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Title: Near-infrared spectroscopy as a potential method for identification of anatomically similar Japanese diploxylons
Authors: Horikawa, Yoshiki
Mizuno-Tazuru, Suyako
Sugiyama, Junji  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0002-5388-4925 (unconfirmed)
Author's alias: 堀川, 祥生
Keywords: Discriminant analysis
NIR spectroscopy
Japanese diploxylons
Wood identification
Aging wood
Issue Date: 31-Jan-2015
Publisher: Springer Japan
Journal title: Journal of Wood Science
Volume: 61
Issue: 3
Start page: 251
End page: 261
Abstract: A reliable technique for distinguishing anatomically similar diploxylons, Pinus densiflora and P. thunbergii, was designed by employing near-infrared (NIR) spectroscopy in combination with multivariate analysis. In total, 24 wood blocks, with half of them being of P. densiflora and the rest of P. thunbergii, were selected from the collections of the Kyoto University xylarium and scrutinized to build an acceptable model for discriminating between the two species. The prediction model was constructed only from heartwood, and the best performance was obtained for wavenumbers of 7, 300–4, 000 cm−1 in the second derivative spectra. To apply this model to actual materials obtained from historical wooden buildings, 12 aging wood samples were analyzed and compared by microscopic identification. Unexpectedly, the spectral differences between the species were smaller than those caused by aging, and the prediction error was approximately 50 %. The spectra of the aging samples were quite distinct in the specific region characteristic of absorbed water (5, 220 cm−1); this was demonstrated clearly by principal component analysis. Therefore, for the proposed model to be suitable for use in practical applications, further investigations of aging wood samples and the corresponding spectroscopic data are necessary to understand the effects of aging on the spectral data.
Rights: The final publication is available at Springer via http://dx.doi.org/10.1007/s10086-015-1462-2.
The full-text file will be made open to the public on 31 January 2016 in accordance with publisher's 'Terms and Conditions for Self-Archiving'.
This is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。
URI: http://hdl.handle.net/2433/201492
DOI(Published Version): 10.1007/s10086-015-1462-2
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