详细信息
Rapid Detection of Knot Defects on Wood Surface by Near Infrared Spectroscopy Coupled with Partial Least Squares Discriminant Analysis ( SCI-EXPANDED收录 EI收录) 被引量:6
文献类型:期刊文献
英文题名:Rapid Detection of Knot Defects on Wood Surface by Near Infrared Spectroscopy Coupled with Partial Least Squares Discriminant Analysis
作者:Yang, Zhong[1] Zhang, Maomao[1] Li, Kang[1] Chen, Ling[1]
第一作者:杨忠
通信作者:Yang, Z[1]
机构:[1]Chinese Acad Forestry, Res Inst Wood Ind, Beijing 100091, Peoples R China
年份:2016
卷号:11
期号:1
起止页码:2557-2567
外文期刊名:BIORESOURCES
收录:;EI(收录号:20212610561147);Scopus(收录号:2-s2.0-85052744587);WOS:【SCI-EXPANDED(收录号:WOS:000372321200053)】;
基金:The authors are grateful for the support of the China National Natural Science Fund (Grant No. 31370711 and Grant No. 30800889).
语种:英文
外文关键词:Rapid detection; Knot defects; Wood surface; Near infrared spectroscopy; Partial least squares discriminant analysis (PLS-DA)
摘要:Natural defects, especially knots, on the surface of veneers have a great influence on the sorting and degradation of veneers. To realize rapid and accurate knot detection, a study on the possibility of detecting knots was carried out. Samples of poplar, eucalypt, and masson pine were used. The experiments mainly focused on the ability of using the models built with samples from one type of knot and normal wood to predict samples from a different type of knot and normal wood within the same wood species; and when only the samples from middle-sized knots and normal wood were used, whether or not the model based on one species could predict the samples from another species. The results showed that using the model built with small knots and normal wood to predict the larger knots and normal wood was not satisfactory, but the model based on large knots and normal wood can predict the samples from smaller knots and normal wood under a certain condition. When only the middle-sized knots and normal wood from the three species were used, the model built with eucalypt samples could predict the samples from poplar, and vice versa; however, the model built with masson pine samples could not predict the other two sample species, and vice versa.
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