Nondestructive Classification Analysis of Wood Soaked in Seawater by Using Near-Infrared Spectroscopy

Abstract

Abstract Large amounts of construction wood were generated as disaster waste during the 2011 Tōhoku, Japan, earthquake and tsunami. The construction wood waste had been immersed in seawater and thus contained salts. When the saltwater-immersed wood was incinerated during restoration efforts, dioxins harmful to human health were likely produced. Thus, it is necessary to determine if wood waste had been exposed to saltwater before combustion. Furthermore, online recycling of coastal wood debris containing saltwater could be applied to the disposal of industrial wastes. Near-infrared (NIR) spectroscopy was used to distinguish saltwater-immersed wood. Three wood species, Cryptomeria japonica, Chamaecyparis obtuse, and Larix kaempferi, which are commonly used in the construction of Japanese houses, were prepared. Immersion time was changed from 24 to 72 hours to investigate the time-dependent change. NIR spectra were obtained from wood samples before and after immersion in seawater and were used in classification analysis by soft independent modeling of class analogy (SIMCA). For SIMCA at immersion time of 24 hours, the percentage of correct classification was for 94 percent for Cryptomeria japonica, 96 percent for Chamaecyparis obtuse, and 92 percent for Larix kaempferi. There is no difference in the classification accuracy by the wood species and immersion time. Moreover, another classification analysis (partial least-squares discriminant analysis [PLS-DA]) was performed to raise the classification precision. The result of PLS-DA was superior to SIMCA. NIR was a powerful tool in identifying saltwater-immersed wood samples and indicated the possibility of using it at the wood-recycling factory.