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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Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro
2019
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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 |
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Terra,Teddy Diogo Rios Vieira,Renato da Silva Baraúna,Edy Eime Pereira |
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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. |
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Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro |
publishDate |
2019 |
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http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872019000100133 |
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1756439344956047360 |