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A potentiometric electronic tongue as a discrimination tool of water-food indicator/contamination bacteria

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Resumo:Microorganism assessment plays a key role in food quality and safety control but conventional techniques are costly and/or time consuming. Alternatively, electronic tongues (E-tongues) can fulfill this critical task. Thus, a potentiometric lab-made E-tongue (40 lipid sensor membranes) was used to differentiate four common food contamination bacteria, including two Gram positive (Enterococcus faecalis, Staphylococcus aureus) and two Gram negative (Escherichia coli, Pseudomonas aeruginosa). Principal component analysis and a linear discriminant analysis-simulated annealing algorithm (LDA-SA) showed that the potentiometric signal profiles acquired during the analysis of aqueous solutions containing known amounts of each studied bacteria allowed a satisfactory differentiation of the four bacterial strains. An E-tongue-LDA-SA model (12 non-redundant sensors) correctly classified 98 ± 5% of the samples (repeated K-fold-CV), the satisfactory performance of which can be attributed to the capability of the lipid membranes to establish electrostatic interactions/hydrogen bonds with hydroxyl, amine and/or carbonyl groups, which are comprised in the bacteria outer membranes. Furthermore, multiple linear regression models, based on selected subsets of E-tongue sensors (12–15 sensors), also allowed quantifying the bacteria contents in aqueous solutions (0.993 ± 0.011 ≤ R2 ≤ 0.998 ± 0.005, for repeated K-fold-CV). In conclusion, the E-tongue could be of great value as a preliminary food quality and safety diagnosis tool.
Autores principais:Ghrissi, Hiba
Outros Autores:Veloso, Ana C.A.; Marx, Ítala; Dias, Teresa; Peres, António M.
Assunto:Chemometrics Electronic tongue Food-water bacteria Linear discriminant analysis Lipid sensor membranes Potentiometric analysis Principal component analysis Simulated annealing variable selection algorithm
Ano:2021
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
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author Ghrissi, Hiba
author2 Veloso, Ana C.A.
Marx, Ítala
Dias, Teresa
Peres, António M.
author2_role author
author
author
author
author_facet Ghrissi, Hiba
Veloso, Ana C.A.
Marx, Ítala
Dias, Teresa
Peres, António M.
author_role author
contributor_name_str_mv Biblioteca Digital do IPB
country_str PT
creators_json_txt [{\"Person.name\":\"Ghrissi, Hiba\"},{\"Person.name\":\"Veloso, Ana C.A.\"},{\"Person.name\":\"Marx, Ítala\",\"Person.identifier.orcid\":\"0000-0002-7049-2114\"},{\"Person.name\":\"Dias, Teresa\",\"Person.identifier.orcid\":\"0000-0002-9419-9561\"},{\"Person.name\":\"Peres, António M.\",\"Person.identifier.orcid\":\"0000-0001-6595-9165\"}]
datacite.contributors.contributor.contributorName.fl_str_mv Biblioteca Digital do IPB
datacite.creators.creator.creatorName.fl_str_mv Ghrissi, Hiba
Veloso, Ana C.A.
Marx, Ítala
Dias, Teresa
Peres, António M.
datacite.date.Accepted.fl_str_mv 2021-01-01T00:00:00Z
datacite.date.available.fl_str_mv 2018-01-19T10:00:00Z
datacite.date.embargoed.fl_str_mv 2018-01-19T10:00:00Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Chemometrics
Electronic tongue
Food-water bacteria
Linear discriminant analysis
Lipid sensor membranes
Potentiometric analysis
Principal component analysis
Simulated annealing variable selection algorithm
datacite.titles.title.fl_str_mv A potentiometric electronic tongue as a discrimination tool of water-food indicator/contamination bacteria
dc.contributor.none.fl_str_mv Biblioteca Digital do IPB
dc.creator.none.fl_str_mv Ghrissi, Hiba
Veloso, Ana C.A.
