Minimal-Invasive Analytical Method and Data Fusion: an Alternative for Determination of Cu, K, Sr, and Zn in Cocoa Beans
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1007/s12161-020-01904-2 http://hdl.handle.net/11449/205379 |
Resumo: | In the present study, a minimal-invasive analytical method for determination of Cu, K, Sr, and Zn in cocoa beans was performed using energy X-ray fluorescence (EDXRF) and laser-induced breakdown spectroscopy (LIBS) combined with multivariate calibration. Partial least squares (PLS) chemometric technique was applied to modeling the data, and inductively coupled plasma optical emission spectrometry (ICP OES) technique was the reference method for the chemical elements concentration levels, after microwave acid mineralization. The figures of merit estimated for Cu, Sr, Zn, and K showed good performance, with acceptable trueness values (85–120%). Data fusion strategy between EDXRF and LIBS data was used to enhance the predictive capability of K. In addition, lower standard error of cross-validation (SECV) (872 mg kg−1) was obtained, showing better performance than those obtained by individual data. |
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Minimal-Invasive Analytical Method and Data Fusion: an Alternative for Determination of Cu, K, Sr, and Zn in Cocoa BeansChemometricsDirect solid analysisFood samplesNutrientsPartial least squaresSpectroanalytical techniquesIn the present study, a minimal-invasive analytical method for determination of Cu, K, Sr, and Zn in cocoa beans was performed using energy X-ray fluorescence (EDXRF) and laser-induced breakdown spectroscopy (LIBS) combined with multivariate calibration. Partial least squares (PLS) chemometric technique was applied to modeling the data, and inductively coupled plasma optical emission spectrometry (ICP OES) technique was the reference method for the chemical elements concentration levels, after microwave acid mineralization. The figures of merit estimated for Cu, Sr, Zn, and K showed good performance, with acceptable trueness values (85–120%). Data fusion strategy between EDXRF and LIBS data was used to enhance the predictive capability of K. In addition, lower standard error of cross-validation (SECV) (872 mg kg−1) was obtained, showing better performance than those obtained by individual data.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Group of Applied Instrumental Analysis Department of Chemistry Federal University of São CarlosGroup of Alternative Analytical Approaches (GAAA) Bioenergy Research Institute (IPBEN) Institute of Chemistry São Paulo State University (UNESP)National Institute of Alternative Technologies for Detection Toxicological Assessment and Removal of Micropollutants and Radioactive Substances (INCT-DATREM)Group of Alternative Analytical Approaches (GAAA) Bioenergy Research Institute (IPBEN) Institute of Chemistry São Paulo State University (UNESP)FAPESP: 2014/50945-4FAPESP: 2018/18212-8FAPESP: 2019/01102-8FAPESP: 2019/24223-5CNPq: 305637/2015-0CNPq: 307328/2019-8CNPq: 465571/2014-0CAPES: 88887136426/2017/00CAPES: Finance Code 001Universidade Federal de São Carlos (UFSCar)Universidade Estadual Paulista (Unesp)National Institute of Alternative Technologies for Detection Toxicological Assessment and Removal of Micropollutants and Radioactive Substances (INCT-DATREM)Gamela, Raimundo RafaelPereira-Filho, Edenir RodriguesPereira, Fabíola Manhas Verbi [UNESP]2021-06-25T10:14:22Z2021-06-25T10:14:22Z2021-03-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article545-551http://dx.doi.org/10.1007/s12161-020-01904-2Food Analytical Methods, v. 14, n. 3, p. 545-551, 2021.1936-976X1936-9751http://hdl.handle.net/11449/20537910.1007/s12161-020-01904-22-s2.0-85093974860Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengFood Analytical Methodsinfo:eu-repo/semantics/openAccess2021-10-23T12:39:59Zoai:repositorio.unesp.br:11449/205379Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:11:19.157146Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Minimal-Invasive Analytical Method and Data Fusion: an Alternative for Determination of Cu, K, Sr, and Zn in Cocoa Beans |
