Prediction of Properties of Sclerolobium paniculatum and Qualea grandiflora Charcoal

ABSTRACT There is a lack of techniques for the rapid and accurate determination of wood quality for charcoal production with good energy characteristics. The association of NIR spectroscopy and important charcoal parameters allows the prediction of these characteristics. This is a fast method that does not require sample preparation before the reading. The spectral readings were performed with solid and ground samples, and presented the second best representation of the evaluated parameters. Data went was adjusted to correct for variations that could occur during the spectra reading. The treatment with the best results was the normal transformation of variation. The evaluated spectra were able to explain 77% of the data for the variable gravimetric yield, 88% for volatile materials content and 86% for fixed carbon content.

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Main Authors: Terra,Teddy Diogo Rios, Vieira,Renato da Silva, Baraúna,Edy Eime Pereira
Format: Digital revista
Language:English
Published: Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro 2019
Online Access:http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872019000100133
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spelling oai:scielo:S2179-808720190001001332019-02-11Prediction of Properties of Sclerolobium paniculatum and Qualea grandiflora CharcoalTerra,Teddy Diogo RiosVieira,Renato da SilvaBaraúna,Edy Eime Pereira NIR spectroscopy wood quality biomass energy ABSTRACT There is a lack of techniques for the rapid and accurate determination of wood quality for charcoal production with good energy characteristics. The association of NIR spectroscopy and important charcoal parameters allows the prediction of these characteristics. This is a fast method that does not require sample preparation before the reading. The spectral readings were performed with solid and ground samples, and presented the second best representation of the evaluated parameters. Data went was adjusted to correct for variations that could occur during the spectra reading. The treatment with the best results was the normal transformation of variation. The evaluated spectra were able to explain 77% of the data for the variable gravimetric yield, 88% for volatile materials content and 86% for fixed carbon content.info:eu-repo/semantics/openAccessInstituto de Florestas da Universidade Federal Rural do Rio de JaneiroFloresta e Ambiente v.26 n.1 20192019-01-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872019000100133en10.1590/2179-8087.007216
institution SCIELO
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country Brasil
countrycode BR
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region America del Sur
libraryname SciELO
language English
format Digital
author Terra,Teddy Diogo Rios
Vieira,Renato da Silva
Baraúna,Edy Eime Pereira
spellingShingle Terra,Teddy Diogo Rios
Vieira,Renato da Silva
Baraúna,Edy Eime Pereira
Prediction of Properties of Sclerolobium paniculatum and Qualea grandiflora Charcoal
author_facet Terra,Teddy Diogo Rios
Vieira,Renato da Silva
Baraúna,Edy Eime Pereira
author_sort Terra,Teddy Diogo Rios
title Prediction of Properties of Sclerolobium paniculatum and Qualea grandiflora Charcoal
title_short Prediction of Properties of Sclerolobium paniculatum and Qualea grandiflora Charcoal
title_full Prediction of Properties of Sclerolobium paniculatum and Qualea grandiflora Charcoal
title_fullStr Prediction of Properties of Sclerolobium paniculatum and Qualea grandiflora Charcoal
title_full_unstemmed Prediction of Properties of Sclerolobium paniculatum and Qualea grandiflora Charcoal
title_sort prediction of properties of sclerolobium paniculatum and qualea grandiflora charcoal
description ABSTRACT There is a lack of techniques for the rapid and accurate determination of wood quality for charcoal production with good energy characteristics. The association of NIR spectroscopy and important charcoal parameters allows the prediction of these characteristics. This is a fast method that does not require sample preparation before the reading. The spectral readings were performed with solid and ground samples, and presented the second best representation of the evaluated parameters. Data went was adjusted to correct for variations that could occur during the spectra reading. The treatment with the best results was the normal transformation of variation. The evaluated spectra were able to explain 77% of the data for the variable gravimetric yield, 88% for volatile materials content and 86% for fixed carbon content.
publisher Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro
publishDate 2019
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872019000100133
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