Analyzing the Antecedents and Consequences of Manual Log Bucking in Mechanized Wood Harvesting

Authors: Kalle Kärhä, Jyri Änäkkälä, Ollipekka Hakonen, Teijo Palander, Juha-Antti Sorsa, Tapio Räsänen, Tuomo Moilanen

ABSTRACT. The study focused on the frequency of applying a manual tree-stem bucking to logs in coniferous forests of Finland. The aim of the study was to clarify harvesting conditions where manual log bucking is utilized most and the effects of the utilization of manual bucking on the log bucking outcome. In addition to the stm Big Data of harvesters, in order to investigate the consequences of manual log bucking, data from the enterprise resource production (ERP) systems of wood procurement organization and sawmills was collected, as well as harvester operators were interviewed. The study results illustrated that the share of manual bucking of Norway spruce (Picea abies L. Karst.) logs was, on average, 46% and with Scots pine (Pinus sylvestris L.) logs 67%. The operators used manual bucking more frequently in thinning stands with small-sized and defected log stems. When the utilization degree of manual log bucking was high, the utilization of log sections with spruce and pine log stems was lower, logs were shorter and the volume of logs was smaller. Furthermore, log percentage and apportionment degree were significantly lower when the shares of manual log bucking were higher. The relative production value of spruce logs was lower, and correspondingly the relative production value of pine logs was higher when applying plenty of manual bucking. On the basis of the study results, it can be recommended that nowadays the target for the manual log bucking percentage with spruce must be less than 20–30% of the total log volume cut. In the future, our aim must be fully automatic or semi-automatic and harvester computer-aided bucking based on the quality grades of the log section zones of log stems with pine and spruce. It will require equipping harvesters with novel mobile laser scanning (MLS) and machine vision (MV) applications.

Keywords: forest engineering, cross-cutting, cut-to-length (CTL) method, softwood, value recovery, Big Data, sawmilling industry, Finland

DOI 10.2412/mmse.45.20.957


[1] Marshall, H. D. (2005). An Investigation of Factors Affecting the Optimal Log Output Distribution from Mechanical Harvesting and Processing Systems (Doctoral dissertation). Oregon State University. Retrieved from

[2] Strandström, M. (2017). Timber Harvesting and Long-distance Transportation of Roundwood 2016. Metsätehon Tuloskalvosarja 1b/2017. Retrieved from

[3] Mäki-Simola, E. (2017). The average forest machinery in commercial roundwood production in Finland, 2010–2016. Natural Resources Institute Finland, Unpublished statistics.

[4] Marshall, H. (2007). Log merchandizing model used in mechanical harvesting. In A. Weintraub, C. Romero, T. Bjørndal, & R. Epstein (Eds.), Handbook of Operations Research in Natural Resources (pp. 379-389). New York, NY: Springer Science+Business Media. ISBN 978-0-387-71814-9

[5] Geerts, J. M. P., & Twaddle, A. A. (1984). A method to assess log value loss caused by cross-cutting practice on the skidsite. New Zealand Journal of Forestry, 29 (2), 173-184. Retrieved from

[6] Pickens, J. B., Lee, A., & Lyon, G. W. (1992). Optimal Bucking of Northern Hardwoods. Northern Journal of Applied Forestry, 9(4), 149-152.

[7] Bowers, S. (1998). Increased Value through Optimal Bucking. Western Journal of Applied Forestry, 13(3), 85-89.

[8] Wang, J., LeDoux, C. B., & McNeel, J. (2004). Optimal tree-stem bucking of northeastern species of China. Forest Products Journal, 52(2), 45-52. Retrieved from

[9] Malinen, J., & Palander, T. (2004). Metrics for Distribution Similarity Applied to the Bucking to Demand Procedure. International Journal of Forest Engineering, 15(1), 33-40. Retrieved from

[10] Nummi, T., Sinha, B. K., & Koskela, L. (2005). Statistical properties of the apportionment degree and alternative measures in bucking outcome. Revista Investigación Operacional, 26(3), 259-267. Retrieved from

[11] Holappa Jonsson, S., & Hägglund, J. (2016). The Effect of Harvester Drivers on Assortment Yield and Length Distribution of Pine Logs in Final Fellings. Sveriges Lantbruksuniversitet, Institutionen för skogens ekologi och skötsel, Kandidatarbete i skogsvetenskap 2016:04.

