Skip to main content
Log in

Estimation of moisture content of trembling aspen (Populus tremuloides Michx.) strands by near infrared spectroscopy (NIRS)

  • Original
  • Published:
European Journal of Wood and Wood Products Aims and scope Submit manuscript

Abstract

In a preliminary study on improving manufacturing control of composite wood products, near infrared spectroscopy (NIRS) was tested to determine moisture content (MC) of trembling aspen (Populus tremuloides Michx.) flakes that are used in oriented strand board (OSB) manufacturing. Three drying cycles (of 1 kg each) of aspen flakes were scanned at different drying levels by NIRS in the 1,300–2,200 nm spectral region. The study showed an influence of MC on NIR spectra. A partial least squares regression model was developed between NIR spectra and gravimetric-based moisture contents. The statistics achieved R2 and root mean square error (RMSE) for the calibration model ranging from 0.97 to 0.99 and from 2.5 to 5.9 %, respectively. The validation statistic models achieved R2 and RMSE ranging from 0.96 to 0.99 and from 2.7 to 6.01 %, respectively. These preliminary results show that NIRS can be a useful tool for monitoring MC of OSB flakes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Acuna MA (2006) Wood properties and use of sensor technology to improve optimal bucking and value recovery of Douglas-fir. Ph.D. thesis dissertation, College of Forestry, Oregon State University

  • Adedipe OE, Dawson-Andoh B (2008) Predicting moisture content of yellow poplar (Liriodendron Tulipifera L.) veneer using near infrared spectroscopy. For Prod J 58(4):425–473

    Google Scholar 

  • ASTM D4442-07 (2009) Standard test methods for direct moisture content measurement of wood and wood-base materials. Book of standards Vol 04.10

  • Bächle H, Zimmer B, Windeisen E, Wegener G (2010) Evaluation of thermally modified beech and spruce wood and their properties by FT-NIR spectroscopy. Wood Sci Technol 44(3):421–433

    Article  Google Scholar 

  • Blanco M, Alcalia M (2006) Simultaneous quantitation of five active principles in a pharmaceutical preparation: development and validation of a near infrared spectroscopic method. Eur J Pharm Sci 27(2–3):280–286

    Article  CAS  PubMed  Google Scholar 

  • Boulesteix A-L, Strimmer K (2006) Partial least squares: a versatile tool for the analysis of high dimensional genomic data. Brief Bioinform 8(1):32–44

    Article  PubMed  Google Scholar 

  • Braga JWB, Pastore TCM, Coradin VTR, Camargos JAA, Da Silva AR (2011) The use of near infrared spectroscopy to identify solid wood specimens of Swietenia macrophylla. IAWA J 32(2):285–296

    Google Scholar 

  • Burns DA, Ciurczak EW (2008) Handbook of near-infrared analysis. 3rd edn. p.cm. In: Pratical spectroscopy, Vol 5, Issue (35). ISBN 978-0-8493-7393-0

  • Chen MJ, Meister JJ, Gunnells DW, Gardner DJ (1995) A process for coupling wood to thermoplastic using graft copolymers. Adv Polym Technol 14(2):97–109

    Article  Google Scholar 

  • Chow S (1971) Infrared spectral characteristics and surface inactivation of wood at high temperatures. Wood Sci Technol 5(1):27–39

    Article  CAS  Google Scholar 

  • Christiansen AW (1990) How over drying wood reduces its bonding to phenol-formaldehyde adhesives: a critical review of the literature. Part I. Physical responses. Wood Fiber Sci 22(4):441–459

    CAS  Google Scholar 

  • Christiansen AW (1991) How over drying wood reduces its bonding to phenol formaldehyde adhesives: A critical review of the literature. Part II chemical reactions. Wood Fiber Sci 23(1):69–84

    CAS  Google Scholar 

  • Cozzolino D, Murray I (2003) Identification of animal meat muscles by visible and near infrared reflectance spectroscopy. LWT-Food Sci Technol Int 37(4):447–452

    Article  Google Scholar 

  • Cozzolino D, Smyth HE, Gishen M (2003) Feasibility study on the use of visible and near-infrared spectroscopy together with chemometrics to discriminate between commercial white wines of different varietal origins. J Agric Food Chem 51(26):703–708

    Article  Google Scholar 

  • Engstrom B, Johnson B, Hedquist M, Grothage M, Sundstrom H, Arlebrandt A (1998) Process modeling system for particleboard manufacturing, incorporating near infrared spectroscopy on dried wood particles. In: Proceedings of the 2nd European Panel Products Symposium, 21–22 October 1998, Llandudno, Wales, pp 107–114

  • Esbensen KH, Guyot D, Westad F, Houmoller LP (2002) Multivariate data analysis in practice: an introduction to multivariate data analysis and experimental design. CAMO Process AS, 5th ed.

