Predicting probability of A-quality lumber of Scots pine (Pinus sylvestris L.) prior to or concurrently with logging operation

Knot properties have a profound influence on the suitability of wood for many wood products leading to significant value differences between different quality grades. It would therefore be rather advantageous to maximise the volume of good quality timber attained from the logs. The objective of this...

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Bibliographic Details
Published in:Scandinavian journal of forest research 2018-07, Vol.33 (5), p.475-483
Main Authors: Uusitalo, Jori, Ylhäisi, Olli, Rummukainen, Hannu, Makkonen, Marika
Format: Article
Language:English
Subjects:
Bucking
cross-cutting
Field tests
Ground level
Growth rate
knots
Logging
Lumber
Pine trees
Pinus sylvestris
Quality
Quality assessment
Regression models
Statistical analysis
Wood
Wood products
wood quality
wood supply chain management
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Summary:Knot properties have a profound influence on the suitability of wood for many wood products leading to significant value differences between different quality grades. It would therefore be rather advantageous to maximise the volume of good quality timber attained from the logs. The objective of this study was to assess how well A-quality lumber of Scots pine derived from log tomography features can be predicted with characteristics measured prior to or concurrently with the logging operation. The study is based on field experiments and X-ray scanning of 204 stems from southern Finland in 2014. We employed mixed logistic regression techniques to model the relationship between the main stem characteristics and probability of A-quality lumber. From the tree characteristics that can be measured or detected from standing trees, the height from the ground level to the lowest dead branch was found to be the best predictor of A-quality lumber. From the characteristics that could, at least in theory, be detected and measured at the moment of harvest, early growth rate and size of tree were found to be the best combination for predicting the probability of A-class quality.
ISSN:0282-7581
1651-1891
DOI:10.1080/02827581.2018.1461922