Abstract
The effect of thermal modification (TM) on the color of western hemlock wood and its physical and mechanical properties were investigated. The focus of this study was the prediction of material properties of thermally modified wood based on the color change via the “group method of data handling (GMDH)” neural network (NN). The NN was trained by color parameters for predicting the equilibrium moisture content (EMC), density, porosity, water absorption (WA), swelling coefficient, dynamic modulus of elasticity (MOEdyn) and hardness. The color parameters showed a significant correlation with temperature and are well correlated with the heat treatment (HT) intensity. Color parameters combined with the GMDH-type NN successfully predicted the physical properties of the material. The best correlation was achieved with the swelling coefficient, EMC and WA. All these properties were significantly influenced by HT. The color parameters did not seem suitable for predicting the wood hardness and MOEdyn. The GMDH NN shows a higher model accuracy than the multivariate linear and partial least squares (PLS) regression models.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: None declared.
Employment or leadership: None declared.
Honorarium: None declared.
References
Albrektas, D., Navickas, P. (2017) An evaluation of modulus of elasticity, dimensional stability and bonding strength of bonded heat-treated wood. Drvna. Ind. 68:137–144.10.5552/drind.2017.1641Search in Google Scholar
ASTM D1037-12. Standard Test Methods for Evaluating Properties of Wood-Base Fiber and Particle Panel Materials. ASTM International, West Conshohocken, PA, 2012.Search in Google Scholar
ASTM D143-14. Standard test method for small clear specimens of timber. In ASTM, West Conshohocken, PA, Vol. 143, pp. 143–94, 1994.Search in Google Scholar
ASTM D2244-16. Standard Practice for Calculation of Color Tolerances and Color Differences from Instrumentally Measured Color Coordinates. ASTM International, West Conshohocken, PA, 2016.Search in Google Scholar
ASTM D2395-17. Standard Test Methods for Density and Specific Gravity (Relative Density) of Wood and Wood-Based Material. ASTM International, West Conshohocken, PA, 2017.Search in Google Scholar
ASTM D4442-16. Standard Test Methods for Direct Moisture Content Measurement of Wood and Wood-Based Materials. ASTM International, West Conshohocken, PA, 2016.Search in Google Scholar
Avramidis, S., Iliadis, L. (2005) Wood-water sorption isotherm prediction with artificial neural networks: a preliminary study. Holzforschung 59:336–341.10.1515/HF.2005.055Search in Google Scholar
Bekhta, P., Niemz, P. (2003) Effect of high temperature on the change in color, dimensional stability and mechanical properties of spruce wood. Holzforschung 57:539–546.10.1515/HF.2003.080Search in Google Scholar
Boonstra, M. A two-stage thermal modification of wood. Doctoral Dissertation, Ghent University, Ghent, Belgium and Université Henry Poincaré, Nancy, France, 2008.Search in Google Scholar
Bourgois, J., Janin, G., Guyonnet, R. (1991) Measuring colour: a method of studying and optimising the chemical transformations of thermally-treated wood. Holzforschung 45:377–382.10.1515/hfsg.1991.45.5.377Search in Google Scholar
Brischke, C., Welzbacher, C.R., Brandt, K., Rapp, A.O. (2007) Quality control of thermally modified timber: Interrelationship between heat treatment intensities and CIE L* a* b* color data on homogenized wood samples. Holzforschung 61:19–22.10.1515/HF.2007.004Search in Google Scholar
Candelier, K., Thevenon, M.F., Petrissans, A., Dumarcay, S., Gerardin, P., Petrissans, M. (2016) Control of wood thermal treatment and its effects on decay resistance: a review. Ann. For. Sci. 73:571–583.10.1007/s13595-016-0541-xSearch in Google Scholar
