Artificial neural network employment for element determination in: Mugil cephalus by ICP OES in Pontal Bay, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1039/d0ay00799d http://hdl.handle.net/11449/199273 |
Resumo: | Fish are important sources of protein, making them very significant in the human diet. Although the consumption of this food is beneficial for health, it is essential that the product does not contain inorganic components above the limits recommended by the current legislation. Therefore, a method for determination of elements in fish (Mugil cephalus) samples was optimized. A simplex centroid mixture design with restriction was applied for optimization of the acid digestion of samples in an open system under reflux in order to evaluate the best ratio between the reagents HNO3, H2O2 and H2O. The results indicated that more intense analyte signals were obtained when a mixture containing 3.6 mL of HNO3 (65% v/v), 0.4 mL of H2O2 (30% v/v) and 6.0 mL of H2O was used. The accuracy of the method was assessed with a CRM of oyster tissue (NIST 1566b). The method presented relative standard deviations (RSDs) of 3.54%; 3.82%; 4.81% and 3.50% for Zn, Fe, Cu and S, respectively. The detection limits were 0.002 mg kg-1 for Cu and Zn and 0.02 mg kg-1 for Fe and S. The proposed method was applied for the determination of Zn, Fe, Cu and S in fish samples. A Kohonen Self-Organizing Map (KSOM) with K-means implementation was applied to better delimit the boundary between groups and the spatial and temporal influence on how concentrations of the chemical elements were perceived. To verify the separation, the Davies-Bouldin and Silhouette indices were used, obtaining 0.5374 and 0.8541, respectively, indicating satisfactory separation. |
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Repositório Institucional da UNESP |
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Artificial neural network employment for element determination in: Mugil cephalus by ICP OES in Pontal Bay, BrazilFish are important sources of protein, making them very significant in the human diet. Although the consumption of this food is beneficial for health, it is essential that the product does not contain inorganic components above the limits recommended by the current legislation. Therefore, a method for determination of elements in fish (Mugil cephalus) samples was optimized. A simplex centroid mixture design with restriction was applied for optimization of the acid digestion of samples in an open system under reflux in order to evaluate the best ratio between the reagents HNO3, H2O2 and H2O. The results indicated that more intense analyte signals were obtained when a mixture containing 3.6 mL of HNO3 (65% v/v), 0.4 mL of H2O2 (30% v/v) and 6.0 mL of H2O was used. The accuracy of the method was assessed with a CRM of oyster tissue (NIST 1566b). The method presented relative standard deviations (RSDs) of 3.54%; 3.82%; 4.81% and 3.50% for Zn, Fe, Cu and S, respectively. The detection limits were 0.002 mg kg-1 for Cu and Zn and 0.02 mg kg-1 for Fe and S. The proposed method was applied for the determination of Zn, Fe, Cu and S in fish samples. A Kohonen Self-Organizing Map (KSOM) with K-means implementation was applied to better delimit the boundary between groups and the spatial and temporal influence on how concentrations of the chemical elements were perceived. To verify the separation, the Davies-Bouldin and Silhouette indices were used, obtaining 0.5374 and 0.8541, respectively, indicating satisfactory separation.Departamento de Ciências Exatas e Tecnológicas Universidade Estadual de Santa Cruz Campus Soane Nazaré de Andrade, Km 16 BR-415Instituto de Química Universidade Federal da Bahia Campus Universitário de OndinaDepartamento de Química e Exatas Universidade Estadual Do Sudoeste da Bahia Campus Universitário de Jequié-BA Avenida José Moreira Sobrinho, 677-JequiezinhoInstitute of Chemistry São Paulo State University (UNESP)Institute of Chemistry São Paulo State University (UNESP)Universidade Estadual de Santa CruzUniversidade Federal da Bahia (UFBA)Universidade Estadual Do Sudoeste da BahiaUniversidade Estadual Paulista (Unesp)Batista, Milana Aboboreira SimõesSantos, Luana NovaesChagas, Bruna CirineuLôbo, Ivon PinheiroNovaes, Cleber GalvãoGuedes, Wesley Nascimento [UNESP]De Jesus, Raildo MotaAmorim, Fábio Alan CarqueijaPacheco, Clissiane Soares VianaMoreira, Luana SantosDa Silva, Erik Galvão Paranhos2020-12-12T01:35:19Z2020-12-12T01:35:19Z2020-08-07info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article3713-3721http://dx.doi.org/10.1039/d0ay00799dAnalytical Methods, v. 12, n. 29, p. 3713-3721, 2020.1759-96791759-9660http://hdl.handle.net/11449/19927310.1039/d0ay00799d2-s2.0-85089545331Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengAnalytical Methodsinfo:eu-repo/semantics/openAccess2021-10-23T06:37:33Zoai:repositorio.unesp.br:11449/199273Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-06T00:10:15.116352Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Artificial neural network employment for element determination in: Mugil cephalus by ICP OES in Pontal Bay, Brazil |