  • Esteban LG, Gril J, de Palacios de Palacios P, Guindeo Casasús A (2005) Reduction of wood hygroscopicity and associated dimensional response by repeated humidity cycles. Ann For Sci 62(3):275–284

    Article  Google Scholar 

  • Faber NM, Bro R (2001) Standard error of prediction for multiway PLS. 1. Background and simulation study. Chemom Intell Lab Syst 61(1–2):133–149

    Google Scholar 

  • Faber NM, Song X-H, Hopke PK (2003) Sample-specific standard error of prediction for partial least squares regression. TrAC Trends Anal Chem 22(5):330–334

    Article  CAS  Google Scholar 

  • Fackler K, Schwanninger M, Gradinger C, Hinterstoiser B, Messner K (2007a) Qualitative and quantitative changes of beech wood degraded by wood-rotting basidiomycetes monitored by Fournier transform infrared spectroscopic methods and multivariate date analysis. Microb Lett 271(7):162–169

    Article  CAS  Google Scholar 

  • Fackler K, Schmutzer M, Manoch L, Schwanninger M, Hinterstoisser B, Ters T, Messner K, Gradinger C (2007b) Evaluation of the selectivity of white rot isolates using near infrared spectroscopic techniques. Enzyme Microb Tech 41(6):881–887

    Article  CAS  Google Scholar 

  • Geladi P, Kowalski B (1986) Partial least-squares regression: a tutorial. Anal Chim Acta 185:1–17

    Article  CAS  Google Scholar 

  • González-Martín I, González-Pérez C, Hernández-Méndez J, Alvarez-García N (2003) Determination of fatty acids in the subcutaneous fat of Iberian breed swine by near infrared spectroscopy (NIRS) with a fibre-optic probe. Meat Sci 65(2):713–719

    Article  PubMed  Google Scholar 

  • Guo W (2013) Self-heating and spontaneous combustion of wood pallets during storage. Ph.D. thesis, Faculty of Chemical and Biological Engineering, University of British Columbia

  • Hans G, Leblon B, Stirling R, Nader J, LaRocque A, Cooper P (2013) Monitoring of moisture content and basic specific gravity in black spruce logs using a hand-held MEMS-based near-infrared spectrometer. For Chron 89(5):607–620

    Article  Google Scholar 

  • Koumbi-Mounanga T, Ung T, Groves K, Leblon B, Cooper P (2013) Moisture and surface quality sensing of Douglas-fir (Pseudotsuga menziesii var. menziesii) veneer products. For Chron 89(5):646–653

    Article  Google Scholar 

  • Koumbi-Mounanga T, Ung T, Cooper P, Leblon B, Groves K (2014) Surface quality sensing of trembling aspen (Populus tremuloides Michx.) veneer products by near infrared spectroscopy. Wood Mater Sci Eng. Online. doi:10.1080/17480272.2014.923936

    Google Scholar 

  • Lande S, van Riel S, Hoitbo OA, Schneider MH (2009) Development of chemometric model based on near infrared spectroscopy and thermogravimetric analysis for predicting the treatment level of furfurylated Scots pine. Wood Sci Technol 44(2):189–203

    Article  Google Scholar 

  • Leblon B, Adedipe O, Hans G, Haddadi A, Tsuchikawa S, Burger J, Stirling R, Pirouz Z, Groves K, Nader J, LaRocque A (2013) A review of near infrared spectroscopy for monitoring moisture content and density of solid wood. For Chron 89(5):595–606

    Article  Google Scholar 

  • Lee SB, Luner P (1972) The wetting and interfacial properties of lignin. TAPPI 55(1):116–121

    CAS  Google Scholar 

  • Lu JZ, Wu Q (2005) Surface and interfacial characterization of wood-pvc composite: Imaging morphology and wetting behaviour 1. Wood Fiber Sci 37(1):95–111

    CAS  Google Scholar 

  • Miller JN, Miller JC (2005) Statistics and chemometrics for Analytical chemistry 5th edn. Pearson Education Limited 2000, QD75.4.S8M54

  • Mitsui K, Inagaki T, Tsuchikawa S (2008) Monitoring of hydroxyl groups in wood during heat treatment using NIR spectroscopy. Biomacromolecules 9(1):286–288

    Article  CAS  PubMed  Google Scholar 

  • Mounanga TK (2008) Original antioxidant amphiphilic compounds for wood preservative formulations. (Translated from French of the Ph.D. thesis University of Lorraine), Faculty of Sciences and Technology previously, University Henri Poincare (UHP), Nancy, France

