Untreated wooden surfaces degrade when exposed to varying doses of natural weathering. In this study, thin wood samples were studied for weathering effects with the aim of modeling the degradation utilizing Near-infrared hyperspectral imaging. Several sets of samples were exposed outdoors for time intervals from 0 to 21 days, and one set of samples was exposed to UV-radiation in a laboratory chamber. Spectra of earlywood and latewood were extracted from the hyperspectral image cubes and changes in the spectra were modeled as a function of UV solar radiation to see if the weathering deterioration was reflected in the NIR spectra. The model was obtained using Tikhonov regression, an algorithm that yields robust prediction models when predicting new test data. Lignin and holocellulose content were estimated on selected samples separately for early- and latewood using a thermogravimetric analysis (TGA). The thermogravimetric curves showed a clear trend with the progress of weathering of the samples, for both earlywood and latewood and both for the outdoor and the UV chamber exposed samples. This indicates that NIR spectroscopy can also be used to model lignin content in the wood. Further studies are planned to confirm this. The result from this work is a first step towards a weather dose model determined by temperature and moisture content on the wooden surface in addition to the solar UV radiation.

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