title |
Artificial neural network employment for element determination in: Mugil cephalus by ICP OES in Pontal Bay, Brazil |
spellingShingle |
Artificial neural network employment for element determination in: Mugil cephalus by ICP OES in Pontal Bay, Brazil Batista, Milana Aboboreira Simões |
title_short |
Artificial neural network employment for element determination in: Mugil cephalus by ICP OES in Pontal Bay, Brazil |
title_full |
Artificial neural network employment for element determination in: Mugil cephalus by ICP OES in Pontal Bay, Brazil |
title_fullStr |
Artificial neural network employment for element determination in: Mugil cephalus by ICP OES in Pontal Bay, Brazil |
title_full_unstemmed |
Artificial neural network employment for element determination in: Mugil cephalus by ICP OES in Pontal Bay, Brazil |
title_sort |
Artificial neural network employment for element determination in: Mugil cephalus by ICP OES in Pontal Bay, Brazil |
author |
Batista, Milana Aboboreira Simões |
author_facet |
Batista, Milana Aboboreira Simões Santos, Luana Novaes Chagas, Bruna Cirineu Lôbo, Ivon Pinheiro Novaes, Cleber Galvão Guedes, Wesley Nascimento [UNESP] De Jesus, Raildo Mota Amorim, Fábio Alan Carqueija Pacheco, Clissiane Soares Viana Moreira, Luana Santos Da Silva, Erik Galvão Paranhos |
author_role |
author |
author2 |
Santos, Luana Novaes Chagas, Bruna Cirineu Lôbo, Ivon Pinheiro Novaes, Cleber Galvão Guedes, Wesley Nascimento [UNESP] De Jesus, Raildo Mota Amorim, Fábio Alan Carqueija Pacheco, Clissiane Soares Viana Moreira, Luana Santos Da Silva, Erik Galvão Paranhos |
author2_role |
author author author author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual de Santa Cruz Universidade Federal da Bahia (UFBA) Universidade Estadual Do Sudoeste da Bahia Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Batista, Milana Aboboreira Simões Santos, Luana Novaes Chagas, Bruna Cirineu Lôbo, Ivon Pinheiro Novaes, Cleber Galvão Guedes, Wesley Nascimento [UNESP] De Jesus, Raildo Mota Amorim, Fábio Alan Carqueija Pacheco, Clissiane Soares Viana Moreira, Luana Santos Da Silva, Erik Galvão Paranhos |
description |
Fish are important sources of protein, making them very significant in the human diet. Although the consumption of this food is beneficial for health, it is essential that the product does not contain inorganic components above the limits recommended by the current legislation. Therefore, a method for determination of elements in fish (Mugil cephalus) samples was optimized. A simplex centroid mixture design with restriction was applied for optimization of the acid digestion of samples in an open system under reflux in order to evaluate the best ratio between the reagents HNO3, H2O2 and H2O. The results indicated that more intense analyte signals were obtained when a mixture containing 3.6 mL of HNO3 (65% v/v), 0.4 mL of H2O2 (30% v/v) and 6.0 mL of H2O was used. The accuracy of the method was assessed with a CRM of oyster tissue (NIST 1566b). The method presented relative standard deviations (RSDs) of 3.54%; 3.82%; 4.81% and 3.50% for Zn, Fe, Cu and S, respectively. The detection limits were 0.002 mg kg-1 for Cu and Zn and 0.02 mg kg-1 for Fe and S. The proposed method was applied for the determination of Zn, Fe, Cu and S in fish samples. A Kohonen Self-Organizing Map (KSOM) with K-means implementation was applied to better delimit the boundary between groups and the spatial and temporal influence on how concentrations of the chemical elements were perceived. To verify the separation, the Davies-Bouldin and Silhouette indices were used, obtaining 0.5374 and 0.8541, respectively, indicating satisfactory separation. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-12-12T01:35:19Z 2020-12-12T01:35:19Z 2020-08-07 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1039/d0ay00799d Analytical Methods, v. 12, n. 29, p. 3713-3721, 2020. 1759-9679 1759-9660 http://hdl.handle.net/11449/199273 10.1039/d0ay00799d 2-s2.0-85089545331 |
url |
http://dx.doi.org/10.1039/d0ay00799d http://hdl.handle.net/11449/199273 |
identifier_str_mv |
Analytical Methods, v. 12, n. 29, p. 3713-3721, 2020. 1759-9679 1759-9660 10.1039/d0ay00799d 2-s2.0-85089545331 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Analytical Methods |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
3713-3721 |
dc.source.none.fl_str_mv |
Scopus 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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1808129591739416576 |