Abstract
Context
One of the most important wood defects affecting the value yield from European beech (Fagus sylvatica [L.]) logs is knots that are visible on the sawn wood surface. The non-invasive technology of X-ray computed tomography (CT) can be used for the assessment of log internal features, especially the geometry and position of knots before primary breakdown to support the decision of value-optimised log rotation in sawmills.
Aims
The objective of this study was to test whether value-optimised log rotation can be performed successfully by using the CT-derived knowledge of internal knottiness for the hardwood species beech.
Methods
Size parameters of 670 knots were measured and their position was marked in CT images from 33 logs. The 3D-reconstructed logs were virtually sawn in 12 different rotational angles using the software InnoSIM. This allowed visual grading of the simulated sawn wood and the calculation of product volume and value.
Results
The results show that if optimal rotation was applied to each single log, both total volume as well as total product value yield could be improved by up to 24 % compared with the average yield of all simulated rotational angles.
Conclusion
In this small-scale study, it is demonstrated that CT technology could be used to support the decision about optimal rotational angle of beech logs to maximise volume and value yield.
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Acknowledgements
The project was supported by the European Commission under the Food, Agriculture and Fisheries, and Biotechnology Theme of the 7th Framework Programme for Research and Technological Development, FP7 Grant Agreement No. 245136. We would like to thank all project partners involved in the FlexWood project. Furthermore, we thank Aikaterini Nakou for statistical advice. The suggestions from two anonymous reviewers and the associate editor were very much appreciated and helped improve the manuscript.
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Handling Editor: Barry Alan Gardiner
Contribution of the co-authors
Stängle: supervising the CT image analysis, running the data analysis and writing the paper;
Brüchert: developing the study design, supervising the work, coordinating the research project and revising the manuscript;
Heikkila: performing the sawing simulations and analysing data;
Usenius, T.: performing the sawing simulations;
Usenius, A.: supervising the sawing simulation, revising the manuscript;
Sauter: coordinating the research project, supervising the work, revising the manuscript;
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Stängle, S.M., Brüchert, F., Heikkila, A. et al. Potentially increased sawmill yield from hardwoods using X-ray computed tomography for knot detection. Annals of Forest Science 72, 57–65 (2015). https://doi.org/10.1007/s13595-014-0385-1
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DOI: https://doi.org/10.1007/s13595-014-0385-1