Applicable analytical methods for the determination of solid impurities content in raw sugarcane
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Tipo de documento: | Tese |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/193319 |
Resumo: | The introduction of sugarcane stalks free of solid impurities in the sugar and ethanol manufacturing system is the ideal situation for sugar and alcohol mills. The solid impurities are mainly related to the presence of green and dry leaves and, also of soil in the raw material, sugar cane However, this type of material is inevitably introduced into the process during the harvest. The presence of solid impurities in the manufacturing system of the sugarcane mills increases the costs and steps in the production of sugar and ethanol. Thus, the aim of this thesis study was to identify which chemical elements could be considered characteristic, such as a fingerprint of solid impurities, as well as to develop models to classify and estimate different levels of impurities in sugarcane. In chapter 1, an analytical method was developed to identify the chemical elements in samples with levels of impurities between 0 and 10% (g/100g) using laser-induced breakdown spectroscopy (LIBS) and the principal component analysis (PCA). The chemical elements Ca, Mg and K were those most related to variations in the levels of solid impurities. In chapter 2, an analytical method was developed using digital images and chemometric techniques to classify the content of sugarcane stalks in the presence of solid impurities. The models had success rates above 97%. In chapter 3, the same data set from the digital images used in chapter 2 was applied, the artificial neural network (ANN) tool. For this case, the sugarcane content was estimated in the presence of solid impurities. The three methods developed showed good rates of precision and accuracy. Besides the applicability present itself possible in view of the absence of analytical methods related of the sugarcane mills process, it must also be considered that the character of simplicity in terms of instrumentation and sample preparation has been achieved. |
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Applicable analytical methods for the determination of solid impurities content in raw sugarcaneMétodos analíticos aplicáveis para a determinação do teor de impurezas sólidas em cana-de-açúcarSugarcaneStrawDigital imagesLaser-induced breakdown spectroscopyChemometricsCana-de-açúcarQuimiometriaImagens digitaisPalhaThe introduction of sugarcane stalks free of solid impurities in the sugar and ethanol manufacturing system is the ideal situation for sugar and alcohol mills. The solid impurities are mainly related to the presence of green and dry leaves and, also of soil in the raw material, sugar cane However, this type of material is inevitably introduced into the process during the harvest. The presence of solid impurities in the manufacturing system of the sugarcane mills increases the costs and steps in the production of sugar and ethanol. Thus, the aim of this thesis study was to identify which chemical elements could be considered characteristic, such as a fingerprint of solid impurities, as well as to develop models to classify and estimate different levels of impurities in sugarcane. In chapter 1, an analytical method was developed to identify the chemical elements in samples with levels of impurities between 0 and 10% (g/100g) using laser-induced breakdown spectroscopy (LIBS) and the principal component analysis (PCA). The chemical elements Ca, Mg and K were those most related to variations in the levels of solid impurities. In chapter 2, an analytical method was developed using digital images and chemometric techniques to classify the content of sugarcane stalks in the presence of solid impurities. The models had success rates above 97%. In chapter 3, the same data set from the digital images used in chapter 2 was applied, the artificial neural network (ANN) tool. For this case, the sugarcane content was estimated in the presence of solid impurities. The three methods developed showed good rates of precision and accuracy. Besides the applicability present itself possible in view of the absence of analytical methods related of the sugarcane mills process, it must also be considered that the character of simplicity in terms of instrumentation and sample preparation has been achieved.A introdução de colmos de cana-de-açúcar livres de impurezas sólidas no sistema de fabricação de açúcar e etanol é a situação ideal para as usinas sucroalcooleiras. As impurezas sólidas estão relacionadas principalmente com a presença de folhas verdes e secas e, também de solo na matéria-prima, cana-de-açúcar. No entanto, esse tipo de material é inevitavelmente introduzido no processo, durante a colheita. A presença de impurezas sólidas no sistema de fabricação das usinas de cana-de-açúcar aumenta os custos e acrescenta etapas na produção de açúcar e etanol. Assim, o objetivo deste estudo de tese foi identificar quais elementos químicos poderiam ser considerados característicos, como uma impressão digital das impurezas sólidas, bem como desenvolver modelos para estimar e classificar diferentes níveis de impurezas na cana-de-açúcar. No capítulo 1, foi desenvolvido um método analítico para identificar os elementos químicos em amostras com níveis de impurezas entre 0 e 10% (g/100g) utilizando a laser-induced breakdown spectroscopy (LIBS) e a principal component analysis (PCA). Os elementos químicos Ca, Mg e K foram aqueles mais relacionados às variações dos teores de impurezas sólidas. No capítulo 2, foi desenvolvido um método analítico utilizando imagens digitais e técnicas quimiométricas para classificar o teor de colmos de cana-de-açúcar na presença de impurezas sólidas. Os modelos apresentaram índices de acertos superiores a 97%. No capítulo 3, foi aplicado ao mesmo conjunto de dados provenientes das imagens digitais utilizadas no capítulo 2, a ferramenta artificial neural network (ANN). Para este caso, foi efetuada a estimativa do teor da cana-de-açúcar na presença de impurezas sólidas. Os três métodos desenvolvidos apresentaram bons índices de precisão e exatidão. Além da aplicabilidade se apresentar possível frente à ausência de métodos analíticos relacionados aos processos das usinas, também deve ser considerado que o caráter de simplicidade em termos de instrumentação e preparo das amostras foi atingido.