Kappa number prediction of Acacia melanoxylon unbleached kraft pulps using NIR-PLSR models with narrow interval of variation

Bibliographic Details
Main Author: Santos, António J.
Publication Date: 2014
Other Authors: Anjos, O., Simões, Rogério, Rodrigues, José Carlos, Pereira, Helena
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.11/2537
Summary: A total of 120 Acacia melanoxylon R. Br. (Australian blackwood) stem discs, belonging to 20 trees from four sites in Portugal, were used in this study. The samples were kraft pulped under standard identical conditions targeted to a Kappa number of 15. A Near Infrared (NIR) partial least squares regression (PLSR) model was developed for the Kappa number prediction using 75 pulp samples with a narrow Kappa number variation range of 10 to 17. Very good correlations between NIR spectra of A. melanoxylon pulps and Kappa numbers were obtained. Besides the raw spectra, also pre-processed spectra with ten methods were used for PLS analysis (cross validation with 48 samples), and a test set validation was made with 27 samples. The first derivative spectra in the wavenumber range from 6110 to 5440 cm-1 yielded the best model with a root mean square error of prediction of 0.4 units of Kappa number, a coefficient of determination of 92.1%, and two PLS components, with the ratios of performance to deviation (RPD) of 3.6 and zero outliers. The obtained NIR-PLSR model for Kappa number determination is sufficiently accurate to be used in screening programs and in quality control.
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spelling Kappa number prediction of Acacia melanoxylon unbleached kraft pulps using NIR-PLSR models with narrow interval of variationAcacia melanoxylonKappa numberNIRRPDA total of 120 Acacia melanoxylon R. Br. (Australian blackwood) stem discs, belonging to 20 trees from four sites in Portugal, were used in this study. The samples were kraft pulped under standard identical conditions targeted to a Kappa number of 15. A Near Infrared (NIR) partial least squares regression (PLSR) model was developed for the Kappa number prediction using 75 pulp samples with a narrow Kappa number variation range of 10 to 17. Very good correlations between NIR spectra of A. melanoxylon pulps and Kappa numbers were obtained. Besides the raw spectra, also pre-processed spectra with ten methods were used for PLS analysis (cross validation with 48 samples), and a test set validation was made with 27 samples. The first derivative spectra in the wavenumber range from 6110 to 5440 cm-1 yielded the best model with a root mean square error of prediction of 0.4 units of Kappa number, a coefficient of determination of 92.1%, and two PLS components, with the ratios of performance to deviation (RPD) of 3.6 and zero outliers. The obtained NIR-PLSR model for Kappa number determination is sufficiently accurate to be used in screening programs and in quality control.Repositório Científico do Instituto Politécnico de Castelo BrancoSantos, António J.Anjos, O.Simões, RogérioRodrigues, José CarlosPereira, Helena2014-09-25T16:28:18Z20142014-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.11/2537eng1930-2126info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-26T14:18:20Zoai:repositorio.ipcb.pt:10400.11/2537Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T21:32:50.500110Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Kappa number prediction of Acacia melanoxylon unbleached kraft pulps using NIR-PLSR models with narrow interval of variation
title Kappa number prediction of Acacia melanoxylon unbleached kraft pulps using NIR-PLSR models with narrow interval of variation
spellingShingle Kappa number prediction of Acacia melanoxylon unbleached kraft pulps using NIR-PLSR models with narrow interval of variation
Santos, António J.
Acacia melanoxylon
Kappa number
NIR
RPD
title_short Kappa number prediction of Acacia melanoxylon unbleached kraft pulps using NIR-PLSR models with narrow interval of variation
title_full Kappa number prediction of Acacia melanoxylon unbleached kraft pulps using NIR-PLSR models with narrow interval of variation
title_fullStr Kappa number prediction of Acacia melanoxylon unbleached kraft pulps using NIR-PLSR models with narrow interval of variation
title_full_unstemmed Kappa number prediction of Acacia melanoxylon unbleached kraft pulps using NIR-PLSR models with narrow interval of variation
title_sort Kappa number prediction of Acacia melanoxylon unbleached kraft pulps using NIR-PLSR models with narrow interval of variation
author Santos, António J.
author_facet Santos, António J.
Anjos, O.
Simões, Rogério
Rodrigues, José Carlos
Pereira, Helena
author_role author
author2 Anjos, O.
Simões, Rogério
Rodrigues, José Carlos
Pereira, Helena
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico de Castelo Branco
dc.contributor.author.fl_str_mv Santos, António J.
Anjos, O.
Simões, Rogério
Rodrigues, José Carlos
Pereira, Helena
dc.subject.por.fl_str_mv Acacia melanoxylon
Kappa number
NIR
RPD
topic Acacia melanoxylon
Kappa number
NIR
RPD
description A total of 120 Acacia melanoxylon R. Br. (Australian blackwood) stem discs, belonging to 20 trees from four sites in Portugal, were used in this study. The samples were kraft pulped under standard identical conditions targeted to a Kappa number of 15. A Near Infrared (NIR) partial least squares regression (PLSR) model was developed for the Kappa number prediction using 75 pulp samples with a narrow Kappa number variation range of 10 to 17. Very good correlations between NIR spectra of A. melanoxylon pulps and Kappa numbers were obtained. Besides the raw spectra, also pre-processed spectra with ten methods were used for PLS analysis (cross validation with 48 samples), and a test set validation was made with 27 samples. The first derivative spectra in the wavenumber range from 6110 to 5440 cm-1 yielded the best model with a root mean square error of prediction of 0.4 units of Kappa number, a coefficient of determination of 92.1%, and two PLS components, with the ratios of performance to deviation (RPD) of 3.6 and zero outliers. The obtained NIR-PLSR model for Kappa number determination is sufficiently accurate to be used in screening programs and in quality control.
publishDate 2014
dc.date.none.fl_str_mv 2014-09-25T16:28:18Z
2014
2014-01-01T00:00:00Z
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