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Appl Spectrosc. 2008 Aug;62(8):854-9. doi: 10.1366/000370208785284295.

Discriminant analyzing system for wood wastes using a visible-near-infrared chemometric imaging technique.

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Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, Japan.


A new optical system was developed and applied to automated separation of wood wastes, using a combined technique of visible-near-infrared (Vis-NIR) imaging analysis and chemometrics. Three kinds of typical wood wastes were used, i.e., non-treated, impregnated, and plastic-film overlaid wood. The classification model based on soft independent modeling of class analogy (SIMCA) was examined using the difference luminance brightness of a sample. Our newly developed system showed a good/promising performance in separation of wood wastes, with an average rate of correct separation of 89%. Hence, it is concluded that the system is efficiently feasible for online monitoring and separation of wood wastes in recycling mills.

[Indexed for MEDLINE]

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