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)001Universidade Estadual Paulista (Unesp)Pereira, Fabíola Manhas Verbi [UNESP]Universidade Estadual Paulista (Unesp)Guedes, Wesley Nascimento [UNESP]2020-08-28T17:57:01Z2020-08-28T17:57:01Z2020-08-06info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfhttp://hdl.handle.net/11449/19331933004030072P857044454736540240000-0002-8117-2108enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESP2023-10-12T06:08:55Zoai:repositorio.unesp.br:11449/193319Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T14:42:26.508335Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Applicable analytical methods for the determination of solid impurities content in raw sugarcane Métodos analíticos aplicáveis para a determinação do teor de impurezas sólidas em cana-de-açúcar |
title |
Applicable analytical methods for the determination of solid impurities content in raw sugarcane |
spellingShingle |
Applicable analytical methods for the determination of solid impurities content in raw sugarcane Guedes, Wesley Nascimento [UNESP] Sugarcane Straw Digital images Laser-induced breakdown spectroscopy Chemometrics Cana-de-açúcar Quimiometria Imagens digitais Palha |
title_short |
Applicable analytical methods for the determination of solid impurities content in raw sugarcane |
title_full |
Applicable analytical methods for the determination of solid impurities content in raw sugarcane |
title_fullStr |
Applicable analytical methods for the determination of solid impurities content in raw sugarcane |
title_full_unstemmed |
Applicable analytical methods for the determination of solid impurities content in raw sugarcane |
title_sort |
Applicable analytical methods for the determination of solid impurities content in raw sugarcane |
author |
Guedes, Wesley Nascimento [UNESP] |
author_facet |
Guedes, Wesley Nascimento [UNESP] |
author_role |
author |
dc.contributor.none.fl_str_mv |
Pereira, Fabíola Manhas Verbi [UNESP] Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Guedes, Wesley Nascimento [UNESP] |
dc.subject.por.fl_str_mv |
Sugarcane Straw Digital images Laser-induced breakdown spectroscopy Chemometrics Cana-de-açúcar Quimiometria Imagens digitais Palha |
topic |
Sugarcane Straw Digital images Laser-induced breakdown spectroscopy Chemometrics Cana-de-açúcar Quimiometria Imagens digitais Palha |
description |
The introduction of sugarcane stalks free of solid impurities in the sugar and ethanol manufacturing system is the ideal situation for sugar and alcohol mills. The solid impurities are mainly related to the presence of green and dry leaves and, also of soil in the raw material, sugar cane However, this type of material is inevitably introduced into the process during the harvest. The presence of solid impurities in the manufacturing system of the sugarcane mills increases the costs and steps in the production of sugar and ethanol. Thus, the aim of this thesis study was to identify which chemical elements could be considered characteristic, such as a fingerprint of solid impurities, as well as to develop models to classify and estimate different levels of impurities in sugarcane. In chapter 1, an analytical method was developed to identify the chemical elements in samples with levels of impurities between 0 and 10% (g/100g) using laser-induced breakdown spectroscopy (LIBS) and the principal component analysis (PCA). The chemical elements Ca, Mg and K were those most related to variations in the levels of solid impurities. In chapter 2, an analytical method was developed using digital images and chemometric techniques to classify the content of sugarcane stalks in the presence of solid impurities. The models had success rates above 97%. In chapter 3, the same data set from the digital images used in chapter 2 was applied, the artificial neural network (ANN) tool. For this case, the sugarcane content was estimated in the presence of solid impurities. The three methods developed showed good rates of precision and accuracy. Besides the applicability present itself possible in view of the absence of analytical methods related of the sugarcane mills process, it must also be considered that the character of simplicity in terms of instrumentation and sample preparation has been achieved. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-08-28T17:57:01Z 2020-08-28T17:57:01Z 2020-08-06 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/11449/193319 33004030072P8 5704445473654024 0000-0002-8117-2108 |
url |
http://hdl.handle.net/11449/193319 |
identifier_str_mv |
33004030072P8 5704445473654024 0000-0002-8117-2108 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
publisher.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
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1808128405495873536 |