Estimation of Scots pine bark biomass delivered to the wood industry in Northern Germany

被引:0
|
作者
Berendt, Ferreol [1 ,2 ]
Bajalan, Iman [1 ,3 ]
Wenig, Charlett [4 ]
Hinds, Charlotte [1 ]
Blasko, Lubomir [1 ,5 ]
Cremer, Tobias [1 ]
机构
[1] Eberswalde Univ Sustainable Dev, Dept Forest Utilizat & Timber Market, D-16225 Eberswalde, Germany
[2] Forest Educ Ctr, State Enterprise Forestry & Timber, North Rhine Westphalia, D-59755 Arnsberg, Germany
[3] Eberswalde Univ Sustainable Dev, Dept GIS & Remote Sensing, D-16225 Eberswalde, Germany
[4] Max Planck Inst Colloids & Interfaces, Dept Biomat, D-14476 Potsdam, Germany
[5] Tech Univ Zvolen, Dept Forest Harvesting Logist & Ameliorat, SK-96001 Zvolen, Slovakia
关键词
bark thickness; bark volume; bark mass; Pinus sylvestris; correlation; ARTIFICIAL NEURAL-NETWORKS; TREE DIAMETER; PICEA-ABIES; THICKNESS; VOLUME; ACCURACY; EQUATIONS; PREDICTION; REGRESSION; CLIMATE;
D O I
10.2478/forj-2022-0019
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Scots pine (Pinus sylvestris L.) is the most widely distributed pine species in the world. In Germany, as in many other European countries, it is a very important species both culturally and economically. Few studies have focused on bark volumes being delivered to the wood industry together with the roundwood, being potentially a valuable resource for material or energetic utilization. Therefore, logs from six different forest sites were collected and bark variables including double bark thickness (DBT) in three different categories, diameter, and bark damage (as a degree of miss-DBT) in three different categories, diameter, and bark damage (as a degree of missing bark) were measured and analyzed in order to model bark volume (V-bark) and bark mass (M-bark). The correlation analysis using Pearson's method showed that the highest correlation coefficients were observed from the correlation between DBT and V-bark, as well as between DBT and M-bark. Also, results demonstrated that with DBT greater than 20 mm, the percentage of V-bark exceeded 20%. Finally, different linear regression models were recommended to predict V-bark and Mbark based on the other variables. The results of this study can be used in different wood industries in order to predict bark volume and bark mass of e.g. truckloads or roundwood stacks.
引用
收藏
页码:89 / 97
页数:9
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