Brown sugar characterization based on sucrose, Cu, Ca, Na, Fe and Mg contents

Detalhes bibliográficos
Autor(a) principal: Natalino, Ricardo
Data de Publicação: 2021
Outros Autores: Reis, Efraim Lázaro, Reis, Cesar, Fidêncio, Paulo Henrique, Mayrink, Maria Isabel Cristina Batista
Tipo de documento: Artigo
Idioma: por
Título da fonte: Revista de Engenharia Química e Química
Texto Completo: https://periodicos.ufv.br/jcec/article/view/12796
Resumo: Samples of light brown sugar (DPC) and dark sugar (DPE) were analyzed, determining their characteristics, based on metal concentration and sucrose data, through of the principal component analysis (PCA). For this purpose, a matrix with 97 sugar samples and 6 variables (sucrose, Cu, Ca, Na, Fe and Mg) was obtained, self-scaling the data with zero mean and unit variance. The principal component analysis showed the common and discrepant characteristics between the different brown sugars. In the data arrangement in the PCA, it is possible to observe that the first two principal components explain practically 70% of the total variance of the data. Observing the separation between the light brown sugar group (DPC) and the dark brown sugar group (DPE), in the first principal component while in the second principal component the separation of the samples from the light brown sugar group (DPC) is evident of six dark brown sugar (DPE) samples, which showed similar characteristics to the light brown sugar group (DPC) samples in first principal component. These characteristics of the samples are evidenced probably due to the cooking process in which cleaning is carried out, to remove the foams formed during the heating of the broth, in order to ensure a lighter product. In this operation, as evidenced by the analyzes, calcium and iron are removed, two variables, in addition to sucrose, which are more significant in the classification of dark brown sugar (DPE).
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spelling Brown sugar characterization based on sucrose, Cu, Ca, Na, Fe and Mg contentsCaracterização de açúcar mascavo baseado nos teores de sacarose, Cu, Ca, Na, Fe e Mg Açúcar mascavo. Análise das componentes principais. Espectrofotometria por absorção atômica.Brown sugar. Principal component analysis. Atomic absorption spectrometry.Samples of light brown sugar (DPC) and dark sugar (DPE) were analyzed, determining their characteristics, based on metal concentration and sucrose data, through of the principal component analysis (PCA). For this purpose, a matrix with 97 sugar samples and 6 variables (sucrose, Cu, Ca, Na, Fe and Mg) was obtained, self-scaling the data with zero mean and unit variance. The principal component analysis showed the common and discrepant characteristics between the different brown sugars. In the data arrangement in the PCA, it is possible to observe that the first two principal components explain practically 70% of the total variance of the data. Observing the separation between the light brown sugar group (DPC) and the dark brown sugar group (DPE), in the first principal component while in the second principal component the separation of the samples from the light brown sugar group (DPC) is evident of six dark brown sugar (DPE) samples, which showed similar characteristics to the light brown sugar group (DPC) samples in first principal component. These characteristics of the samples are evidenced probably due to the cooking process in which cleaning is carried out, to remove the foams formed during the heating of the broth, in order to ensure a lighter product. In this operation, as evidenced by the analyzes, calcium and iron are removed, two variables, in addition to sucrose, which are more significant in the classification of dark brown sugar (DPE).Foram analisadas amostras de açúcar mascavo claro (DPC) e escuro (DPE), determinando-se as características destas, baseado nos dados de concentração de metais e de sacarose, através da análise das componentes principais (PCA). Para tanto, uma matriz com 97 amostras de açucares e 6 variáveis (Sacarose, Cu, Ca, Na, Fe e Mg) foi obtida, auto escalonando-se os dados com média zero e variância unitária. A análise das componentes principais evidenciou as características comuns e discrepantes entre os diferentes açúcares mascavos. Na disposição dos dados na PCA é possível observar que as duas primeiras componentes principais explicam praticamente 70 % da variância total dos dados. Observando-se a separação entre o grupo de açúcar mascavo claro (DPC) e o grupo de açúcar mascavo escuro (DPE), na primeira componente principal enquanto na segunda componente principal fica evidenciado a separação das amostras do grupo de açúcar mascavo claro (DPC) de seis amostras de açúcar mascavo escuro (DPE), que apresentaram características semelhantes às amostras do grupo de açúcar mascavo claro (DPC) na CP1. Estas características das amostras ficam evidenciadas provavelmente devido ao processo de cozimento no qual é realizado uma limpeza, para remover as espumas formadas durante o aquecimento do caldo, de modo a assegurar um produto mais claro. Nesta operação, como evidenciado pelas análises, são retirados cálcio e ferro, duas variáveis, além da sacarose, mais significativas na classificação do açúcar mascaro escuro (DPE).Universidade Federal de Viçosa - UFV2021-07-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufv.br/jcec/article/view/1279610.18540/jcecvl7iss3pp12796-01-09eThe Journal of Engineering and Exact Sciences; Vol. 7 No. 3 (2021); 12796-01-09eThe Journal of Engineering and Exact Sciences; Vol. 7 Núm. 3 (2021); 12796-01-09eThe Journal of Engineering and Exact Sciences; v. 7 n. 3 (2021); 12796-01-09e2527-1075reponame:Revista de Engenharia Química e Químicainstname:Universidade Federal de Viçosa (UFV)instacron:UFVporhttps://periodicos.ufv.br/jcec/article/view/12796/6758Copyright (c) 2021 The Journal of Engineering and Exact Scienceshttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessNatalino, RicardoReis, Efraim LázaroReis, CesarFidêncio, Paulo HenriqueMayrink, Maria Isabel Cristina Batista 2021-08-16T18:50:11Zoai:ojs.periodicos.ufv.br:article/12796Revistahttp://www.seer.ufv.br/seer/rbeq2/index.php/req2/indexONGhttps://periodicos.ufv.br/jcec/oaijcec.journal@ufv.br||req2@ufv.br2446-94162446-9416opendoar:2021-08-16T18:50:11Revista de Engenharia Química e Química - Universidade Federal de Viçosa (UFV)false
dc.title.none.fl_str_mv Brown sugar characterization based on sucrose, Cu, Ca, Na, Fe and Mg contents
Caracterização de açúcar mascavo baseado nos teores de sacarose, Cu, Ca, Na, Fe e Mg
title Brown sugar characterization based on sucrose, Cu, Ca, Na, Fe and Mg contents
spellingShingle Brown sugar characterization based on sucrose, Cu, Ca, Na, Fe and Mg contents
Natalino, Ricardo
Açúcar mascavo. Análise das componentes principais. Espectrofotometria por absorção atômica.
