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Prediction of wood species and pulp brightness from roundwood measurements
Umeå University, Faculty of Science and Technology, Department of Chemistry.
2005 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis presents a number of studies, where a multivariate approach was taken to construct models that predict wood species and thermo mechanical pulp brightness from roundwood of Norway spruce and Scots pine. The first and second studies produced multivariate prediction models for wood species from the bark of spruce and pine. These models can be used for wood species classification and would replace the manual log assessment that takes place today. Principal Component Analysis, PCA, and Partial least squares projections to Latent Structures, PLS, were used to predict the wood species from multivariate measurements recorded from the bark of spruce and pine. Two different kinds of measurements were employed, near-infrared spectroscopy and digital imaging. Both methods showed that it was possible to predict the wood species with a high accuracy.

The third and fourth studies of the thesis are related to the wood storage of roundwood and the deterioration of wood that occurs during the storage. The third study used an experimental design with five storage factors that provided different conditions for the analysed wood. The experimental design made it possible to identify the factors and the interaction between factors, which were important for the ISO brightness of peroxide and dithionite bleached thermo mechanical pulp, TMP. The final study of the thesis used NIR spectroscopy for predicting the ISO brightness of bleached TMP. Spectra recorded from stored wood were used to construct PLS prediction models.

Place, publisher, year, edition, pages
Umeå: Kemi , 2005. , 72 p.
Keyword [en]
Design of Experiments, ISO brightness, Multivariate Image Analysis, Multivariate Modelling, NIR spectroscopy, Norway spruce, PCA, PLS, Roundwood, Scots pine
National Category
Organic Chemistry
Identifiers
URN: urn:nbn:se:umu:diva-605ISBN: 91-7305-959-9 OAI: oai:DiVA.org:umu-605DiVA: diva2:143949
Public defence
2005-10-28, KB3A9, KBC, Umeå Universitet, SE-90187, Umeå, 10:00 (English)
Opponent
Supervisors
Available from: 2005-10-06 Created: 2005-10-06 Last updated: 2011-03-17Bibliographically approved
List of papers
1. Classification of the softwood species spruce and pine using near-infrared reflectance measurements on bark combined with multivariate data analysis
Open this publication in new window or tab >>Classification of the softwood species spruce and pine using near-infrared reflectance measurements on bark combined with multivariate data analysis
(English)Manuscript (Other academic)
National Category
Chemical Sciences
Identifiers
urn:nbn:se:umu:diva-4723 (URN)
Available from: 2005-10-06 Created: 2005-10-06 Last updated: 2013-03-14Bibliographically approved
2. Pine and spruce roundwood species classification using multivariate image analysis on bark
Open this publication in new window or tab >>Pine and spruce roundwood species classification using multivariate image analysis on bark
2005 (English)In: Holzforschung, ISSN 0018-3830, Vol. 59, no 6, 689-695 p.Article in journal (Refereed) Published
Abstract [en]

Wood discs from 67 pine and 79 spruce logs were collected from a forest clearing. Three different 24-bit red-green-blue (RGB) images were acquired from the radial surface of each disc. The first image contained bark, the second image was a mixture of bark and wood surface, and the third image consisted only of wood surface. The image texture was compressed into vectors of Fourier-transformed wavelet coefficients. These were assembled in matrices and analysed by principal component analysis (PCA) and partial least-squares projections to latent structures (PLS). Classification using Fourier-transformed wavelet scales showed that the wood species could be predicted with 90% accuracy. A thorough examination of this classification showed that the predicting power of these models was mostly due to wavelet scales that represented the mean value of each colour channel. The prediction accuracy that could be obtained from coefficients representing image texture was generally low. The use of grey-level co-occurrence matrices prior to the wavelet transformation showed, however, that it is possible to classify the wood species of pine and spruce with an accuracy approaching 100%.

Place, publisher, year, edition, pages
Berlin: Walter de Gruyter, 2005
Keyword
bark, co-occurrence matrix, multivariate image analysis, partial least squares projection to latent structures (PLS), pine, spruce, wavelet, wood species
National Category
Chemical Sciences
Identifiers
urn:nbn:se:umu:diva-4724 (URN)10.1515/HF.2005.110 (DOI)
Available from: 2005-10-06 Created: 2005-10-06 Last updated: 2013-03-14Bibliographically approved
3. The effect of designed wood storage on the brightness of bleached and unbleached thermo mechanical pulp
Open this publication in new window or tab >>The effect of designed wood storage on the brightness of bleached and unbleached thermo mechanical pulp
Show others...
2003 (English)In: Nordic Pulp & Paper Research Journal, Vol. 18, no 4, 369-76 p.Article in journal (Refereed) Published
Abstract [en]

60 Norway Spruce (Picea abies) logs were stored in climate chambers for 14 weeks in order to investigate the effect of wood storage on the brightness of thermo mechanical pulp. The storage conditions were altered according to an experimental design comprised of five factors; light, watering, temperature, tree growth and debarking. Wood samples were collected during the storage period and refined into thermo mechanical pulp. ISO brightness values were measured for the unbleached, the dithionite bleached and the hydrogen peroxide bleached thermo mechanical pulp samples that were refined from the stored wood. The decrease in ISO brightness after 14 weeks of wood storage was significant for some of the samples bleached with dithionite. It was found that the interaction between watering and light had a significant negative effect on the brightness of the unbleached and dithionite bleached samples. The samples bleached with hydrogen peroxide generally showed a more consistent ISO brightness. Only watering and temperature had a significant effect on the brightness of peroxide bleached thermo, mechanical pulp.

National Category
Chemical Sciences
Identifiers
urn:nbn:se:umu:diva-9923 (URN)10.3183/NPPRJ-2003-18-04-p369-376 (DOI)
Available from: 2008-05-23 Created: 2008-05-23 Last updated: 2013-03-14Bibliographically approved
4. Prediction of thermo mechanical pulp brightness using NIR spectroscopy on wood raw material
Open this publication in new window or tab >>Prediction of thermo mechanical pulp brightness using NIR spectroscopy on wood raw material
2005 (English)In: Paperi ja puu, ISSN 0031-1243, Vol. 87, no 2, 102-109 p.Article in journal (Refereed) Published
Abstract [en]

Partial Least Squares regression to latent structures was used to find a correlation between near-infrared reflectance spectra of samples of milled Norway Spruce (Picea abies) and ISO brightness of bleached thermo mechanical pulp. Logs of spruce were stored in climate chambers with different conditions for 14 weeks. A factorial design based on five variables was constructed to control the storage and to provide different brightness properties of the stored spruce logs. Wood samples were collected during the storage and they were analysed with near-infrared reflectance spectroscopy and later refined to thermo mechanical pulp. The pulp was bleached with both hydrogen peroxide and sodium dithionite. The ISO brightness of the bleached pulp was correlated to the near-infrared spectra of the untreated samples using Partial Least Squares regression to latent structures. The modelling showed that it is possible to predict the ISO brightness of bleached thermo mechanical pulp from near-infrared spectra of original wood raw material.

Place, publisher, year, edition, pages
Helsinki: Suomen Paperi- ja Puutavaralehti Oy, 2005
Keyword
near-infrared, spectroscopy, principal component analysis, partial least squares regression to latent variables, thermo mechanical pulp, ISO brightness
National Category
Chemical Sciences
Identifiers
urn:nbn:se:umu:diva-13237 (URN)
Available from: 2007-05-07 Created: 2007-05-07 Last updated: 2013-03-14Bibliographically approved

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