Dunn, D. A preliminary assessment of the Metriguard 239A stress wave timer. Dissertation, University of Canterbury, New Zealand, 1992.Search in Google Scholar
Esteban, L.G., Fernández, F.G., de Palacios, P. (2011) Prediction of plywood bonding quality using an artificial neural network. Holzforschung 65:209–214.10.1515/hf.2011.003Search in Google Scholar
Esteves, B., Pereira, H. (2009) Wood modification by heat treatment: a review. BioResources 4:370–404.10.15376/biores.4.1.EstevesSearch in Google Scholar
Esteves, B., Marques, A.V., Domingos, I., Pereira, H. (2008) Heat-induced colour changes of pine (Pinus pinaster) and eucalypt (Eucalyptus globulus) wood. Wood Sci. Technol. 42:369–384.10.1007/s00226-007-0157-2Search in Google Scholar
Gonzalez de Cademartori, P.H., Schneid, E., Gatto, D.A., Martins Stangerlin, D., Beltrame, R. (2013) Thermal modification of Eucalyptus grandis wood: variation of colorimetric parameters. Maderas-Cienc. Tecnol. 15:57–64.10.4067/S0718-221X2013005000005Search in Google Scholar
González-Peña, M.M., Hale, M.D. (2009a) Colour in thermally modified wood of beech, Norway spruce and Scots pine. Part 1: colour evolution and colour changes. Holzforschung 63:385–393.10.1515/HF.2009.078Search in Google Scholar
González-Peña, M.M., Hale, M.D. (2009b) Colour in thermally modified wood of beech, Norway spruce and Scots pine. Part 2: property predictions from colour changes. Holzforschung 63:394–401.10.1515/HF.2009.077Search in Google Scholar
Guller, B. (2012) Effects of heat treatment on density, dimensional stability and color of Pinus nigra wood. Afr. J. Biotechnol. 11:2204–2209.Search in Google Scholar
Gunduz, G., Aydemir, D., Karakas, G. (2009) The effects of thermal treatment on the mechanical properties of wild pear (Pyrus elaeagnifolia Pall.) wood and changes in physical properties. Mater. Design 30:4391–4395.10.1016/j.matdes.2009.04.005Search in Google Scholar
Hill, C.A. (2007) Wood modification: chemical, thermal and other processes (Vol. 5). Wiley Series in Renewable Resources. John Wiley and Sons, Ltd., Chichester, UK, ISBN: 0-470-02172-1. pp. 99–127.10.1002/0470021748Search in Google Scholar
Hiltunen, E., Pakkanen, T.T., Alvila, L. (2006) Phenolic compounds in silver birch (Betula pendula Roth) wood. Holzforschung 60:519–527.10.1515/HF.2006.086Search in Google Scholar
Iliadis, L., Mansfield, S.D., Avramidis, S., El-Kassaby, Y.A. (2013) Predicting Douglas-fir wood density by artificial neural networks (ANN) based on progeny testing information. Holzforschung 67:771–777.10.1515/hf-2012-0132Search in Google Scholar
Johansson, D. Heat treatment of solid wood: effects on absorption, strength and colour. Doctoral dissertation, Luleå tekniska universitet, Lulea, Sweden, 2008.Search in Google Scholar
Johansson, D., Morén, T. (2006) The potential of colour measurement for strength prediction of thermally treated wood. Holz Roh Werkst 64:104–110.10.1007/s00107-005-0082-8Search in Google Scholar
Kačíková, D., Kačík, F., Čabalová, I., Ďurkovič, J. (2013) Effects of thermal treatment on chemical, mechanical and colour traits in Norway spruce wood. Bioresource Technol. 144:669–674.10.1016/j.biortech.2013.06.110Search in Google Scholar PubMed
Mansfield, S.D., Iliadis, L., Avramidis, S. (2007) Neural network prediction of bending strength and stiffness in western hemlock (Tsuga heterophylla Raf.). Holzforschung 61:707–716.10.1515/HF.2007.115Search in Google Scholar
Mansfield, S.D., Kang, K.Y., Iliadis, L., Tachos, S., Avramidis, S. (2011) Predicting the strength of Populus spp. clones using artificial neural networks and ε-regression support vector machines (ε-rSVM). Holzforschung 65:855–863.10.1515/HF.2011.107Search in Google Scholar
