16 Wooden Material and Environmental Sciences
375
16.8 Conclusion
As shown above, NIR applied research has attracted considerable attention recently
at the fields of wooden materials and environmental sciences due to its rapid measurement and nondestructive sampling and low-cost characteristics. Another significant
advantage is that many properties could be evaluated simultaneously.
Meanwhile, basic research also has been proceeded actively to make sure prediction model robustness. It is very important to clarify the spectroscopic background
and know the limitation of NIRS. Sometimes, a “bridge” research between theory
and practice is also required.
References
1. M.D. Birkett, M.J.T. Gambino, Estimation of pulp kappa number with near-infrared spectroscopy. Tappi J. 72(9), 193–197 (1989)
2. E. Sjostrom, Wood Chemistry: Fundamentals and Applications (Gulf Professional Publishing,
1993)
3. A.M.M. Alves, R.F.S. Simões, C.A. Santos, B.M. Potts, J. Rodrigues, M. Schwanninger,
Determination of Eucalyptus globulus wood extractives content by near infrared-based partial
least squares regression models: comparison between extraction procedures. J. Near Infrared
Spectrosc. 20(2), 275–285 (2012)
4. D.B. Easty, S.A. Berben, F.A. DeThomas, P.J. Brimmer, Near-infrared spectroscopy for the
analysis of wood pulp: quantifying hardwood-softwood mixtures and estimating lignin content.
Tappi J. 73(10), 257–261 (1990)
5. J.A. Wright, M.D. Birkett, M.J.T. Gambino, Prediction of pulp yield and cellulose content from
wood samples using near infrared reflectance spectroscopy. Tappi J. 73(8), 164–166 (1990)
6. L. Wallbäcks, U. Edlund, B. Norden, I. Berglund, Multivariate characterization of pulp using
solid-state 13C NMR, FTIR, and NIR. Tappi J. 74(10), 201–206 (1991)
7. A.R. Da Silva, T.C.M. Pastore, J.W.B. Braga, F. Davrieux, E.Y.A. Okino, V.T.R. Coradin,
J.A.A. Camargos, A.G.S. Do Prado, Assessment of total phenols and extractives of mahogany
wood by near infrared spectroscopy (NIRS). Holzforschung 67(1), 1–8 (2013)
8. W. He, H. Hu, Rapid prediction of different wood species extractives and lignin content using
near infrared spectroscopy. J. Wood Chem. Technol. 33(1), 52–64 (2013)
9. C. Lepoittevin, J.P. Rousseau, A. Guillemin, C. Gauvrit, F. Besson, F. Hubert, D. Da Silva Perez,
L. Harvengt, C. Plomion, Genetic parameters of growth, straightness and wood chemistry traits
in Pinus pinaster. Ann. For. Sci. 68(4), 873–884 (2011)
10. B. Üner, ˙ I. Karaman, H. Tanrıverdi, D. Özdemir, Determination of lignin and extractive content
of Turkish Pine (Pinus brutia Ten.) trees using near infrared spectroscopy and multivariate
calibration. Wood Sci. Technol. 45(1), 121–134 (2011)
11. S. Tsuchikawa, H. Kobori, A review of recent application of near infrared spectroscopy to
wood science and technology. J. Wood Sci. 61(3), 213–220 (2015)
12. K. Watanabe, S.D. Mansfield, S. Avramidis, Application of near-infrared spectroscopy for
moisture-based sorting of green hem-fir timber. J. Wood Sci. 57(4), 288–294 (2011)
13. M. Defo, A.M. Taylor, B. Bond, Determination of moisture content and density of fresh-sawn
red oak lumber by near infrared spectroscopy. For. Prod. J. 57(5), 68–72 (2007)
14. V.T.H. Tham, T. Inagaki, S. Tsuchikawa, 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 (2018)
375
16.8 Conclusion
As shown above, NIR applied research has attracted considerable attention recently
at the fields of wooden materials and environmental sciences due to its rapid measurement and nondestructive sampling and low-cost characteristics. Another significant
advantage is that many properties could be evaluated simultaneously.
Meanwhile, basic research also has been proceeded actively to make sure prediction model robustness. It is very important to clarify the spectroscopic background
and know the limitation of NIRS. Sometimes, a “bridge” research between theory
and practice is also required.
References
1. M.D. Birkett, M.J.T. Gambino, Estimation of pulp kappa number with near-infrared spectroscopy. Tappi J. 72(9), 193–197 (1989)
2. E. Sjostrom, Wood Chemistry: Fundamentals and Applications (Gulf Professional Publishing,
1993)
3. A.M.M. Alves, R.F.S. Simões, C.A. Santos, B.M. Potts, J. Rodrigues, M. Schwanninger,
Determination of Eucalyptus globulus wood extractives content by near infrared-based partial
least squares regression models: comparison between extraction procedures. J. Near Infrared
Spectrosc. 20(2), 275–285 (2012)
4. D.B. Easty, S.A. Berben, F.A. DeThomas, P.J. Brimmer, Near-infrared spectroscopy for the
analysis of wood pulp: quantifying hardwood-softwood mixtures and estimating lignin content.
Tappi J. 73(10), 257–261 (1990)
5. J.A. Wright, M.D. Birkett, M.J.T. Gambino, Prediction of pulp yield and cellulose content from
wood samples using near infrared reflectance spectroscopy. Tappi J. 73(8), 164–166 (1990)
6. L. Wallbäcks, U. Edlund, B. Norden, I. Berglund, Multivariate characterization of pulp using
solid-state 13C NMR, FTIR, and NIR. Tappi J. 74(10), 201–206 (1991)
7. A.R. Da Silva, T.C.M. Pastore, J.W.B. Braga, F. Davrieux, E.Y.A. Okino, V.T.R. Coradin,
J.A.A. Camargos, A.G.S. Do Prado, Assessment of total phenols and extractives of mahogany
wood by near infrared spectroscopy (NIRS). Holzforschung 67(1), 1–8 (2013)
8. W. He, H. Hu, Rapid prediction of different wood species extractives and lignin content using
near infrared spectroscopy. J. Wood Chem. Technol. 33(1), 52–64 (2013)
9. C. Lepoittevin, J.P. Rousseau, A. Guillemin, C. Gauvrit, F. Besson, F. Hubert, D. Da Silva Perez,
L. Harvengt, C. Plomion, Genetic parameters of growth, straightness and wood chemistry traits
in Pinus pinaster. Ann. For. Sci. 68(4), 873–884 (2011)
10. B. Üner, ˙ I. Karaman, H. Tanrıverdi, D. Özdemir, Determination of lignin and extractive content
of Turkish Pine (Pinus brutia Ten.) trees using near infrared spectroscopy and multivariate
calibration. Wood Sci. Technol. 45(1), 121–134 (2011)
11. S. Tsuchikawa, H. Kobori, A review of recent application of near infrared spectroscopy to
wood science and technology. J. Wood Sci. 61(3), 213–220 (2015)
12. K. Watanabe, S.D. Mansfield, S. Avramidis, Application of near-infrared spectroscopy for
moisture-based sorting of green hem-fir timber. J. Wood Sci. 57(4), 288–294 (2011)
13. M. Defo, A.M. Taylor, B. Bond, Determination of moisture content and density of fresh-sawn
red oak lumber by near infrared spectroscopy. For. Prod. J. 57(5), 68–72 (2007)
14. V.T.H. Tham, T. Inagaki, S. Tsuchikawa, 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 (2018)