title |
Minimal-Invasive Analytical Method and Data Fusion: an Alternative for Determination of Cu, K, Sr, and Zn in Cocoa Beans |
spellingShingle |
Minimal-Invasive Analytical Method and Data Fusion: an Alternative for Determination of Cu, K, Sr, and Zn in Cocoa Beans Gamela, Raimundo Rafael Chemometrics Direct solid analysis Food samples Nutrients Partial least squares Spectroanalytical techniques |
title_short |
Minimal-Invasive Analytical Method and Data Fusion: an Alternative for Determination of Cu, K, Sr, and Zn in Cocoa Beans |
title_full |
Minimal-Invasive Analytical Method and Data Fusion: an Alternative for Determination of Cu, K, Sr, and Zn in Cocoa Beans |
title_fullStr |
Minimal-Invasive Analytical Method and Data Fusion: an Alternative for Determination of Cu, K, Sr, and Zn in Cocoa Beans |
title_full_unstemmed |
Minimal-Invasive Analytical Method and Data Fusion: an Alternative for Determination of Cu, K, Sr, and Zn in Cocoa Beans |
title_sort |
Minimal-Invasive Analytical Method and Data Fusion: an Alternative for Determination of Cu, K, Sr, and Zn in Cocoa Beans |
author |
Gamela, Raimundo Rafael |
author_facet |
Gamela, Raimundo Rafael Pereira-Filho, Edenir Rodrigues Pereira, Fabíola Manhas Verbi [UNESP] |
author_role |
author |
author2 |
Pereira-Filho, Edenir Rodrigues Pereira, Fabíola Manhas Verbi [UNESP] |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade Federal de São Carlos (UFSCar) Universidade Estadual Paulista (Unesp) National Institute of Alternative Technologies for Detection Toxicological Assessment and Removal of Micropollutants and Radioactive Substances (INCT-DATREM) |
dc.contributor.author.fl_str_mv |
Gamela, Raimundo Rafael Pereira-Filho, Edenir Rodrigues Pereira, Fabíola Manhas Verbi [UNESP] |
dc.subject.por.fl_str_mv |
Chemometrics Direct solid analysis Food samples Nutrients Partial least squares Spectroanalytical techniques |
topic |
Chemometrics Direct solid analysis Food samples Nutrients Partial least squares Spectroanalytical techniques |
description |
In the present study, a minimal-invasive analytical method for determination of Cu, K, Sr, and Zn in cocoa beans was performed using energy X-ray fluorescence (EDXRF) and laser-induced breakdown spectroscopy (LIBS) combined with multivariate calibration. Partial least squares (PLS) chemometric technique was applied to modeling the data, and inductively coupled plasma optical emission spectrometry (ICP OES) technique was the reference method for the chemical elements concentration levels, after microwave acid mineralization. The figures of merit estimated for Cu, Sr, Zn, and K showed good performance, with acceptable trueness values (85–120%). Data fusion strategy between EDXRF and LIBS data was used to enhance the predictive capability of K. In addition, lower standard error of cross-validation (SECV) (872 mg kg−1) was obtained, showing better performance than those obtained by individual data. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-06-25T10:14:22Z 2021-06-25T10:14:22Z 2021-03-01 |
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/10.1007/s12161-020-01904-2 Food Analytical Methods, v. 14, n. 3, p. 545-551, 2021. 1936-976X 1936-9751 http://hdl.handle.net/11449/205379 10.1007/s12161-020-01904-2 2-s2.0-85093974860 |
url |
http://dx.doi.org/10.1007/s12161-020-01904-2 http://hdl.handle.net/11449/205379 |
identifier_str_mv |
Food Analytical Methods, v. 14, n. 3, p. 545-551, 2021. 1936-976X 1936-9751 10.1007/s12161-020-01904-2 2-s2.0-85093974860 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Food Analytical Methods |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
545-551 |
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 |
|
_version_ |
1808128616122286080 |