Journal of the Korean Wood Science and Technology

The Korean Society of Wood Science & Technology (한국목재공학회)
권호 표지
DOI QR코드

DOI QR Code

Evaluation of Surface Moisture Content of Liriodendron tulipifera Wood in the Hygroscopic Range Using NIR Spectroscopy

근적외선 분광분석법을 이용한 백합나무 목재의 섬유포화점 이하 표면함수율 평가

  • Eom, Chang-Deuk (Dept. of Forest Sciences, College of Agriculture and Life Science, Seoul National University) ;
  • Han, Yeon-Jung (Dept. of Forest Sciences, College of Agriculture and Life Science, Seoul National University) ;
  • Chang, Yoon-Sung (Dept. of Forest Sciences, College of Agriculture and Life Science, Seoul National University) ;
  • Park, Jun-Ho (Dept. of Forest Sciences, College of Agriculture and Life Science, Seoul National University) ;
  • Choi, Joon-Weon (Dept. of Forest Sciences, College of Agriculture and Life Science, Seoul National University) ;
  • Choi, In-Gyu (Dept. of Forest Sciences, College of Agriculture and Life Science, Seoul National University) ;
  • Yeo, Hwan-Myeong (Dept. of Forest Sciences, College of Agriculture and Life Science, Seoul National University)
  • 엄창득 (서울대학교 농업생명과학대학 산림과학부) ;
  • 한연중 (서울대학교 농업생명과학대학 산림과학부) ;
  • 장윤성 (서울대학교 농업생명과학대학 산림과학부) ;
  • 박준호 (서울대학교 농업생명과학대학 산림과학부) ;
  • 최준원 (서울대학교 농업생명과학대학 산림과학부) ;
  • 최인규 (서울대학교 농업생명과학대학 산림과학부) ;
  • 여환명 (서울대학교 농업생명과학대학 산림과학부)
  • Received : 2010.09.14
  • Accepted : 2010.10.25
  • Published : 2010.11.25
Download PDF
⟨ Previous Next ⟩

Abstract

For efficient use of wood, it is important to control moisture of wood in processing wood. Near-infrared (NIR) spectroscopy can be used to estimate the physical and chemical properties of materials quickly and nondestructively. In this study, it was intended to measure the moisture contents on the surface of wood using NIR spectroscopy coupled with multivariate analytic statistical techniques. Because NIR spectroscopy is affected by the chemical components of the specimens and contains signal noise, a regression model for detecting moisture content of wood was established after carrying out several numerical pretreatments such as Smoothing, Derivative and Normalization in this study. It shows that the regression model using NIR absorbance in the range of 750~2,500 nm predicts the actual surface moisture content very well. Near-infrared spectroscopy technique developed in this study is expected to improve a technology to control moisture content of wood in using and drying process.

목재의 합리적인 이용을 위하여 목재 가공 또는 이용시 수분제어를 통한 건조결함 발생 최소화가 중요하다. 근적외선 분광분석법을 이용하여 재료의 물리적 화학적 성질을 신속하고 비파괴적으로 파악할 수 있다. 본 연구 에서는 근적외선 분광분석법을 이용하여 목재의 표면함수율을 측정하였다. 근적외선 분광스펙트럼에는 목재의 화학적 성분의 영향으로 인하여 노이즈가 포함될 수 있기 때문에 평활화, 미분, 표준화를 포함한 수학적 전처리를 적용한 후 회귀분석을 실시하였다. 750~2,500 nm 범위의 적외선 흡광도를 이용한 회귀모델을 통하여 목재의 표면함수율 측정이 가능함을 확인하였다. 본 연구에서 개발된 근적외선 분광분석법을 통하여 비평형상태에서 목재 수분을 정확히 탐지함으로써 건조 또는 수분흡습 중 목재 내 수분이동량을 제어할 수 있는 기술이 발전될 수 있으리라 기대된다.

