Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.