<abstract xmlns="http://www.w3.org/1999/xhtml">

Scots pine (<italic>Pinus sylvestris</italic> 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 (Vbark) and bark mass (Mbark). The correlation analysis using Pearson’s method showed that the highest correlation coefficients were observed from the correlation between DBT and Vbark, as well as between DBT and Mbark. Also, results demonstrated that with DBT greater than 20 mm, the percentage of Vbark exceeded 20%. Finally, different linear regression models were recommended to predict Vbark 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.
</abstract>

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 (Vbark) and bark mass (Mbark). The correlation analysis using Pearson’s method showed that the highest correlation coefficients were observed from the correlation between DBT and Vbark, as well as between DBT and Mbark. Also, results demonstrated that with DBT greater than 20 mm, the percentage of Vbark exceeded 20%. Finally, different linear regression models were recommended to predict Vbark 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.

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

Eberswalde University for Sustainable Development

Department of Forest Utilization and Timber Market

Department of Forest Harvesting, Logistics and Amelioration

Central European Forestry Journal

This work is licensed under the Creative Commons Attribution 4.0 International License.

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...

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

Online veröffentlicht: 18. Mai 2023

Seitenbereich: 89 - 97

DOI: https://doi.org/10.2478/forj-2022-0019

Schlüsselwörter
bark thickness, bark volume, bark mass, correlation

© 2023 Ferréol Berendt et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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

Online veröffentlicht: 18. Mai 2023

Seitenbereich: 89 - 97

DOI: https://doi.org/10.2478/forj-2022-0019

Schlüsselwörterbark thickness, bark volume, bark mass, correlation

© 2023 Ferréol Berendt et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
bark thickness, bark volume, bark mass, correlation