Comparison Study in the Clear Wood Estimation of the Beech tree trunk(Fagus orientalis Libsky)

Document Type : Research Paper

Authors

1 Associate prof., Department of forestry, Faculty of natural resources, University of Guilan, Sowmeh Sara, Iran

2 Professor, Wood science and engineering, Luleå University of technology, Skellefteå, Sweden

Abstract

Fagus orientalis is a valuable deciduous tree species mainly distributed in northern of Iran.There is great demand in the market for itُs log especially for knot-free logs. The classification of roundwood is inextricably linked to the measurement of a particular single wood defect. The appearance, location, and number of defects are important in the quality evaluation of logs and sawn timber, and the most important defects are knots. To evaluate the defects of trees, destructive methods (cutting) and non-destructive methods (CT scans) are used. The purpose of this study was to calculate clear wood by four models and compared to CT- scan. Fifteen stems of oriental beech trees were studied. The Pearson correlation coefficient and the Kolmogorov-Smirnov test have been used to check the normality of the data and the correlation between the parameters. The results show that the detection of CT- scan is high at the organs have a significant difference in the density. The accuracy of detection and evalution is high in the CT-Scan method. The results show that there is a high correlation between all methods of estimating clear wood. The most correlation coefficient was obtained between the fourth model and CT-Scan method(r=0.994) which their clear wood estimation are the same. Among the studied models, the first model (∆r=Ws-Ls ) which is based on the external indicator is more suitable for evaluating of the beech clear wood in the log grading process

Keywords

Main Subjects


[1] Amini, M., Namiranian, M., Sagheb Talebi, Kh.and Amini, R., 2009. Investigation on The Homogenity of Diameter Increment Models in Fagus orientalis L. Trees. Journal of Wood and Forest Science and Technology,16(4):1-23.
[2] Stängle, S.M., Bruchert, F., Kretschmer, U.,Spicker,H. and Sauter, U.H.,2013.Clear wood content in standing trees predicted from branch scar measurements with terrestrial LiDAR and verified with X-ray computed tomography. Canadian Journal of Forest Research, 44:145-153.
[3] Torkaman, J., Vaziri, M.,Sandberg,D. and Limaei,S.M.,2018. Relationship between branch-scar parameters and knot features of oriental beech (Fagus orientalis Libsky). Wood Material Science and Engineering, 13: 117-120.
[4] Thomas, R.E., 2009.Modeling the relationships among internal defect features and external Appalachian hardwood log defect indicators. Silva Fennica, 43(3): 447–456.
[5] Racko, V., 2013. Verify the accuracy of estimation the model between dimensional characteristics of branch scar and the location of the knot in the beech trunk. Forestry and Wood Technology, 84: 60-65.
[6] Wei, Q., Leblon,B. and Rocque, A.L.,2011.On the use of X-ray computed tomography for determining wood properties: a review1. Canadian Journal of Forest Research, 41: 2120–2140.
[7] Oja,J.,Grundberg,S.,Fredriksson,J. and Berg, P.,2004. Automatic grading of sawlogs: a comparison between X-ray scanning, optical three-dimensional scanning and combinations of both methods. Scandinavian Journal of Forest Research, 19(1): 89–95.
[8] Grundberg, S. and Grönlund, A.,1991. Methods for reducing data when scanning for internal log defects. In Proceedings of the 4th International Conference on Scanning Technology in the Wood Industry, San Francisco, Calif. 28–29 October 1991. Luleå University of Technology, Luleå, Sweden.
[9]  Grundberg, S. and Grönlund, A.,1992. Log scanning - extraction of knot geometry. In Proceedings of the 1st International Seminar/Workshop on Scanning Technology and Image Processing on Wood, Skellefteå, Sweden. 30 August – 1 September. Luleå University of Technology, Luleå, Sweden
[10] Osterloh,k.,2006. Radiographic and Tomographic Testing of Wood, ECNDT 2006 - Th.1.3.3
[11] Oja, J.,2000. Evaluation of knot parameters measured automatically in CT-images of Norway spruce (Picea abies (L.) Karst.). Europian Journal of Wood and Wood Products, 58(5): 375–379.
[12] Oja, J. and Temnerud, E.,1999. The appearance of resin pockets in CT-images of Norway spruce (Picea abies (L.) Karst). Europian Journal of Wood and Wood Products 57(5): 400–406.
[13] Oja,J.,1997. A Comparison between Three Different Methods of Measuring Knot Parameters in Picea abies. Scandinavian Journal of Forest Research,12: 311-315.
[14] Wernsdorfer,H.,Constant,T.,Mothe,F.,Badia,M.A.,Nepveu,G. and Seeling,U.,2005. Detailed analysis of the geometric relationship between external traits and the shape of red  heartwood in beech trees (Fagus sylvatica L.). Trees, 19: 482–491.
[15] Wei,Q.,Leblon,B.,Chui,Y.H. and Zhang,S.Y.,2008a.Identification of selected log characteristics from computed tomography images of sugar maple logs using maximum likelihood classifier and textural analysis. Holzforschung, 62(4):441–447.
[16] Wang,C.,Zhao,Z., Hein,S., Zeng,J.,Schuler,J.,Guo,J., Guo,W.  and Zeng,J.,2015. Effect of Planting Density on Knot Attributes and Branch Occlusion of Betula alnoides under Natural Pruning in Southern China.Forests, 6:1343-1361.
[17] Kazemi-Najafi,S.,Shalbafan,A.and Ebrahimi,GH.,2009.Internal decay assessment in standing beech trees using ultrasonic velocity measurement.Europian Journal of Forest Research,128:345-350.
[18] Li,W.,Wen,J.,Xiao,Z.and Xu,S.,2018.Application of Ground-Penetrating Radar for Detecting Internal Anomalies in Tree Trunk with Irregular Contours.Sensors,18,649(open access).
[19] Schulz, H.,1961. Die Beurteilung der Qualit¨atsentwicklung junger B¨aume. Forstarchiv, 32:89–99
[20] Wernsd¨orfer, H.,Constant,T., Mothe, F., Badia, M.A.,Nepveu,G. and Seeling,U.,2005. Detailed analysis of the geometric relationship between external traits and the shape of red heartwood in beech trees(Fagus sylvatica L.). Trees , 19: 482–491.