Marenče Jurij, Ph. D.

Mathematical models for optimization of group work in harvesting operation

volume: 26, issue: 1

Effect of Transmission Type on Wheel Slip under Overload – Presented on the Example of the AGT 835 T Tractors

volume: 35, issue: 2

Possibilities of Using Small Tractors for Forestry Operations on Private Property

volume: 37, issue: 1

Monitoring the Quality and Quantity of Beechwood from Tree to Sawmill Product

volume: 41, issue: 1

The analysis evaluates the potential and methods of the respective assessment of beech trees, beech logs and sawn timber. The objective of the study was to assess the impact of the quality of the incoming raw material (tree) on the quality and quantity of products – obtained at the sawmill. The study presents a model that indicates the relations between the assessment of the quality of a standing beech tree and the quality of the sawmill products obtained from its wood. In addition, relations between individual quality classes of sawlogs, pulpwood, energy wood and sawn timber are shown. Standing trees were assessed in three sites according to the national 5-grade quality scale, assortments produced from selected trees pursuant to the EN 1316-1 standard, and sawn timber produced from assortments according to the rules of the European Organisation of the Sawmill Industry (EOS). In total, 87.04 m3 of timber was harvested. In higher quality trees (quality 1 and 2), the shares of sawlogs were between 53% and 72% of gross tree volume, but in the poorest quality trees, the shares were only between 23% and 36%. What remained was pulp and energy wood. In trees of excellent quality (quality 1), sawlogs of the highest quality prevailed (A and B quality grade), while sawlogs of C and B quality prevailed in trees of lower quality. Covered knots and heart defects were typically the decisive criteria for classifying sawlogs quality in all three sites. A total of 30,786 m3 of unedged timber was sawn from the sawlogs, which comprised 35% of the total gross quantity of trees on average. Nine percent of the sawn timber was classified into the A–EOS class (top quality), 27% into the B–EOS class and 47% into the C–EOS class. Seventeen percent of the timber was only suitable for post-processing. The crucial criteria for classifying sawn timber were as follows: dead and rotten knots, heart, curvature and cracks. Above-average sawlogs (A and B quality grade) was mainly obtained from trees of better quality. Relations between the quality of trees, sawlogs and sawn timber indicated the suitability of classifying standing trees and sawlogs, since it was possible to produce sawn timber of higher quality from quality trees or logs. The model presents a rare attempt to establish and monitor quality and quantity from standing tree to end product.


Web of Science Impact factor (2022): 3.200
Five-years impact factor: 3.000

Quartile: Q1 - Forestry

Subject area

Agricultural and Biological Sciences