This review article introduces recent scientific and technical reports due to near infrared spectroscopy (NIRS) at wood science and technology, most of which was published between 2006 and 2013. Many researchers reported that NIR technique was useful to detect multi traits of chemical, physical, mechanical and anatomical properties of wood materials although it was widely used in a state where characteristic cellular structure was retained. However, we should be sensitive and careful for application of NIRS, when spectra coupled with chemometrics presents unexpected good results (especially, for mechanical physical and anatomical properties). The real application for on-line or at-line monitoring in wood industry is desired as next step. Basic spectroscopic research for wooden material is also progressed. It should be a powerful and meaningful analytical spectroscopic tool.
Visible-near-infrared hyperspectral imaging was tested for its suitability for monitoring the moisture content (MC) of wood samples during natural drying. Partial least-squares regression (PLSR) prediction of MC was performed on the basis of average reflectance spectra obtained from hyperspectral images. The validation showed high prediction accuracy. The results were compared concerning the PLSR prediction of MC mapping from raw spectra and standard normal variate (SNV) treatment. SNV pretreatment leads to the best results for visualizing the MC distribution in wood. Hyperspectral imaging has a high potential for monitoring the water distribution of wood. (Résumé d'auteur
The intention of this exploratory study was to determine whether near-infrared spectroscopy, combined with multivariate statistical modeling, could become a swift and accurate tool for identifying sub-alpine fir within a typical spruce-pine-fir (SPF) lumber mix in the green chain of a sawmill. This need arises from the difficulty encountered in the drying sub-alpine fir. Its identification and removal from the SPF mix before kiln drying may be quite beneficial for producing high quality lumber. Near-infrared spectra were obtained from scanning of small specimens that were prepared from freshly cut trees. The results of the initial principal component analysis indicated that all four components could be used for species differentiation with the help of partial least squares discriminant analysis. All specimens in the training set were fitted into the correct subgroup of either fir or spruce-pine groups. The test set was validated and it revealed that all specimens were correctly classified. The outcome also confirmed that near-infrared spectroscopy combined with multivariate statistical modeling could be a suitable prediction model for separation of sub-alpine fir from the SPF mix.
Near infrared (NIR) spectra obtained from 100 Japanese larch (Larix kaempferi) wood samples containing various amounts of moisture were used to examine the effect of moisture conditions on the accuracy of predicting wood density. Partial least squares regression (PLS-R) analysis was performed to predict wood density under air dry (DEN_ar), water impregnated (DEN_wi) and oven dry (DEN_ov) conditions. The NIR spectra varied with the moisture conditions of the wood, where the characteristic absorbance bands in the vicinity of 7320 cm −1 (1366 nm), 7160 cm −1 (1400 nm) and 7000 cm −1 (1428 nm) were related to cellulose and water. The spectral differences between high-and low-density samples varied depending on the moisture conditions; high-density samples showed low absorbance values at 7160 cm −1 when wet and showed high absorbance values at 7320 cm −1 and 7000 cm −1 when dry. DEN_ar, DEN_wi and DEN_ov could be predicted using spectra collected from the corresponding moisture conditions [coefficient of determination (R 2 ) = 0.79-0.89; standard error of prediction (SEP) = 24-26 kg m −3 ]. Prediction of DEN_ar and DEN_ov could also be achieved using spectra collected from various moisture conditions (R 2 = 0.86-0.87, SEP = 22 kg m −3 ). The loadings from PLS-R analysis indicated that the absorption bands in the vicinity of 7320 cm −1 , 7160 cm −1 and 7000 cm −1 played an important role in predicting wood density. NIR spectroscopy has the potential to predict wood density independently of the moisture content of the sample.
In the present study, colour changes in black alder (Alnus glutinosa L. Gaertn.) and beech (Fagus sylvatica L.) wood veneers subjected to heat treatment at 190°C for different time spans were investigated. The potential of CIELab system and near infrared (NIR) spectroscopy were used to evaluate the colour changes. The changes in colour appeared mostly by the reduction in lightness which is related to the degradation of hemicelluloses during heat treatment in both wood species. It was found that black alder discoloured much more than beech veneers under same treatment conditions. NIR spectra revealed that the dark colour that wood veneers get under heat exposure is due to the chemical decomposition of lignin and hemicelluloses. Heat treatment could, therefore, enhance the use of such veneers for value added products in furniture manufacturing as an alternative to expensive tropical species.
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