NIR Analyses

The Value Proposition

Growing eucalypts for pulp depends on growing merchantable volume as quickly as possible. The mass of pulp produced from each unit area of forest depends on

  • Merchantable volume
  • Wood density
  • Pulp yield

​Pulp yield is the proportion of biomass that remains at the end of the pulping process [1].

​For a pulp mill processing 4 million green tonnes of wood per year, an increase in Kraft pulp yield (KPY) of 1% equates to ~20,000 tonnes of extra pulp for no additional growing or processing costs.

Unlike volume and density, KPY has been slow and expensive to measure. Consequently both forest growers and pulp manufacturers have had limited opportunity to include it in managing their value chain.

​NIR prediction of KPY is inexpensive, requires only small (1 gram or more) samples.

Low cost Pulp Yield assessment

Near Infra Red (NIR) spectroscopy is widely used in agriculture and manufacturing. Application to KPY measurement  spans two decades of R&D, demonstrating its ability to provide precise measurements of KPY in samples as small as 0.5 gm. 

Numerous studies have shown NIR offers

​Low cost measurement

  • Expanded application of traditional analyses
  • Efficient ranking of trees and sites
  • Precise KPY values that are highly heritable

NIR can be used to measure a range of commercially valuable wood properties

  • Pulp Yield [2–6]
  • Density  [2]
  • Dry Matter content [7]
  • Stiffness [8,9]
  • Microfibril Angle [8]
  • Non-recoverable collapse [8,9]

The biggest issue is trusting the values that NIR measurement generates. 

Consequently any application of NIR requires a means of quality control until such time as the user has confidence that the values are precise.  This can only occur through repeated experience.

The development of NIR calibrations is therefore an iterative process.  Cycles of development and validation are required until precise and accurate predictions are consistently obtained.  This process applies to both the type of NIR application being developed and the individual wood property being measured.

Near Infra Red spectroscopy is a multi-variate statistical approach to obtain qualitative and/or quantitative information about the properties of an organic substance based on its absorption of light in the near infra red range (typically 1000 – 2500 nm)

References

1. Downes GM, Hudson IL, Raymond CA, Dean GH, Michell AJ, Schimleck LR, et al. Sampling Plantation Eucalypts for Wood and Fibre Properties [Internet]. CSIRO Publishing; 1997. Available from: http://dx.doi.org/10.1071/9780643105287
2. Downes GM, Meder R, Bond H, Ebdon N, Hicks C, Harwood C. Measurement of cellulose content, Kraft pulp yield and basic density in eucalypt woodmeal using multisite and multispecies near infra-red spectroscopic calibrations. Southern Forests: a Journal of Forest Science [Internet]. 2011;73:181–6. Available from: http://dx.doi.org/10.2989/20702620.2011.639489
3. Downes G, Meder R, Harwood C. A Multi-Site, Multi-Species near Infrared Calibration for the Prediction of Cellulose Content in Eucalypt Woodmeal. Journal of Near Infrared Spectroscopy [Internet]. 2010;18:381–7. Available from: http://dx.doi.org/10.1255/jnirs.910
4. Downes GM, Meder R, Ebdon N, Bond H, Evans R, Joyce K, et al. Radial Variation in Cellulose Content and Kraft Pulp Yield in Eucalyptus Nitens using Near-Infrared Spectral Analysis of Air-Dry Wood Surfaces. Journal of Near Infrared Spectroscopy [Internet]. 2010;18:147–54. Available from: http://dx.doi.org/10.1255/jnirs.875
5. Downes GM, Meder R, Hicks C, Ebdon N. Developing and evaluating a multisite and multispecies NIR calibration for the prediction of Kraft pulp yield in eucalypts. Southern Forests: a Journal of Forest Science [Internet]. 2009;71:155–64. Available from: http://dx.doi.org/10.2989/sf.2009.71.2.11.826
6. Downes GM, Harwood CE, Wiedemann J, Ebdon N, Bond H, Meder R. Radial variation in Kraft pulp yield and cellulose content in Eucalyptus globulus wood across three contrasting sites predicted by near infrared spectroscopy. Canadian Journal of Forest Research [Internet]. 2012;42:1577–86. Available from: http://dx.doi.org/10.1139/x2012-083
7. Downes G, Meder R, Ebdon N, Menz D, Hicks C. Quality Assessment of Australian woodchips Project 5: Field-based application of acoustic velocity and NIR as predictors of pulp quality across site and species. The Commonwealth Scientific and Industrial Research Organisation [Internet]. 2009; Available from: http://rgdoi.net/10.13140/RG.2.2.36601.19046
8. Downes GM, Touza M, Harwood C, Wentzel-Vietheer M. NIR detection of non-recoverable collapse in sawn boards of Eucalyptus globulus. European Journal of Wood and Wood Products [Internet]. 2014;72:563–70. Available from: http://dx.doi.org/10.1007/s00107-014-0813-9
9. Wentzel-Vietheer M, Washusen R, Downes G, Harwood C, Ebdon N, Ozarska B, et al. Prediction of non-recoverable collapse in Eucalyptus globulus from near infrared scanning of radial wood samples. European Journal of Wood and Wood Products [Internet]. 2013;71:755–68. Available from: http://dx.doi.org/10.1007/s00107-013-0735-y