FT-NIR spectroscopy equipped with a fiber optic probe was used to predict the mass loss caused by a brownrot fungus (Coniophora puteana) in Scots pine heartwood. Because decay tests are impractical for generating reference data for the calibration of prediction models, the possibilities of using the concentration of heartwood extractives as a reference variable instead of mass loss was studied. The material investigated covered a wide range of natural variation in durability and diffuse reflectance infrared Fourier transform spectra were recorded from the cross section of 41 pines. The partial least square (PLS) regression models were found to be satisfactory for prediction of the mass loss and the concentration of extractives (total phenolics, resin acids, pinosylvin and pinosylvin monomethyl ether). It was concluded that FT-NIR spectroscopy has the potential to become a tool for the decay resistance grading of Scots pine heartwood timber, especially if the prediction models will be based on heartwood extractives.

Moisture content distributions of Scots pine logs in the green state were measured by a novel multi-step procedure. After sample preparation, the transverse sections of the wood surfaces were scanned by an automated scanning device with a fiber optical probe connected to a Fourier transform near-infrared spectroscope. In the course of the measurement sequences, several issues were addressed, such as surface drying, measurement geometry, ease of automation and interconnected data handling. The near-infrared (NIR) data were first modeled separately for heartwood and sapwood by means of multivariate partial least squares regression. The models for moisture content were evaluated by root mean square error of prediction, the result being 0.8% for heartwood and 10% for sapwood. The two models were then applied to the NIR data collected from sets of disks cut from nine logs. The results of the calculated moisture contents were evaluated by methods of descriptive statistics, and they indicated clear differences and trends in the distribution of moisture content in transverse or longitudinal regions of a log. Additionally, inter-tree variation in moisture content was detected.

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