Distributions of three cross-sectional dimensions: radial and tangential tracheid width, and cell wall thickness in different timber assortments of Norway spruce were investigated. Wood samples from a mature stand were measured with SilviScan. In the analysis, virtual trees were constructed from measurement data, and divided into three assortments: whole stem, top pulpwood and sawmill chips. Average values and distributions of the properties were calculated for all assortments, and distributions divided into earlywood and latewood across the whole tree assortment. There was considerable variation within latewood in all three cross-sectional dimensions, but variation in earlywood was slight in radial width and cell wall thickness. In earlywood, tangential tracheid width showed considerable internal variation, and the difference between earlywood and latewood in tangential width was small. Within-assortment variation of all three properties was larger than between assortments. We may conclude that only a moderate difference in pulp properties can be achieved by sorting raw material into sawmill chips and top pulpwood. Pulp fractionation into earlywood and latewood seems to be a more efficient method, since it gives classes with small within-class variation and distinct average properties. However, it should be kept in mind that the results are valid only in mature stands, where growth rate variation and juvenile wood content are small.
Preharvest information on the quality of Scots pine (Pinus sylvestris) timber is required by the forest industry in Nordic countries, due to the strong association between the technical quality and product recovery of this species in particular. The objective of this study was to assess the accuracy of estimating external quality attributes and classifying the quality of mature Scots pine trees by terrestrial laser scanning (TLS). The tree quality was estimated using a random forest approach, based on both field and TLS measurements of stem diameters, tree height and branch heights. The relative root mean squared errors of the TLS measurements for tree height, diameter, diameter at 6 m and the lowest living and OPEN ACCESSForests 2014, 5 1880 dead branch height were 7.1%, 5.9%, 8.9%, 9.6% and 42.9%, respectively. The highest errors of the branch heights were caused by the shadowing effect in the point cloud data. The quality classes were estimated accurately, based on both (field and TLS measured) tree attributes. Trees were classified with 95.0% and 83.6% accuracy into three operationally-important quality classes and with 87.1% and 76.4% accuracy into five classes using, field or TLS measurements, respectively. The obtained quality classification results were promising. The enhanced tree quality information could have a significant effect on planning forest management procedures, wood supply chains and optimizing the flow of raw materials. To fully integrate tree quality measurements in operational forestry, the methods used should be fully automated.
While X-ray scanning is increasingly used to measure the interior quality of logs, terrestrial laser scanning (TLS) could be used to collect information on external tree characteristics. As branches are one key indicator of wood quality, we compared TLS and X-ray scanning data in deriving whorl locations and each whorl's maximum branch and knot diameters for 162 Scots pine (Pinus sylvestris L.) log sections. The mean number of identified whorls per tree was 37.25 and 22.93 using X-ray and TLS data, respectively. The lowest TLS-derived whorl in each sample tree was an average 5.56 m higher than that of the X-ray data. Whorl-to-whorl mean distances and the means of the maximum branch and knot diameters in a whorl measured for each sample tree using TLS and Xray data had mean differences of −0.12 m and −6.5 mm, respectively. One of the most utilized wood quality indicators, tree-specific maximum knot diameter measured by X-ray, had no statistically significant difference to the tree-specific maximum branch diameter measured from the TLS point cloud. It appears challenging to directly derive comparative branch structure information using TLS and X-ray. However, some features that are extractable from TLS point clouds are potential wood quality indicators.
Cell wall thickness and tracheid radial and tangential diameter are important characteristics in papermaking. These fibre cross-sectional dimensions affect paper properties such as light scattering, and tear and tensile indexes. In the authors' previous article, the mean values and distributions of tracheid cross-sectional dimensions were obtained for Norway spruce (Picea abies). This article characterises the cross-sectional tracheid properties of Scots pine (Pinus sylvestris) using exactly the same methodology as in the previous study on Norway spruce, which enables the comparison between the tree species. The distributions for Scots pine cell wall thickness and tracheid radial diameter were similar: a narrow peak due to earlywood tracheids, and a wide peak due to latewood tracheids. The tangential diameter distributions for Scots pine were very similar in both earlywood and latewood, having one wide peak. Also, the distributions in whole stem, top pulpwood and sawmill chip assortments were quite similar. The differences between Scots pine and Norway spruce tracheid cross-sectional dimensions were fairly marginal. This is at least the case when comparing large tracheid populations, in which differences tend to even out. The situation may be different on a more detailed level of observation, for example, when individual annual rings in the different tree species are compared.
Wood procurement in sawmills could be improved by resolving detailed three-dimensional stem geometry references from standing timber. This could be achieved, using the increasingly available terrestrial point clouds from various sources. Here, we collected terrestrial laser-scanning (TLS) data from 52 Scots pines (Pinus sylvestris L.) with the purpose of evaluating the accuracy of the log geometry and analysing its relationship with wood quality. For reference, the log-specific top-end diameter, volume, tapering, sweep, basic density and knottiness were measured in a sawmill. We produced stem models from the TLS data and bucked them into logs similar to those measured in the sawmill. In comparison to the sawmill data, the log-specific TLS-based top-end diameter, volume, taper and sweep estimates showed relative mean differences of 1.6%,-2.4%,-3.0%, and 78%, respectively. The correlation coefficients between increasing taper and decreasing wood density and whorl-to-whorl distances were 0.49 and-0.51, respectively. Although the stem-model geometry was resolved from the point clouds with similar accuracy to that at the sawmills, the remaining uncertainty in defining the sweep and linking the wood quality 2 with stem geometry may currently limit the method's feasibilities. Instead of static TLS, mobile platforms would likely be more suitable for operational point cloud data acquisition.
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