Keywords

References

  1. Alves, A, M. Schwanninger, H. Pereira, and J. Rodrigucs. 2006. Calibration of NIR to assess lignin composition (H/G ratio) in maritime pine wood using analytical pyrolysis as the reference method. Holzforschung 60: 29-31. https://doi.org/10.1515/HF.2006.006
  2. Blanco, M. and I. Villarroya. 2002. NIR spectroscopy: a rapid-response analytical tool. Trends in analytical chemistry 21(4): 240-250. https://doi.org/10.1016/S0165-9936(02)00404-1
  3. Eom, C D., J. H. Park, K. J. Yoon, and H. M. Yeo 2009. Evaluation on internal moisture movement of yellow poplar in unsteady state. Proceeding of 2009 Korean society of wood science and technology annual meeting 47-48.
  4. Gierlinger. N., M. Schwanninger, B. Hinterstoisser, and R. Wimmer. 2002. Rapid determination of heartwood extractives in Larix sp by means of Fourier transform near infrared spectroscopy. Journal of Near Infrared Spectroscopy 10: 203-214. https://doi.org/10.1255/jnirs.336
  5. Lundqvist, S. O. and L. G. Thygesen. 2000. NIR measurement of moisture content in wood under unstable temperature conditions. Journal of Near Infrared Spectroscopy 8: 183-189. https://doi.org/10.1255/jnirs.277
  6. Schimleck, L. and J. Workman. 2004. Analysis of Timber and Paper. Agronomy 44: 635-646.
  7. Schultz, T. P. and D. A Burns. 1990. Rapid secondary analysis of lignocellulose Comparison of near-infrared (NIR) and Fourier-transform infrared (FTIR). TAPPI Journal 73: 209-212.
  8. Schwanninger, M. and B. Hinterstoisser. 2002. Klason lignin: Modifications to improve the precision of the standardized determination. Holzforschung. 56: 161-166. https://doi.org/10.1515/HF.2002.027
  9. Tsuchikawa, S. 2007. A Review of Recent Near Infrared Research for Wood and Paper. Applied Spectroscopy Reviews 42 43-71. https://doi.org/10.1080/05704920601036707
  10. Tsuchikawa, S., M. Torii, and S. Tsutsumi. 1996. Application of near infrared spectrophotometry to wood. 4. Calibration equations for moisture content. Mokuzai Gakkaishi 42: 743-754.
  11. Yeh, T. F., H. M. Chang and J. F. Kadla. 2004. Rapid prediction of solid wood lignin content using transmittance near-infrared spectroscopy. Journal of Agricultural and Food Chemistry 52: 1435-1439. https://doi.org/10.1021/jf034874r
  12. 안태호, H. Kanada, and T. Uomoto. 2005. 근적외선 분광법에 의한 콘크리트 진단방법. 콘크리트학회지 18(3): 51-58.
  13. 조규채. 1998. 근적외선 분광분석법의 농업 분야 적용. 한국농업기계학회지 23(2):195-205.

Cited by

  1. Development of Moisture Content Prediction Model for Larix kaempferi Sawdust Using Near Infrared Spectroscopy vol.43, pp.3, 2015, https://doi.org/10.5658/WOOD.2015.43.3.304
  2. The shrinkage properties of red pine wood assessed by image analysis and near-infrared spectroscopy vol.34, pp.13, 2016, https://doi.org/10.1080/07373937.2016.1138964
  3. Moisture Content Prediction Model Development for Major Domestic Wood Species Using Near Infrared Spectroscopy vol.43, pp.3, 2015, https://doi.org/10.5658/WOOD.2015.43.3.311
  4. Chemometrics Approach For Species Identification of Pinus densiflora Sieb. et Zucc. and Pinus densiflora for. erecta Uyeki - Species Classification Using Near-Infrared Spectroscopy in combination with Multivariate Analysis - vol.43, pp.6, 2015, https://doi.org/10.5658/WOOD.2015.43.6.701