Non-destructive prediction of the properties of forest biomass for chemical and bioenergy applications using near infrared spectroscopy

Journal of Near Infrared Spectroscopy

Volumn 23, Issue 2, 2015, Pages 93-102

  Acquah, Gifty E ^a   Via, Brian K ^a   Fasina, Oladiran O ^b   Eckhardt, Lori G ^a  

^a AUBURN UNIVERSITY   (United States)

^b AUBURN UNIVERSITY   (United States)

Author keywords

Chemical composition; Energy value; Heterogeneous forest biomass; Near infrared spectroscopy; Partial least squares regression; Proximate analysis

Indexed keywords

BIOCONVERSION; CHEMICAL ANALYSIS; FEEDSTOCKS; FORECASTING; FORESTRY; INFRARED DEVICES; LEAST SQUARES APPROXIMATIONS; NEAR INFRARED SPECTROSCOPY;

CHEMICAL COMPOSITIONS; ENERGY VALUE; FOREST BIOMASS; PARTIAL LEAST SQUARES REGRESSION; PROXIMATE ANALYSIS;

BIOMASS;

EID: 84931436461     PISSN: 09670335     EISSN: 17516552     Source Type: Journal    
DOI: 10.1255/jnirs.1153     Document Type: Article

References (35)

1. US Department of Energy. Billion-Ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry, Leads R.D. Perlack and B.J. Stokes, ORNL/TM-2011/224. Oak Ridge National Laboratory, Oak Ridge, TN (2011).
2. th Council on Forest Engineering (June 2011). https://www.cirrelt.ca/cofe2011/proceedings/17-Greene-COFE2011-Final.pdf
3. G.E. Acquah, Characterization of Forest Harvest Residue from the Great Lakes-St Lawrence Forests of South-Eastern Ontario. MSc Thesis, Faculty of Forestry, University of Toronto, Canada (2010).
4. H. Mark and B. Campbell, An Introduction to Near Infrared Spectroscopy and Associated Chemometrics (2008). http://www.idrc-chambersburg.org/cnirs/pdfs/nirand-chemometrics.pdf
5. G. Reich, "Near infrared spectroscopy and imaging: basic principles and pharmaceutical applications", Adv. Drug Deliv. Rev. 57, 1109-1143 (2005). doi: http://dx.doi.org/10.1016/j.addr.2005.01.020
6. K. Varmuza and P. Filzmoser, Introduction to Multivariate Statistical Analysis in Chemometrics. Taylor & Francis, Boca Raton, FL (2009). doi: http://dx.doi.org/10.1201/9781420059496
7. M. Defo, A.M. Taylor and B. Bond, "Determination of moisture and density of fresh sawn red oak lumber by near infrared spectroscopy", Forest Prod. J. 57, 68-72 (2007).
8. T.A. Lestander and C. Rhen, "Multivariate NIR spectroscopy models for moisture, ash and calorific content in biofuels using bi-orthogonal partial least squares regression", Analyst 130, 1182-1189 (2005). doi: http://dx.doi.org/10.1039/b500103j
9. P. Cooper, D. Jeremic, S. Radivojevic, Y.T. Ung and F. Leblon, "Potential of near-infrared spectroscopy to characterize wood products", Can. J. For. Res. 41, 2150-2157 (2011). doi: http://dx.doi.org/10.1139/x11-088
10. N.S.A. Derkyi,B. Adu-Amankwa, D. Sekyereand N.A. Darkwa, "Rapid prediction of extractives and polyphenolic contents in Pinus caribaea bark using near infrared reflectance spectroscopy", Int. J. Appl. Sci. 2, 1 (2011).
11. K. Nkansah, B. Dawson-Andoh and J. Slahor, "Rapid characterization of biomass using near infrared spectroscopy coupled with multivariate data analysis: Part 1 yellow-poplar (Liriodendron tulipifera L.)", Bioresour. Technol. 101, 4570-4576 (2010). doi: http://dx.doi.org/10.1016/j.biortech.2009.12.046
12. R. Sykes, B. Li, G. Hodge, B. Goldfarb, J. Kadla and H.-M. Chang, "Prediction of loblolly pine wood properties using transmittance near-infrared spectroscopy", Can. J. For. Res. 35, 2423-2431 (2005). doi: http://dx.doi.org/10.1139/x05-161
13. N. Gierlinger, M. Schwanninger, B. Hinterstoisser and R. Wimmer, "Rapid determination of the heartwood extractives in Larix sp. by means of Fourier Transform near infrared spectroscopy", J. Near Infrared Spectrosc. 10, 203-214 (2002). doi: http://dx.doi.org/10.1255/jnirs.336
14. F.S. Poke and C.A. Raymond, "Predicting extractives, lignin, and cellulose contents using near infrared spectroscopy on solid wood in Eucalyptus globulus", J. Wood Chem. Technol. 26, 2 (2006), 187-199. doi: http://dx.doi.org/10.1080/02773810600732708
15. W. Jiang, G. Han, B.K. Via, M. Tu, W. Liu and O. Fasina, "Rapid assessment of coniferous biomass lignin-carbohydrates with near-infrared spectroscopy", Wood Sci Technol. 48, 1 (2014), 109-122. doi: http://dx.doi.org/10.1007/s00226-013-0590-3
16. P.R.G. Hein, J.T. Lima and G. Chaix, "Effects of sample preparation on NIR spectroscopic estimation of chemical properties of Eucalyptus urophylla S.T. Blake wood", Holzforschung, 64, 45-54 (2010). doi: http://doi.org/10.1515/hf.2010.011
