Evaluation of the spatial variation in moisture content inside wood pieces during drying by NIR spectroscopy

Lívia Freire Baliza; Carlos Henrique da Silva; Evelize Aparecida Amaral; Fernanda Maria Guedes Ramalho; Paulo Fernando Trugilho; Honggang Sun; Paulo Ricardo Gherardi Hein

doi:10.1515/hf-2022-0123

Article

Evaluation of the spatial variation in moisture content inside wood pieces during drying by NIR spectroscopy

Lívia Freire Baliza , Carlos Henrique da Silva , Evelize Aparecida Amaral , Fernanda Maria Guedes Ramalho , Paulo Fernando Trugilho , Honggang Sun and Paulo Ricardo Gherardi Hein

Published/Copyright: December 12, 2022

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From the journal Holzforschung Volume 77 Issue 2

Abstract

The moisture content (MC) of wood affects its industrial performance, but it is difficult to monitor spatial variations in MC. Here, a multivariate regression was developed to estimate the MC from near infrared (NIR) spectra and was used to monitor the spatial variation in the MC of wood during air- and oven-drying. The spectra and mass of wood pieces were measured at five stages during drying (at each 20% loss of initial water mass). Wood pieces were dried naturally and oven-dried at 60 °C. Initially, 25 spectra were recorded at equidistant points covering the entire longitudinal × radial surface of the sample. Then, a planing machine was used to access the inside of the wood, and NIR spectra were measured for each new surface, at a total of 100 points spatially distributed within the wood pieces. The wood pieces were analyzed in their original state, and when they had lost 20, 40, 60, and 80% of their initial water mass. An NIR-based regression (R²_p = 0.90 and RMSEP = 10.51%) was applied to estimate the MC, and its spatial gradient during drying was then mapped. These analyses revealed the spatial variation in MC within wood pieces during drying.

Keywords: desorption monitoring; moisture gradient; NIR spectroscopy; spatial variation; wood drying

Corresponding author: Paulo Ricardo Gherardi Hein, Departamento de Ciências Florestais, DCF, Universidade Federal de Lavras, 37200-900 Lavras, MG, Brazil; and Núcleo de Estudos em Madeira (NEMAD/UFLA), Lavras, Brazil, E-mail: paulo.hein@ufla.br

Funding source: Conselho Nacional de Desenvolvimento Científico e Tecnológico

Award Identifier / Grant number: 309620/2020-1

Award Identifier / Grant number: 406593/2021-3

Acknowledgments

The authors thank Jennifer Smith, PhD, from Edanz (https://www.edanz.com/ac) for editing a draft of this manuscript.

Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: This project was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001, by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq: grants n. 406593/2021-3) and by Fundação de Amparo a ` Pesquisa do Estado de Minas Gerais (FAPEMIG). P. R. G. Hein was supported by CNPq grants (process no. 309620/2020-1). This study was also supported by the Wood Science and Technology Graduation Program (DCF/UFLA, Brazil).
Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

References

Adedipe, O.E. and Dawson-Andoh, B. (2008). Predicting moisture content of yellow-poplar (Liriodendron tulipifera) veneer using nearinfrared spectroscopy. For. Prod. J. 58: 28–33.Search in Google Scholar

Amaral, E.A., Santos, L.M., Costa, E.V.S., Trugilho, P.F., and Hein, P.R.G. (2020). Estimation of moisture in wood chips by near infrared spectroscopy. Maderas Cienc. Tecnol. 22: 291–302, https://doi.org/10.4067/s0718-221x2020005000304.Search in Google Scholar

Andersson, M., Persson, L., Sjöholm, M., and Svanberg, S. (2006). Spectroscopic studies of wood-drying processes. Opt. Express 14: 3641–3653.10.1364/OE.14.003641Search in Google Scholar PubMed

Associação Brasileira de Normas Técnicas (ABNT) (2003). NBR 14929: Madeira – determinação do teor de umidade de cavacos – método por secagem em estufa. ABNT, Rio de Janeiro.Search in Google Scholar

Costa, E.V.S., Rocha, M.F.V., Hein, P.R.G., Amaral, E.A., Santos, L.M., Brandão, L.E.V.S., and 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 Spectrosc. 26: 106–116, https://doi.org/10.1177/0967033518757070.Search in Google Scholar

Defo, M., Taylor, M., and Bond, B. (2007). Determination of moisture content and density of fresh-sawn red oak lumber by near-infrared spectroscopy. For. Prod. J. 57: 68–72.Search in Google Scholar

Engelund, E.T., Thygesen, L.G., Svensson, S., and Hill, C.A.S. (2013). A critical discussion of the physics of wood–water interactions. Wood Sci. Technol. 47: 141–161, https://doi.org/10.1007/s00226-012-0514-7.Search in Google Scholar

Fujimoto, T., Numa, T., Kobori, H., and Tsuchikawa, S. (2015). Visualisation of spatial distribution of moisture content and basic density using near-infrared hyperspectral imaging method in sugi (Cryptomeria japonica). Int. Wood Prod. J. 6: 46–48, https://doi.org/10.1179/2042645314y.0000000084.Search in Google Scholar

Gonçalez, J.C., Breda, L.C.S., Barros, J.F.M., Macedo, D.G., Janin, G., Costa, A.F., and Vale, A.T. (2006). Technological characteristics of the wood of Eucalyptus Grandis W.Hill ex Maiden and Eucalyptus cloeziana F. Muell, as a supply for the furniture industry. Revista Ciência Florestal 16: 329–341, https://doi.org/10.5902/198050981912.Search in Google Scholar

