Wood and Wood Products (1): A Special Issue of Journal of Near Infrared Spectroscopy

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Wood and Wood Products (1): A Special Issue of Journal of Near Infrared Spectroscopy

This Special Issue of the Journal of Near Infrared Spectroscopy showcases 17 applications of NIR spectroscopy that span the full range of the forestry value chain. There continues to be significant on-going effort in the development of global calibration models that cover multiple species and/or varying geography for chemical composition in both hardwood and softwood species. Geneticists and tree breeders seem to require endless amounts of phenotypic data on a number of physical and chemical properties, on large numbers of trees and NIR is well placed to be able to provide that data. Consequently, one paper presents the application of NIR to progeny (breeding) trials. The properties and performance of solid wood and engineered wood products are becoming increasingly important as evidenced by investigations on oriented strand board, discrimination of musical tone woods, characterisation of density in both veneer and solid wood, and the detection of knots in solid lumber. An improved calibration for moisture content in wood is presented, as is a study of wood degradation due to brown rot. As a result of renewed interest in wood biomass as a potential biofuel source, there are papers devoted to the chemical composition of wood, particularly cellulose and lignin content, as well as one paper describing the application of NIR to the measurement of solid wood calorific value. Considering the highly heterogeneous nature of the wood matrix and the spatial variation that exists for all wood properties, there are applications which explore the dependence of the wood surface on spectral acquisition for the determination of microfibril angle or that profile the variation of microfibril angle at high spatial resolution in the radial direction. The full heterogeneity of the wood matrix is shown in the two-dimensional mapping of the variation in chemical composition. As the need for mapping variation becomes more important this paper provides an indication as to where the challenges lie in the area of image analysis of NIR hyperspectral data.