evaluation of aspects of heterogeneous wood quality has been facilitated. The mapping results were visually checked by looking at the difference between earlywood (EW) and latewood (LW) for density and by means of the Mäule color reaction indicating high lignin contents in CW in terms of MFA validation as CWs have high MFA values.
Keywords: compression wood (CW); microfibril angle (MFA); NIR hyperspectral imaging; partial least squares (PLS) regression analysis; SilviScan system; wood density

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About the article

Received: 2016-09-15
Accepted: 2016-12-07
Published Online: 2017-01-13
Published in Print: 2017-04-01
Citation Information: Holzforschung, ISSN (Online) 1437-434X, ISSN (Print) 0018-3830, DOI: https://doi.org/10.1515/hf-2016-0153.
©2017 Walter de Gruyter GmbH, Berlin/Boston. 
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https://www.degruyter.com/view/j/hfsg.2017.71.issue-4/hf-2016-0153/hf-2016-0153.xml?rskey=BCyRzR&result=1
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