详细信息
Correlation of Near Infrared Spectroscopy Measurements with the Surface Roughness of Wood ( SCI-EXPANDED收录 EI收录) 被引量:7
文献类型:期刊文献
英文题名:Correlation of Near Infrared Spectroscopy Measurements with the Surface Roughness of Wood
作者:Zhang, Maomao[1] Liu, Yana[1] Yang, Zhong[1]
通信作者:Yang, Z[1]
机构:[1]Chinese Acad Forestry, Res Inst Wood Ind, Beijing 100091, Peoples R China
年份:2015
卷号:10
期号:4
起止页码:6953-6960
外文期刊名:BIORESOURCES
收录:;EI(收录号:20212410501702);Scopus(收录号:2-s2.0-85107656461);WOS:【SCI-EXPANDED(收录号:WOS:000366990800052)】;
基金:The authors are grateful for the support of the China National Natural Science Fund (Grant No. 31370711), and the support of the Ministry of Science and Technology of the People's Republic of China (Grant No. 2012104006).
语种:英文
外文关键词:Wood; Surface roughness; Near infrared spectroscopy; Correlation
摘要:The surface roughness of Chinese fir and Eucalyptus wood samples were measured using the stylus profile method in order to investigate the correlation between near infrared (NIR) spectroscopy and surface roughness. The results showed that the NIR spectra absorption showed differences among samples from different surface roughnesses, and the absorption decreased with the increase of the surface roughness. A strong relationship was found between the surface roughness parameters, i.e., the arithmetical mean deviation of the profile (R-a), the ten-point height of irregularities (R-z), and the maximum height of profile (R-y). Based on the NIR spectra of the Chinese fir wood samples and the mixed wood samples of the two wood species, and the correlation coefficients of these two types of wood samples in a calibration set were 0.77 to 0.83 and 0.67 to 0.74, respectively. A relatively poor correlation was found in the model based on the Eucalyptus samples; however, it was still significant. These results suggested that there was relative information about the surface roughness from the NIR spectra, which further illustrated that the surface roughness may influence the effect of models for wood properties built by NIR data.
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