Estimation of moisture in wood chips by near infrared spectroscopy
Keywords:
Cellulose, integrating sphere, optical fiber, paper, physical propertiesAbstract
In order to assess the moisture content of wood chips on an industrial scale, readily applicable techniques are required. Thus, near infrared (NIR) spectroscopy was used to estimate moisture in wood chips by means of partial least squares regressions. NIR spectra were obtained in spectrometer with an integrating sphere and optical fiber probe, on the longitudinal and transverse surface of Eucalyptus wood chips. The specimens had their masses and NIR spectra measured in 10 steps during drying from saturated to anhydrous condition. Principal Component Analysis was performed to explore the effect of moisture of wood chip on NIR signatures. The values of moisture content of chips were associated with the respective NIR spectra by Partial Least Squares Regression (PLS-R) and Partial Least Squares Discriminant Analysis (PLS-DA) to estimate the moisture content of wood chips and its moisture classes, respectively. Model developed from spectra recorded on the longitudinal face by the integrating sphere method presented statistics slightly better (R²cv = 0,96; RMSEcv = 7,15 %) than model based on optical fiber probe (R²cv = 0,90; RMSEcv = 11,86 %). This study suggests that for calibration of robust predictive model for estimating moisture content in chips the spectra should be recorded on the longitudinal surface of wood using the integrating sphere acquisition method.
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References
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Thygesen, L.G.; Lundqvist, S.O. 2000. NIR Measurement of Moisture Content in Wood under Unstable Temperature Conditions. Part 1. Thermal Effects in near Infrared Spectra of Wood. J Near Infrared Spec 8(3):183-189. https://doi.org/10.1255/jnirs.277
Tsuchikawa, S.; Kobori, H. 2015. A review of recent application of near infrared spectroscopy to wood science and technology. J Wood Sci 61(3): 213–220. https://doi.org/10.1007/s10086-015-1467-x
Tsuchikawa, S.; Schwanninger, M. 2013. A review of recent near-infrared research for wood and paper (Part 2). Appl Spectrosc Rev 48(7): 560-587. https://doi.org/10.1080/05704928.2011.621079
Tyson, J.A.; Schimleck, L.R.; Aguiar, A.M.; Abad, J.I.M.; Rezende, G.D.S.P; Filho, O.M. 2012. Development of near infrared calibrations for physical and mechanical properties of eucalypt pulps of mill-line origin. J Near Infrared Spec 20(2): 287-294. https://doi.org/10.1255/jnirs.988
Watanabe, K.; Mansfield, S. D.; Avramidis, S. 2011. Application of near-infrared spectroscopy for moisture-based sorting of green, hem-fir timber. J Wood Sci 57(4): 288-294. https://doi.org/10.1007/s10086-011-1181-2
Yang, L.; Liu, H.; Cai, Y.; Hayashi, K.; Wu, Z. 2014. Effect of drying conditions on the collapse-prone wood of Eucalyptus urophylla. BioResources 9(4): 7288-7298. https://doi.org/10.15376/biores.9.4.7288-7298
Zhang, M.; Liu, Y.; Yang, Z. 2015. Correlation of near infrared spectroscopy measurements with the surface roughness of wood. BioResouces 10(4): 6953-6960. https://doi.org/10.15376/biores.10.4.6953-6960
Associação Brasileira de Normas Técnicas. ABNT. 2017. NBR 14929: Madeira: determinação do teor de umidade de cavacos - Método por secagem em estufa. ABNT, Rio de Janeiro, Brasil. 3 p. https://www.abntcatalogo.com.br/norma.aspx?ID=369854
Arriel, T.G.; Ramalho, F.M.G.; Lima, R.A.B.; Souza, K.I.R.; Hein, P.R.G. Trugilho, P.F. 2019. Developing near infrared spectroscopic models for predicting density of Eucalyptus wood based on indirect measurement. Cerne 25(3): 294-300. https://doi.org/10.1590/01047760201925032646
Biermann, C. J. 1996. Handbook of Pulping and Papermaking. 2nd Ed. Academic Press. San Diego, USA. 754p. https://doi.org/10.1016/B978-0-12-097362-0.X5000-6
Costa, E.V.S.; Rocha, M.F.V.; Hein, R.G.; Amaral, E.A.; Santos, L.M.; Brandão, L.E.V.S.; Trugilho, P.F. 2018. Influence of spectral acquisition technique and wood anisotropy on the statistics of predictive near infrared–based models for wood density. J Near Infrared Spec 26(2): 106-116. https://doi.org/10.1177/0967033518757070
Dahlbacka, J. Lillhonga, T. 2010. Moisture measurement in timber utilising a multi-layer partial least squares calibration approach. J Near Infrared Spec 18(6): 425-432. https://doi.org/10.1255/jnirs.906
Defo, M.; Taylor, A.M.; Bond, B. 2007. Determination of moisture content and density of fresh-sawn red oak lumber by near infrared spectroscopy. Forest Prod J 57(5): 68-72.
