Minimal-Invasive Analytical Method and Data Fusion: an Alternative for Determination of Cu, K, Sr, and Zn in Cocoa Beans

Detalhes bibliográficos
Autor(a) principal: Gamela, Raimundo Rafael
Data de Publicação: 2021
Outros Autores: Pereira-Filho, Edenir Rodrigues, Pereira, Fabíola Manhas Verbi [UNESP]
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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spelling 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
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