Militz, H., Altgen, M. (2014) Processes and properties of thermally modified wood manufactured in Europe. ACS Symp. Ser. 1158:269–285.10.1021/bk-2014-1158.ch016Search in Google Scholar
Mitani, A., Barboutis, I. (2014) Changes caused by heat treatment in colour and dimensional stability of beech (Fagus sylvatica L.) wood. Drvna. Ind. 65:225–232.10.5552/drind.2014.1250Search in Google Scholar
Nasir, V., Cool, J. (2018) A review on wood machining: characterization, optimization, and monitoring of the sawing process. Wood Mat. Sci. Eng. https://doi.org/10.1080/17480272.2018.1465465.10.1080/17480272.2018.1465465Search in Google Scholar
Nasir, V., Nourian, S., Avramidis, S., Cool, J. (2018) Stress wave evaluation by accelerometer and acoustic emission sensor for thermally modified wood classification using three types of neural networks. Eur J Wood Wood Prod. https://doi.org/10.1007/s00107-018-1373-1.10.1007/s00107-018-1373-1Search in Google Scholar
Nishino, Y., Janin, G., Yainada, Y., Kitano, D. (2000) Relations between the colorimetric values and densities of sapwood. J. Wood Sci. 46:267–272.10.1007/BF00766215Search in Google Scholar
Obataya, E., Tomita, B. (2002) Hygroscopicity of heat-treated wood, 2: Reversible and irreversible reductions in the hygroscopicity of wood due to heating. Mokuzai Gakkaishi 48:288–295.Search in Google Scholar
Pleschberger, H., Teischinger, A., Müller, U., Hansmann, C. (2014) Change in fracturing and colouring of solid spruce and ash wood after thermal modification. Wood Mat. Sci. Eng. 9:92–101.10.1080/17480272.2014.895418Search in Google Scholar
Poncsak, S., Kocaefe, D., Younsi, R. (2011) Improvement of the heat treatment of Jack pine (Pinus banksiana) using ThermoWood technology. Eur. J. Wood Prod. 69:281–286.10.1007/s00107-010-0426-xSearch in Google Scholar
Repellin, V., Guyonnet, R. Evaluation of heat treated beech by non destructive testing. In Proceedings of the First European Conference on Wood Modification, Ghent University, Ghent, Belgium, 2003.Search in Google Scholar
Rowell, R.M. (2012) Handbook of Wood Chemistry and Wood Composites. 2nd ed. CRC Press, Boca Raton, FL. pp. 511–531.10.1201/b12487Search in Google Scholar
Sandberg, D., Kutnar, A., Mantanis, G. (2017) Wood modification technologies – a review. iForest 10:895.10.3832/ifor2380-010Search in Google Scholar
Schnabel, T., Zimmer, B., Petutschnigg, A.J., Schönberger, S. (2007) An approach to classify thermally modified hardwoods by color. Forest Prod. J. 57:105.Search in Google Scholar
Sundqvist, B., Morén, T. (2002) The influence of wood polymers and extractives on wood colour induced by hydrothermal treatment. Eur J. Wood Wood Prod. 60:375–376.10.1007/s00107-002-0320-2Search in Google Scholar
Tjeerdsma, B.F. (1998). Thermal modification of non-durable wood species. Part 2. Improved wood properties of thermally treated wood, International Research Group on Wood Protection, Stockholm, Sweden, Document no. IRG/WP 98-40124.Search in Google Scholar
Todorovic, N.V., Popović, Z., Milić, G., Popadić, R. (2012) Estimation of heat-treated beechwood properties by color change. BioResources 7:0799–0815.10.15376/biores.7.1.799-815Search in Google Scholar
Unsal, O., Buyuksari, U., Ayrilmis, N., Korkut, S. (2009) Properties of wood and wood based materials subjected to thermal treatments under various conditions. International wood science and engineering conference in the third millennium (ICWSE), Brasov, Romania.Search in Google Scholar
Willems, W., Lykidis, C., Altgen, M., Clauder, L. (2015) Quality control methods for thermally modified wood. Holzforschung 69:875–884.10.1515/hf-2014-0185Search in Google Scholar
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