Eom, C.D.; Park, J.H.; Choi, I.G.; Choi, J.W.; Han, Y.; Yeo, H. 2013. Determining surface emission coefficient of wood using theoretical methods and near-infrared spectroscopy. Wood Fiber Sci 45(1): 76–83. https://wfs.swst.org/index.php/wfs/article/view/522
Fardim, P.; Ferrreira, M.M.C.; Duran, N. 2005. Determination of mechanical and optical properties of Eucalyptus kraft pulp by NIR spectrometry and multivariate calibration. J Wood Chem Technol 25(4): 267–279. https://doi.org/10.1080/02773810500366748
Fujimoto, T.; Kobori, H.; Tsuchikawa, S. 2012. Prediction of wood density independently of moisture conditions using near infrared spectroscopy. J Near Infrared Spec 20(3): 353-359. https://doi.org/10.1255/jnirs.994
Gomide, J.L.; Fantuzzi Neto, H. 2000. Aspectos fundamentais da polpação Kraft de madeira de Eucalyptus. O Papel 3(61): 62-68.
Karttunen, K.; Leinonen, A.; Saren, M. 2008. A survey of moisture distribution in two sets of Scots pine logs by NIR-spectroscopy. Holzforschung 62(4): 435-440. https://doi.org/10.1515/HF.2008.060
Martens, H.; Naes, T. 1991. Multivariate calibration. 1st Ed. John Wiley & Sons. New York, USA. 419p.
Muñiz, G.I.; Magalhães, W.L.E.; Carneiro, M.E.; Viana, L.C. 2012. Fundamentos e estado da arte da Espectroscopia no Infravermelho Próximo no setor de base florestal. Cienc Florest 22(4): 865-875. http://dx.doi.org/10.5902/198050987567
Nunes, C.A.; Freitas, M.P; Pinheiro, A.C.M.; Bastos, S.C. 2012. Chemoface: a novel free user-friendly interface for chemometrics. J Brazil Chem Soc 23(11): 2003-2010. https://doi.org/10.1590/S0103-50532012005000073
Pasquini, C. 2003. Near infrared spectroscopy: fundamentals, practical aspects and analytical applications. J Brazil Chem Soc 14(2): 198-219. https://doi.org/10.1590/S0103-50532003000200006
Pasquini, C. 2018. Near Infrared Spectroscopy: a mature analytical technique with new perspectives – A review. Anal Chim Acta 1026: 8-36. https://doi.org/10.1016/j.aca.2018.04.004
Pavia, D.L.; Lampman, G.M.; Kriz, G.S.; Vyvyan, J.R. 2010. Introdução a espectroscopia. 4th Ed. Cengage Learning. São Paulo, Brazil. 716p. https://www.cengage.com.br/learning-solutions/introducao-a-espectroscopia-traducao-da-4a-edicao-norte-americana/
Price, N.C.; Dwek, R.A.; Wormald, M.; Ratcliffe, R.G. 2001. Principles and problems in physical chemistry for biochemists. 3rd Ed. Oxford University Press. Oxford, UK. 401p.