Brown sugar. Principal component analysis. Atomic absorption spectrometry.
title_short Brown sugar characterization based on sucrose, Cu, Ca, Na, Fe and Mg contents
title_full Brown sugar characterization based on sucrose, Cu, Ca, Na, Fe and Mg contents
title_fullStr Brown sugar characterization based on sucrose, Cu, Ca, Na, Fe and Mg contents
title_full_unstemmed Brown sugar characterization based on sucrose, Cu, Ca, Na, Fe and Mg contents
title_sort Brown sugar characterization based on sucrose, Cu, Ca, Na, Fe and Mg contents
author Natalino, Ricardo
author_facet Natalino, Ricardo
Reis, Efraim Lázaro
Reis, Cesar
Fidêncio, Paulo Henrique
Mayrink, Maria Isabel Cristina Batista
author_role author
author2 Reis, Efraim Lázaro
Reis, Cesar
Fidêncio, Paulo Henrique
Mayrink, Maria Isabel Cristina Batista
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Natalino, Ricardo
Reis, Efraim Lázaro
Reis, Cesar
Fidêncio, Paulo Henrique
Mayrink, Maria Isabel Cristina Batista
dc.subject.por.fl_str_mv Açúcar mascavo. Análise das componentes principais. Espectrofotometria por absorção atômica.
Brown sugar. Principal component analysis. Atomic absorption spectrometry.
topic Açúcar mascavo. Análise das componentes principais. Espectrofotometria por absorção atômica.
Brown sugar. Principal component analysis. Atomic absorption spectrometry.
description Samples of light brown sugar (DPC) and dark sugar (DPE) were analyzed, determining their characteristics, based on metal concentration and sucrose data, through of the principal component analysis (PCA). For this purpose, a matrix with 97 sugar samples and 6 variables (sucrose, Cu, Ca, Na, Fe and Mg) was obtained, self-scaling the data with zero mean and unit variance. The principal component analysis showed the common and discrepant characteristics between the different brown sugars. In the data arrangement in the PCA, it is possible to observe that the first two principal components explain practically 70% of the total variance of the data. Observing the separation between the light brown sugar group (DPC) and the dark brown sugar group (DPE), in the first principal component while in the second principal component the separation of the samples from the light brown sugar group (DPC) is evident of six dark brown sugar (DPE) samples, which showed similar characteristics to the light brown sugar group (DPC) samples in first principal component. These characteristics of the samples are evidenced probably due to the cooking process in which cleaning is carried out, to remove the foams formed during the heating of the broth, in order to ensure a lighter product. In this operation, as evidenced by the analyzes, calcium and iron are removed, two variables, in addition to sucrose, which are more significant in the classification of dark brown sugar (DPE).
publishDate 2021
dc.date.none.fl_str_mv 2021-07-02
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.ufv.br/jcec/article/view/12796
10.18540/jcecvl7iss3pp12796-01-09e
url https://periodicos.ufv.br/jcec/article/view/12796
identifier_str_mv 10.18540/jcecvl7iss3pp12796-01-09e
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://periodicos.ufv.br/jcec/article/view/12796/6758
dc.rights.driver.fl_str_mv Copyright (c) 2021 The Journal of Engineering and Exact Sciences
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 The Journal of Engineering and Exact Sciences
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Viçosa - UFV
publisher.none.fl_str_mv Universidade Federal de Viçosa - UFV
dc.source.none.fl_str_mv The Journal of Engineering and Exact Sciences; Vol. 7 No. 3 (2021); 12796-01-09e
The Journal of Engineering and Exact Sciences; Vol. 7 Núm. 3 (2021); 12796-01-09e
The Journal of Engineering and Exact Sciences; v. 7 n. 3 (2021); 12796-01-09e
2527-1075
reponame:Revista de Engenharia Química e Química
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instname_str Universidade Federal de Viçosa (UFV)
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reponame_str Revista de Engenharia Química e Química
collection Revista de Engenharia Química e Química
repository.name.fl_str_mv Revista de Engenharia Química e Química - Universidade Federal de Viçosa (UFV)
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