Marx, Ítala
Dias, Teresa
Peres, António M.
dc.date.Accepted.fl_str_mv 2021-01-01T00:00:00Z
dc.date.available.fl_str_mv 2018-01-19T10:00:00Z
dc.date.embargoed.fl_str_mv 2018-01-19T10:00:00Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://hdl.handle.net/10198/24330
dc.language.none.fl_str_mv eng
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.subject.none.fl_str_mv Chemometrics
Electronic tongue
Food-water bacteria
Linear discriminant analysis
Lipid sensor membranes
Potentiometric analysis
Principal component analysis
Simulated annealing variable selection algorithm
dc.title.fl_str_mv A potentiometric electronic tongue as a discrimination tool of water-food indicator/contamination bacteria
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_6501
description Microorganism assessment plays a key role in food quality and safety control but conventional techniques are costly and/or time consuming. Alternatively, electronic tongues (E-tongues) can fulfill this critical task. Thus, a potentiometric lab-made E-tongue (40 lipid sensor membranes) was used to differentiate four common food contamination bacteria, including two Gram positive (Enterococcus faecalis, Staphylococcus aureus) and two Gram negative (Escherichia coli, Pseudomonas aeruginosa). Principal component analysis and a linear discriminant analysis-simulated annealing algorithm (LDA-SA) showed that the potentiometric signal profiles acquired during the analysis of aqueous solutions containing known amounts of each studied bacteria allowed a satisfactory differentiation of the four bacterial strains. An E-tongue-LDA-SA model (12 non-redundant sensors) correctly classified 98 ± 5% of the samples (repeated K-fold-CV), the satisfactory performance of which can be attributed to the capability of the lipid membranes to establish electrostatic interactions/hydrogen bonds with hydroxyl, amine and/or carbonyl groups, which are comprised in the bacteria outer membranes. Furthermore, multiple linear regression models, based on selected subsets of E-tongue sensors (12–15 sensors), also allowed quantifying the bacteria contents in aqueous solutions (0.993 ± 0.011 ≤ R2 ≤ 0.998 ± 0.005, for repeated K-fold-CV). In conclusion, the E-tongue could be of great value as a preliminary food quality and safety diagnosis tool.
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funding.funder.name_str_mv Fundação para a Ciência e a Tecnologia
Fundação para a Ciência e a Tecnologia
Fundação para a Ciência e a Tecnologia
funding.name_str_mv 6817 - DCRRNI ID
6817 - DCRRNI ID
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organization_str_mv urn:organizationAcronym:ipb
person_str_mv Ghrissi, Hiba
Veloso, Ana C.A.
Marx, Ítala
Marx, Ítala
https://www.ciencia-id.pt/2717-C420-DEAE
2717-C420-DEAE
http://orcid.org/0000-0002-7049-2114
0000-0002-7049-2114
Dias, Teresa
Dias, Teresa
http://orcid.org/0000-0002-9419-9561
0000-0002-9419-9561
Peres, António M.
Peres, António M.
https://www.ciencia-id.pt/CF16-5443-F420
CF16-5443-F420
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spelling engen_ENMicroorganism assessment plays a key role in food quality and safety control but conventional techniques are costly and/or time consuming. Alternatively, electronic tongues (E-tongues) can fulfill this critical task. Thus, a potentiometric lab-made E-tongue (40 lipid sensor membranes) was used to differentiate four common food contamination bacteria, including two Gram positive (Enterococcus faecalis, Staphylococcus aureus) and two Gram negative (Escherichia coli, Pseudomonas aeruginosa). Principal component analysis and a linear discriminant analysis-simulated annealing algorithm (LDA-SA) showed that the potentiometric signal profiles acquired during the analysis of aqueous solutions containing known amounts of each studied bacteria allowed a satisfactory differentiation of the four bacterial strains. An E-tongue-LDA-SA model (12 non-redundant sensors) correctly classified 98 ± 5% of the samples (repeated K-fold-CV), the satisfactory performance of which can be attributed to the capability of the lipid membranes to establish electrostatic interactions/hydrogen bonds with hydroxyl, amine and/or carbonyl groups, which are comprised in the bacteria outer membranes. Furthermore, multiple linear regression models, based on selected subsets of E-tongue sensors (12–15 sensors), also allowed quantifying the bacteria contents in aqueous solutions (0.993 ± 0.011 ≤ R2 ≤ 0.998 ± 0.005, for repeated K-fold-CV). In conclusion, the E-tongue could be of great value as a preliminary food quality and safety diagnosis tool.application/pdfen_ENA potentiometric electronic tongue as a discrimination tool of water-food indicator/contamination bacteriaGhrissi, HibaVeloso, Ana C.A.PersonalMarx, ÍtalaDSpacehttp://dspace.org/items/ea543e4e-b9e9-45f1-afac-dda52dbf0ab8DSpacehttp://dspace.org/items/ea543e4e-b9e9-45f1-afac-dda52dbf0ab8MarxÍtalaCiência IDhttps://www.ciencia-id.pt2717-C420-DEAEORCIDhttp://orcid.org0000-0002-7049-2114Researcher IDhttps://www.researcherid.comGLV-5485-2022Scopus Author IDhttps://www.scopus.com57191503603PersonalDias, TeresaDSpacehttp://dspace.org/items/87c9cae0-314d-4622-ba85-4d3ec5726606DSpacehttp://dspace.org/items/87c9cae0-314d-4622-ba85-4d3ec5726606DiasTeresaORCIDhttp://orcid.org0000-0002-9419-9561Scopus Author IDhttps://www.scopus.com56830642600PersonalPeres, António M.DSpacehttp://dspace.org/items/7d93be47-8dc4-4413-9304-5b978773d3bbDSpacehttp://dspace.org/items/7d93be47-8dc4-4413-9304-5b978773d3bbPeresAntónio M.Ciência IDhttps://www.ciencia-id.ptCF16-5443-F420ORCIDhttp://orcid.org0000-0001-6595-9165Researcher IDhttps://www.researcherid.comI-8470-2012Scopus Author IDhttps://www.scopus.com7102331969HostingInstitutionOrganizationalBiblioteca Digital do IPBe-mailmailto:dspace@ipb.ptdspace@ipb.ptDOIIsPartOf10.3390/chemosensors90601432018-01-19T10:00:00Z20212021-01-01T00:00:00ZHandlehttp://hdl.handle.net/10198/24330http://purl.org/coar/access_right/c_abf2open accessChemometricsElectronic tongueFood-water bacteriaLinear discriminant analysisLipid sensor membranesPotentiometric analysisPrincipal component analysisSimulated annealing variable selection algorithm1615370 bytesFundação para a Ciência e a TecnologiaMountain Research Center6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871Fundação para a Ciência e a TecnologiaCentre of Biological Engineering of the University of Minho6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871Fundação para a Ciência e a TecnologiaImprovement of olive oil flavor and bioactive composition by optimizing industrial extraction using taste sensor devicesPOR_NORTECrossref Funder IDhttp://doi.org/10.13039/501100001871literaturehttp://purl.org/coar/resource_type/c_6501journal articlehttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://bibliotecadigital.ipb.pt/bitstreams/68908809-8dee-4149-80ff-e07144731b5d/download
spellingShingle A potentiometric electronic tongue as a discrimination tool of water-food indicator/contamination bacteria
Ghrissi, Hiba
Chemometrics
Electronic tongue
Food-water bacteria
Linear discriminant analysis
Lipid sensor membranes
Potentiometric analysis
Principal component analysis
Simulated annealing variable selection algorithm
status SINGLETON
subject.fl_str_mv Chemometrics
Electronic tongue
Food-water bacteria
Linear discriminant analysis
Lipid sensor membranes
Potentiometric analysis
Principal component analysis
Simulated annealing variable selection algorithm
title A potentiometric electronic tongue as a discrimination tool of water-food indicator/contamination bacteria
title_full A potentiometric electronic tongue as a discrimination tool of water-food indicator/contamination bacteria
title_fullStr A potentiometric electronic tongue as a discrimination tool of water-food indicator/contamination bacteria
title_full_unstemmed A potentiometric electronic tongue as a discrimination tool of water-food indicator/contamination bacteria
title_short A potentiometric electronic tongue as a discrimination tool of water-food indicator/contamination bacteria
title_sort A potentiometric electronic tongue as a discrimination tool of water-food indicator/contamination bacteria
topic Chemometrics
Electronic tongue
Food-water bacteria
Linear discriminant analysis
Lipid sensor membranes
Potentiometric analysis
Principal component analysis
Simulated annealing variable selection algorithm
topic_facet Chemometrics
Electronic tongue
Food-water bacteria
Linear discriminant analysis
Lipid sensor membranes
Potentiometric analysis
Principal component analysis
Simulated annealing variable selection algorithm
url http://hdl.handle.net/10198/24330
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