Rosado, L.R.; Takarada, L.M.; Araújo, A.C.C.; Souza, K.R.D.; Hein, P.R.G.; Rosado, S.C.S.; Gonçalves, F.M.A. 2019. Near infrared spectroscopy: rapid and accurate analytical tool for prediction of non-structural carbohydrates in wood. Cerne 25(1): 84-92. https://doi.org/10.1590/01047760201925012614
Santos, L.M. 2017. Monitoramento da dessorção de água na madeira por espectroscopia no infravermelho próximo. Master thesis. Universidade Federal de Lavras, Lavras. 56 p.
Schimleck, L.R.; Doran, J.C.; Rimbawanto, A. 2003. Near infrared spectroscopy for cost effective screening of foliar oil characteristics in a Melaleuca cajuputi breeding population. J Agric Food Chem 51(9): 2433-2437. https://doi.org/10.1021/jf020981u
Sobering, D.C.; Williams, C. 1993. Comparison of commercial near infrared transmittance and reflectance instruments for analysis of whole grains and seeds. J Near Infrared Spec 1(1): 25-33. https://www.osapublishing.org/jnirs/abstract.cfm?URI=jnirs-1-1-25
Tham, V.T.H.; Inagaki, T.E.; Tsuchikawa, S. 2018. A novel combined application of capacitive method and near-infrared spectroscopy for predicting the density and moisture content of solid wood. Wood Sci Technol 52(1): 115-129. https://doi.org/10.1007/s00226-017-0974-x
Thygesen, L.G.; Lundqvist, S.O. 2000. NIR Measurement of Moisture Content in Wood under Unstable Temperature Conditions. Part 1. Thermal Effects in near Infrared Spectra of Wood. J Near Infrared Spec 8(3):183-189. https://doi.org/10.1255/jnirs.277
Tsuchikawa, S.; Kobori, H. 2015. A review of recent application of near infrared spectroscopy to wood science and technology. J Wood Sci 61(3): 213–220. https://doi.org/10.1007/s10086-015-1467-x
Tsuchikawa, S.; Schwanninger, M. 2013. A review of recent near-infrared research for wood and paper (Part 2). Appl Spectrosc Rev 48(7): 560-587. https://doi.org/10.1080/05704928.2011.621079
Tyson, J.A.; Schimleck, L.R.; Aguiar, A.M.; Abad, J.I.M.; Rezende, G.D.S.P; Filho, O.M. 2012. Development of near infrared calibrations for physical and mechanical properties of eucalypt pulps of mill-line origin. J Near Infrared Spec 20(2): 287-294. https://doi.org/10.1255/jnirs.988
Watanabe, K.; Mansfield, S. D.; Avramidis, S. 2011. Application of near-infrared spectroscopy for moisture-based sorting of green, hem-fir timber. J Wood Sci 57(4): 288-294. https://doi.org/10.1007/s10086-011-1181-2
Yang, L.; Liu, H.; Cai, Y.; Hayashi, K.; Wu, Z. 2014. Effect of drying conditions on the collapse-prone wood of Eucalyptus urophylla. BioResources 9(4): 7288-7298. https://doi.org/10.15376/biores.9.4.7288-7298
Zhang, M.; Liu, Y.; Yang, Z. 2015. Correlation of near infrared spectroscopy measurements with the surface roughness of wood. BioResouces 10(4): 6953-6960. https://doi.org/10.15376/biores.10.4.6953-6960
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2020-07-01
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A. Amaral, E., M. Santos, L., R. G. Hein, P., V. S. Costa, E., & F. Trugilho, P. (2020). Estimation of moisture in wood chips by near infrared spectroscopy. Maderas-Cienc Tecnol, 22(3), 291–302. Retrieved from https://revistas.ubiobio.cl/index.php/MCT/article/view/4076
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