  • Mounanga TK, Gérardin P, Poaty B, Perrin D, Gérardin C (2008) Synthesis and properties of antioxidant amphiphilic ascorbate salts. Coll Surf Physiochemical Eng.Asp 318(1–3):134–140

    Article  CAS  Google Scholar 

  • Natsuga M, Kawamura S (2006) Visible and near-infrared reflectance spectroscopy for determining physicochemical properties of rice. ASABE 49(4):1069–1076

    Article  CAS  Google Scholar 

  • Neville HH, Elvin PJ (1975) BLIPS: the building research establishment library processing system. Aslib Proc 27(5):189–203

    Article  Google Scholar 

  • Patton TC (1970) A simplified review of adhesion theory based on surface energetics. TAPPI 53(3):421–429

    CAS  Google Scholar 

  • Pezzullo JC (2000) Graph Pad Software. Quickcalcs: online calculators of p-value from a Z, t, F, r, or Chi square value, (online), Available at: http://www.graphpad.com/quickcalcs/pvalue1.cfm, Accessed March, 2002

  • Rosipal R, Kramer N (2006) Overview and recent advances in partial least squares Subspace. Latent Str Feature Sel 3940:34–51

    Article  Google Scholar 

  • Schwanninger M, Rodrigues J, Fackler K (2011) A review of band assignments in near-infrared spectra of wood and wood components. J Near-Infrared Spectrosc 19(5):287–308

    Article  CAS  Google Scholar 

  • Stirling R (2013) Near-infrared spectroscopy as a potential quality assurance tool for the wood preservation industry. For Chron 89(5):654–658

    Article  Google Scholar 

  • Thygesen LG, Lundqvist SO (2000a) NIR measurement of moisture content in wood under unstable temperature conditions. Thermal effects in near-infrared spectra of wood (Part I). J Near-Infrared Spectrsc 8(3):183–189

    Article  CAS  Google Scholar 

  • Thygesen LG, Lundqvist SO (2000b) NIR measurement of moisture content in wood under unstable temperature conditions. Handling temperature change (Part II). J Near-Infrared Spectrosc 8(3):183–189

    Article  CAS  Google Scholar 

  • Tsuchikawa S, Schwanninger M (2013) A review of recent near-infrared research for wood and paper. (Part2). Appl Spectrosc Rev 48(7):560–587

    Article  Google Scholar 

  • Tsuchikawa S, Siesler HW (2003) Near-infrared spectroscopic monitoring of the diffusion process of deuterium labelled molecules in wood Part I: softwood. Appl Spectrosc Rev 57:675–681

    Article  CAS  Google Scholar 

  • Wang S, Du G, Zhang Y (2005) Microwave wood strand drying energy consumption, VOC emission and drying quality. In: IADC. 3rd Inter-American drying conference, vol 3, Issue 4, pp 1–10

  • Williams P, Norris K (1987) Near-infrared technology in the agricultural and food industries. American Association of Cereal Chemists, Inc., St. Paul, Minnesota

    Google Scholar 

  • Yang S-Y, Han Y, Chang Y-S, Kim K-M, Choi I-G, Yeo H (2013) Moisture content prediction below and above fiber saturation point by partial least squares regression analysis on near infrared absorption spectra of Korean pine. Wood Fiber Sci 45(4):1–8

    Google Scholar 

  • Yeo TL, Sun TV, Grattan KT (2008) Fibre-optic sensor technologies for humidity and moisture measurement. Sens Actuators A 144(2):280–295

    Article  CAS  Google Scholar 

  • Zhang Y, Du G, Wang S (2005) Microwave wood strand drying: Energy consumption VOC emission and drying quality. In: Proceeding of the 3rd Inter-American drying conference, 2005

Download references

Acknowledgments

The authors appreciate the assistance of the Value to Wood Program from the Canadian Forest Service, Natural Resources Canada for the financial support and the participation of Tony Ung from Faculty of Forestry (University of Toronto) with the technical laboratory assistance, Frank Rinker from FPInnovations (Vancouver) and Armand LaRocque from Faculty of Forestry and Environmental Management (UNB, Fredericton) with the NIR scans.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Thierry Koumbi-Mounanga.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 872 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Koumbi-Mounanga, T., Groves, K., Leblon, B. et al. Estimation of moisture content of trembling aspen (Populus tremuloides Michx.) strands by near infrared spectroscopy (NIRS). Eur. J. Wood Prod. 73, 43–50 (2015). https://doi.org/10.1007/s00107-014-0856-y

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00107-014-0856-y

Keywords

Navigation