Multivariate calibration models using NIR spectroscopy on pulp and paper industrial applications
✍ Scribed by Henrik Antti; Michael Sjöström; Lars Wallbäcks
- Publisher
- John Wiley and Sons
- Year
- 1996
- Tongue
- English
- Weight
- 604 KB
- Volume
- 10
- Category
- Article
- ISSN
- 0886-9383
No coin nor oath required. For personal study only.
✦ Synopsis
A goal for the pulp and paper industry is to get a fast and reliable charactenzation of raw matenals as wood and pulp compositions. One possibility for this is near infrared reflectance (NIR) spectroscopy combined with multivariate analysis. In the first part of this study the possibiiity to make predictions of mixtures of wood chips from three different wood species (Swedish pine, Swedish spruce and Polish pine) is investigated based on NIR spectroscopy. Mixture design and Partial least squares projections to latent structures (PLS) were used for the multivariate calibration modeling. The calculated model was validated both intemally and with an extemal test set. "he result was a PLS model with a Q' = 0.91 according to cross-validation and good prediction of the test set objects, Q",,,,, = 0.78.
In the second part NIR spectroscopy is used to charactenze a series of pulp samples. The pulps were also characterized by seventeen traditionally measured pulp properties. PLS was used for the calibration model and intemal as well as extemal validation were done. The resulting PLS model for the 17 pulp properties gave an overall QZ = 0.61 according to cross-validation. Predictions of the test set objects show that most of the properties are well descnbed by the model.