17. B.K. Via, T. Shupe, L. Groom, M. Stine and C. So, "Multivariate modeling of density, strength and stiffness from near infrared spectra for mature, juvenile and pith wood of longleaf pine (Pinus palustris)", J. Near Infrared Spectrosc. 11, 365-378 (2003). doi: http://dx.doi.org/10.1255/jnirs.388
18. P.R.G. Hein, B. Clair, L. Brancheriau and G. Chaix, "Predicting microfibril angle in Eucalyptus wood from different wood faces and surface qualities using near infrared spectra", J. Near Infrared Spectrosc. 18, 6 (2010), 455-464. doi: http://dx.doi.org/10.1255/jnirs.905
19. J.P. McLean, G. Jin, M. Brennan, M.K. Nieuwoudt and P.J. Harris, "Using NIR and ATR-FTIR spectroscopy to rapidly detect compression wood in Pinus radiata", Can. J. For. Res. 44, 820-830 (2014). doi: http://dx.doi.org/10.1139/cjfr-2013-0329
20. G.M. Downes, F. Catela and R. Meder, "Developing and evaluating a multisite and multispecies NIR calibration for the prediction of Kraft pulp yield in eucalypts", South. For. 71, 2 (2009), 155-164. doi: http://dx.doi.org/10.2989/sf.2009.71.2.11.826
21. C. So and T.L. Eberhardt, "Chemical and calorific characterization of longleaf pine using near infrared spectroscopy", J. Near Infrared Spectrosc. 18, 417-423 (2010). doi: http://dx.doi.org/10.1255/jnirs.889
22. R. Conner and A. Hartsell, "Forest area and conditions", in Southern Forest Resource Assessment, Ed by D. Wear and J.G. Greis. General Technical Report SRS-53, USDA Forest Service, Southern Research Station, Asheville, NC 635 pp. 2002.
23. B.K. Via, C. Zhou, G. Acquah, W. Jiang and L. Eckhardt, "Near infrared spectroscopy calibration for wood chemistry : which chemometric technique is the best for prediction and interpretation?", Sensors, 14, 13532-13547 (2014). doi: http://dx.doi.org/10.3390/s140813532
24. B. Mevik and H.R. Cederkvist, "Mean squared error of prediction (MSEP) estimates for principal component regression (PCR) and partial least squares regression (PLSR)", J. Chemom. 18, 422-429 (2004). doi: http://dx.doi.org/10.1002/cem.887
25. S.S. Kelley, T.G. Rials, R. Snell, L.H. Groom and A. Sluiter, "Use of near infrared spectroscopy to measure the chemical and mechanical properties of solid wood", Wood Sci. Technol. 38, 257-276 (2004). doi: http://dx.doi.org/10.1007/s00226-003-0213-5
26. B.K. Via, S. Adhikari and S. Taylor, "Modeling for proximate analysis and heating value of torrefied biomass with vibration spectroscopy", Bioresour. Technol. 133, 1-8 (2013). doi: http://dx.doi.org/10.1016/j.biortech.2013.01.108
27. P.D. Jones, L.R. Schimleck, G.F. Peter, R.F. Daniels and A. Clark (III), "Nondestructive estimation of wood chemical composition of sections of radial wood strips by diffuse reflectance near infrared spectroscopy", Wood Sci. Technol. 40, 709-720 (2006). doi: http://dx.doi.org/10.1007/s00226-006-0085-6
28. M.A. Sanderson, F. Agblevor, M. Collins and D.K. Johnson, "Compositional analysis of biomass feed-stocks by near infrared reflectance spectroscopy", Biomass Bioeng. 11, 5, 365-370 (1996). doi: http://dx.doi.org/10.1016/S0961-9534(96)00039-6
29. M. Schwanninger, J. Rogrigues and K. Fackler, "A review of band assignments in near infrared spectra of wood and wood components", J. Near Infrared Spectrosc. 19, 287-308 (2011). doi: http://dx.doi.org/10.1255/jnirs.955
30. P. Williams, "Near Infrared Technology - Getting the Best Out of Light", a Short Course in the Practical Implementation of Near Infrared Spectroscopy for the User. PDK Grain, Nanaimo, British Columbia, Canada (2004).
31. B.K. Via, "Characterization and evaluation of wood strand composite load capacity with near infrared spectroscopy", Mater. Struct. 2013, doi: 10.1617/s11527-013-0018-4. doi: http://dx.doi.org/10.1617/s11527-013-0018-4
32. th International Convention of Society of Wood Science and Technology, 27-31 August 2012, Beijing, China.
33. K. Ono, M. Hiraide and M. Amari, "Determination of lignin, holocellulose, and organic solvent extractives in fresh leaf, litterfall, and organic material on forest floor using near-infrared reflectance spectroscopy", J. For. Res. 8, 191-198 (2003). doi: http://dx.doi.org/10.1007/s10310-003-0026-2
34. D. Gillon, C. Hernando, J-C Valette, and R. Joffre, "Fast estimation of the calorific values of forest fuels by near-infrared reflectance spectroscopy", Can. J. For. Res. 27, 760-765 (1997). doi: http://dx.doi.org/10.1139/x97-021
35. W.R. Windham, N.S. Hill and J.A. Stuedemann, "Ash in forage, esophageal, and fecal samples analyzed using near-infrared reflectance spectroscopy", Crop Sci. 31, 1345-1349 (1991). doi: http://dx.doi.org/10.2135/cropsci1991.0011183X003100050053x