Abstract
Predictive models of the moisture content of Para rubber timber were developed and validated using near-infrared (NIR) spectroscopy. A portable NIR spectrometer connected to a smartphone was developed to facilitate real-time moisture content determination of Para rubber timber. An android application was created to control the NIR spectrometer in acquiring, displaying, and processing the spectral data on the smartphone. Three predictive models for determining the moisture content of Para rubber timber were developed using partial least squares regression in the range 0–89% on a dry basis (%db), < 30% db, and > 30% db. The predictive model for moisture content in the range 0–89%db had a correlation coefficient of cross validation (Rcv) of 0.98 and a root-mean-square error of cross validation (RMSECV) of 5.48%. The predictive model for moisture content in the range less than 30%db had values for Rcv and RMSECV of 0.84 and 2.05% db, respectively. Lastly, the predictive model of moisture content in the range greater than 30% db had values for Rcv and RMSECV of 0.85 and 4.57% db, respectively. The performance of the predictive equation for determining the moisture content in Para rubber timber in the range less than 30% db was validated using unknown samples, which were not used in the model development, assigned as an external prediction set, which resulted in a root-mean-square error of prediction (RMSEP) of 1.44% db. The portable NIR spectrometer connected to a smartphone through an android application is a suitable system for practical application in sawn timber factories because it is cheap and conveniently portable. In addition, the calibration model should be updated and more samples added to cover the variation in growing season and growth area for greater robustness and accuracy of the predictive models.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
ASTM (2000) D 143–94 Standard test methods for small clear specimens of timber American Society for Testing and Materials
Buijs K, Choppin GR (1963) Near-infrared studies of the structure of water. II Ionic Solut J Chem Phys 39(8):2042–2050
Defo M, Taylor AM, 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
Dietsch P, Franke S, Franke B, Gamper A, Winter S (2015) Methods to determine wood moisture content and their applicability in monitoring concepts. J Civil Struct Health Monit 5(2):115–127. https://doi.org/10.1007/s13349-014-0082-7
dos Santos LM, Amaral EA, Nieri EM, Costa EVS, Trugilho PF, Calegário N, Hein PRG (2020) Estimating wood moisture by near infrared spectroscopy: Testing acquisition methods and wood surfaces qualities. Wood Mater Sci Eng. https://doi.org/10.1080/17480272.2020.1768143
Fujimoto T, Kurata Y, Matsumoto K, Tsuchikawa S (2008) Application of near infrared spectroscopy for estimating wood mechanical properties of small clear and full length lumber specimens. J near Infrared Spec 16(6):529–537. https://doi.org/10.1255/jnirs.818
Inagaki T, Yonenobu H, Tsuchikawa S (2008) Near-infrared spectroscopic monitoring of the water adsorption/desorption process in modern and archaeological wood. Appl Spectrosc 62(8):860–865. https://doi.org/10.1366/000370208785284312
Inarejos-García AM, Gómez-Alonso S, Fregapane G, Salvador MD (2013) Evaluation of minor components, sensory characteristics and quality of virgin olive oil by near infrared (NIR) spectroscopy. Food Res Int 50(1):250–258. https://doi.org/10.1016/j.foodres.2012.10.029
Kaewngam P (2021) Rubber wood, value and opportunity in the Thai wood industry. The Office of Industrial Economics, Ministry of Industry. http://www.oie.go.th/assets/portals/1/fileups/2/files/ArticlesAnalysis/rubberwood19.pdf. Accessed 12 May 2021
Kang R, Zhao M, O’Donnell C (2017) Explorations of guided microwave spectroscopy (GMS) features for infant milk formula detection. Biosyst Food Eng Res Rev 22:85
Kobori H, Gorretta N, Rabatel G, Bellon-Maurel V, Chaix G, Roger J-M, Tsuchikawa S (2013) Applicability of Vis-NIR hyperspectral imaging for monitoring wood moisture content (MC). Holzforschung 67(3):307–314. https://doi.org/10.1515/hf-2012-0054
Meier KJ, Brudney JL, Bohte J (2014) Applied statistics for public and nonprofit administration. Wadsworth, Boston
Osborne BG, Fearn T, Hindle PH (1993) Practical NIR spectroscopy with applications in food and beverage analysis. Longman Science & Technology, U.S.A.
Rego G, Ferrero F, Valledor M, Campo JC, Forcada S, Royo LJ, Soldado A (2020) A portable IoT NIR spectroscopic system to analyze the quality of dairy farm forage. Comput Electron Agric. https://doi.org/10.1016/j.compag.2020.105578
Schwanninger M, Rodrigues JC, Fackler K (2011) A review of band assignments in near infrared spectra of wood and wood components. J Near Infrared Spec 19(5):287–308. https://doi.org/10.1255/jnirs.955
Tham VTH, Inagaki T, Tsuchikawa S (2019) A new approach based on a combination of capacitance and near-infrared spectroscopy for estimating the moisture content of timber. Wood Sci Technol 53(3):579–599. https://doi.org/10.1007/s00226-019-01077-0
Thepaksorn P, Siriwong W, Neitzel RL, Somrongthong R, Techasrivichien T (2018) Relationship between noise-related risk perception, knowledge, and the use of hearing protection devices among para rubber wood sawmill workers. Saf Health Work 9(1):25–29. https://doi.org/10.1016/j.shaw.2017.06.002
TISI (2009) 2423–2552. Rubberwood sawn timber. Thai Industrial Standards Institute TISI.
Tsuchikawa S (2007) A review of recent near infrared research for wood and paper. Appl Spectrosc Rev 42(1):43–71. https://doi.org/10.1080/05704920601036707
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
Tsuchikawa S, Tsutsumi S (1998) Adsorptive and capillary condensed water in biological material. J Mater Sci Lett 17(8):661–663. https://doi.org/10.1023/A:1006672324163
Watanabe K, Mansfield SD, 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
Williams P (2007) Grains and seeds. In: Ozaki Y, McClure WF, Christy AA (eds) Near-infrared technology in food science and technology. John Wiley & Sons Inc, New Jersey, pp 165–217
Acknowledgements
The Thailand Research Fund (Grant number: RDG62T0001) and the Faculty of Engineering at Kamphaengsaen, Kasetsart University, Thailand provided financial support for this research.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Noypitak, S., Puttipipatkajorn, A., Ruangkhasap, S. et al. Application of a portable near-infrared spectrometer for rapid, non-destructive evaluation of moisture content in Para rubber timber. Wood Sci Technol 56, 285–303 (2022). https://doi.org/10.1007/s00226-021-01354-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00226-021-01354-x