[12] Uusitalo, J., Kokko, S., & Kivinen, V.-P. (2004). The Effect of Two Bucking Methods on Scots Pine Lumber Quality. Silva Fennica, 38(3), 291-303. DOI 10.14214/sf.417

[13] Kivinen, V.-P. (2007). Design and testing of stand-specific bucking instructions for use on modern cut-to length harvester (Doctoral dissertation). University of Helsinki, Dissertationes Forestales 37. ISBN 978-951-651-163-7

[14] Twaddle, A. A., & Goulding, C. J. (1989). Improving profitability by optimising log-making. New Zealand Journal of Forestry, 34(1), 17-23. Retrieved from

[15] Wang, J., Liu, J., & LeDoux, C. B. (2009). A Three-Dimensional Bucking System for Optimal Bucking of Central Appalachian Hardwoods. International Journal of Forest Engineering, 20(2), 26-35. Retrieved from

[16] Akay, A. E., Sessions, J., Serin, H., Pak, M., & Yenilmez, N. (2010). Applying Optimum Bucking Method in Producing Taurus Fir (Abies cilicica) Logs in Mediterranean Region of Turkey. Baltic Forestry, 16(2), 273-279. Retrieved from[2]/Abdulach_etal_2010%2016(2)_273_279.pdf

[17] Serin, H., Akay, A. E., & Pak, M. (2010). Estimating the effects of optimum bucking on the economic value of Brutian pine (Pinus brutia) logs extracted in Mediterranean region of Turkey. African Journal of Agricultural Research, 5(9), 916-921. Retrieved from

[18] Akay, A. E., Serin, H., & Pak, M. (2015). How stem defects affect the capability of optimum bucking method? Journal of the Faculty of Forestry Istanbul University, 65(2), 38-45. DOI 10.17099/jffiu.54455

[19] Ylitalo, E. (2017). Forest industries’ wood consumption in Finland, 1860–2016. Natural Resources Institute Finland, Statistics Database. Retrieved from

[20] Skogforsk. (2007). StanForD. Standard for Forest Data and communications. Retrieved from

[21] Änäkkälä, J. (2017). The frequency of manual bucking on Norway spruce logs in eastern Finland at Stora Enso Wood Supply Finland (Master’s thesis). University of Eastern Finland.

[22] Labelle, E. R., Bergen, M., & Windisch, J. (2017). The effect of quality bucking and automatic bucking on harvesting productivity and product recovery in a pine-dominated stand. European Journal of Forest Research, 136(4), 639-652.

[23] Gellerstedt, S. (2002). Operation of the Single-Grip Harvester: Motor-Sensory and Cognitive Work. International Journal of Forest Engineering, 13(2), 35-47. Retrieved from

[24] Nicholls, A., Bren, L., & Humphreys, N. (2004). Harvester Productivity and Operator Fatigue: Working Extended Hours. International Journal of Forest Engineering, 15(2), 57-65. Retrieved from

[25] Marshall, H., & Murphy, G. (2004). Economic evaluation of implementing improved stem scanning systems on mechanical harvesters/processors. New Zealand Journal of Forestry Science, 34(2), 158-174. Retrieved from

[26] Murphy, G., Wilson, I., & Barr, B. (2006). Developing methods for pre-harvest inventories which use a harvester as the sampling tool. Australian Forestry, 69(1), 9-15. DOI 10.1080/00049158.2006.10674982

[27] Murphy, G. (2008). Determining Stand Value and Log Product Yields Using Terrestrial Lidar and Optimal Bucking: A Case Study. Journal of Forestry, 106(6), 317-324.

[28] Häggström, C. (2015). Human Factors in Mechanized Cut-to-Length Forest Operations (Doctoral dissertation). Swedish University of Agricultural Sciences, Acta Universitatis agriculturae Sueciae 2015:59. urn:nbn:se:slu:epsilon-e-2644

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