Silva Fennica : quarterly issues : 38(3) : sa383291.htm

Jori Uusitalo, Sampsa Kokko & Veli-Pekka Kivinen. 2004.

The effect of two bucking methods on Scots pine lumber quality

Silva Fennica 38(3): 291–303

Modern harvesters are equipped with measurement and bucking optimization systems able not only to continuously measure the length and diameter of the stem but also to predict the profile of the unknown part of a stem and to calculate the optimal cross-cutting points for the whole stem. So far, tree-bucking optimization in the Nordic countries has been efficiently applied only with spruce because the quality of pine and birch varies much more both within a stem and between stems. Since limitations in the measuring equipment mean that the presence and position of grade limits as well as additional defects in the stem will normally have to be detected and estimated manually. Consequently, optimization works inefficiently because the harvester operator is continuously forced to disregard the cutting suggestions supplied by the harvester’s automatic system. This paper presents the outcome of research intended to define how change from the current quality bucking principle to automatic bucking affects lumber quality. The study is based on field experiments and test sawing data on 100 Scots pine (Pinus sylvestris) stems from southwestern Finland in 2001. Automatic bucking does not markedly lower the amount of good-quality lumber compared to quality bucking. Since automatic bucking inevitably leads to log distribution that matches the length requirements of customers better, it may be regarded as appropriate for these harvesting conditions.

Keywords
harvesting, mechanized logging, tree bucking

Addresses
Uusitalo and Kokko, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland; Kivinen, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland. E-mail jori.uusitalo@joensuu.fi

Received 11 September 2003 Accepted 8 June 2004
ISSN 0037-5330

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