Hein, P.R.G., Lima, J.T., and Chaix, G. (2010). Effects of sample preparation on NIR spectroscopic estimation of chemical properties of Eucalyptus urophylla S.T. Blake wood. Holzforschung 64: 45–54.10.1515/hf.2010.011Search in Google Scholar

Kobori, H., Gorretta, N., Rabatel, G., Bellon-Maurel, V., Chaix, G., Roger, J.M., and Tsuchikawa, S. (2013). Applicability of Vis-NIR hyperspectral imaging for monitoring wood moisture content (MC). Holzforschung 67: 307–314, https://doi.org/10.1515/hf-2012-0054.Search in Google Scholar

Leblon, B., Adedipe, O., Hans, G., Haddadi, A., Tsuchikawa, S., Burger, J., Stirling, R., Pirouz, Z., Groves, K., Nader, J., et al.. (2013). A review of near-infrared spectroscopy for monitoring moisture content and density of solid wood. For. Chron. 89: 595–606, https://doi.org/10.5558/tfc2013-111.Search in Google Scholar

Lenth, C. and Sargent, R. (2008). Wood material behavior during drying: moisture-dependent tensile stiffness and strength of radiata pine at 70–150°C. Dry. Technol. 26: 1112–1117, https://doi.org/10.1080/07373930802266082.Search in Google Scholar

Martens, H.E. and Tormod, N. (1989). Multivariate calibration. J. Wiley, New York.Search in Google Scholar

Mora, C.R., Schimleck, L.C., Clark, A., and Daniels, R.F. (2011). Determination of basic density and moisture content of merchantable loblolly pine logs by near infrared spectroscopy. J. Near Infrared Spectrosc. 19: 392–399, https://doi.org/10.1255/jnirs.947.Search in Google Scholar

Nunes, C.A., Freitas, M.P., Pinheiro, A.C.M., and Bastos, S.C. (2012). Chemoface: a novel free user-friendly interface for chemometrics. J. Braz. Chem. Soc. 23: 2003–2010, https://doi.org/10.1590/s0103-50532012005000073.Search in Google Scholar

Pasquini, C. (2018). Near infrared spectroscopy: a mature analytical technique winew perspective – a review. Anal. Chim. Acta 5: 8–36, https://doi.org/10.1016/j.aca.2018.04.004.Search in Google Scholar PubMed

Perré, P. (1997). Image analysis, homogenization, numerical simulation and experiment as complementary tools to enlighten the relationship between wood anatomy and drying behavior. Dry. Technol. 15: 2211–2238, https://doi.org/10.1080/07373939708917359.Search in Google Scholar

Sandak, J., Sandak, A., and Meder, R. (2016). Assessing trees, wood and derived products with near infrared spectroscopy: hints and tips. J. Near Infrared Spectrosc. 24: 485–505, https://doi.org/10.1255/jnirs.1255.Search in Google Scholar

Santos, L.M., Amaral, E.A., Nieri, E.M., Costa, E.V.S., Trugilho, P.F., Calegário, N., and Hein, P.R.G. (2020). Estimating wood moisture by near infrared spectroscopy: testing acquisition methods and wood surfaces qualities. Wood Mater. Sci. Eng. 16: 336–343, https://doi.org/10.1080/17480272.2020.1768143.Search in Google Scholar

Schwanninger, M., Rodrigues, J., and Fackler, K. (2011). A review of band assignments in near infrared spectra of wood and wood components. J. Near Infrared Spectrosc. 19: 287–308, https://doi.org/10.1255/jnirs.955.Search in Google Scholar

Severo, E.T.D. (2000). Quality of sawn timber drying of Eucalyptus dunnii. Ciência Florest. 10: 109–124, https://doi.org/10.5902/19805098399.Search in Google Scholar

Stefansson, P., Thiis, T., Gobakken, L.R., and Burud, I. (2020). Hyperspectral NIR time series imaging used as a new method for estimating the moisture content dynamics of thermally modified Scots pine. Wood Mater. Sci. Eng. 16: 49–57, https://doi.org/10.1080/17480272.2020.1772366.Search in Google Scholar

Williams, P.C. and Sobering, D.C. (1993). Comparison of commercial near infrared transmittance and reflectance instruments for analysis of whole grains and seeds. J. Near Infrared Spectrosc. 1: 25–33, https://doi.org/10.1255/jnirs.3.Search in Google Scholar

Workman, J. and Weywer, L. (2007). Practical guide to interpretive near-infrared spectroscopy. CRC Press, Boca Raton, p. 332.10.1201/9781420018318Search in Google Scholar

Zhang, H., Li, X., Zhang, H., Zhang, Y., and Li, P. (2011). Application of near infrared spectroscopy in wood water content prediction. Adv. Mater. Res. 187: 434–438, https://doi.org/10.4028/www.scientific.net/amr.187.434.Search in Google Scholar

Received: 2022-07-24

Accepted: 2022-11-29

Published Online: 2022-12-12

Published in Print: 2023-02-23

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Articles in the same Issue

https://doi.org/10.1515/hf-2022-0123

Keywords for this article

desorption monitoring; moisture gradient; NIR spectroscopy; spatial variation; wood drying