Repository logo
 
Publication

Dairy products discrimination according to the milk type using an electrochemical multisensor device coupled with chemometric tools

dc.contributor.authorTazi, Imam
dc.contributor.authorTriyana, Kuwat
dc.contributor.authorSiswanta, Dwi
dc.contributor.authorVeloso, Ana C.A.
dc.contributor.authorPeres, António M.
dc.contributor.authorDias, L.G.
dc.date.accessioned2020-02-21T15:48:27Z
dc.date.available2020-02-21T15:48:27Z
dc.date.issued2018
dc.description.abstractThis study shows the potential application of a potentiometric electronic tongue coupled with a lab-made DataLogger device for the classification of dairy products according to the type of milk used in their production, i.e., natural, fermented and UHT milk. The electronic tongue device merged a commercial pH electrode and 15 lipid/polymeric membranes, which were obtained by a drop-by-drop technique. The potentiometric signal profiles gathered from the 16 sensors, during the analysis of the 11 dairy products (with ten replicate samples), together with principal component analysis showed that dairy samples could be naturally grouped according to the three types of milk evaluated. To further investigate and verify this capability, a linear discriminant analysis together with a simulated annealing variable selection algorithm was also applied to the electrochemical data, which were randomly split into two datasets, one used for model training and internal-validation using a repeated K-fold cross-validation procedure (with 64% of the data); and the other for external validation purposes (containing the remaining 36% of the data). The multivariate supervised strategy used allowed establishing a classification model, based on the potentiometric information of four sensor lipid membranes, which enabled achieving a successful discrimination rate of 100% for both internal- and external-validation processes. The demonstrated versatility of the built electronic tongue for discriminating dairy products according to the type of milk used in their production combined with its simplicity, low-cost and fast time analysis may envisage a possible future application in dairy industry.pt_PT
dc.description.sponsorshipThis study was funded in part by the Ministry of Research, Technology and Higher Education, the Republic of Indonesia, Project 001/SP2H/LT/DRPM/IV/2017. The authors also thank the Directorate General of Islamic Education and Instituto Politécnico de Bragança, Portugal, for their support throughout the completion of this work. This work was financially supported by Project POCI- 01–0145-FEDER-006984 – Associate Laboratory LSRE-LCM, Project UID/BIO/04469/2013 – CEB and strategic project PEst-OE/ AGR/UI0690/2014 – CIMO all funded by FEDER - Fundo Europeu de Desenvolvimento Regional through COMPETE2020 - Programa Operacional Competitividade e Internacionalização (POCI) – and by national funds through FCT - Fundação para a Ciência e a Tecnologia, Portugal.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationTazi, Imam; Triyana, Kuwat; Siswanta, Dwi; Veloso, Ana C.A.; Peres, António M.; Dias, L.G. (2018). Dairy products discrimination according to the milk type using an electrochemical multisensor device coupled with chemometric tools. Journal of Food Measurement and Characterization. ISSN 2193-4134. 12:4, p. 235-2393pt_PT
dc.identifier.doi10.1007/s11694-018-9855-8pt_PT
dc.identifier.issn2193-4134
dc.identifier.urihttp://hdl.handle.net/10198/20640
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/pt_PT
dc.subjectDairy productspt_PT
dc.subjectElectronic tonguept_PT
dc.subjectPrincipal component analysispt_PT
dc.subjectLinear discriminant analysispt_PT
dc.subjectSimulated annealing algorithmpt_PT
dc.titleDairy products discrimination according to the milk type using an electrochemical multisensor device coupled with chemometric toolspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FBIO%2F04469%2F2013/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/PEst-OE%2FAGR%2FUI0690%2F2014/PT
oaire.citation.endPage2393pt_PT
oaire.citation.issue4pt_PT
oaire.citation.startPage2385pt_PT
oaire.citation.titleJournal of Food Measurement and Characterizationpt_PT
oaire.citation.volume12pt_PT
oaire.fundingStream5876
oaire.fundingStream5876
person.familyNamePeres
person.familyNameDias
person.givenNameAntónio M.
person.givenNameLuís G.
person.identifier107333
person.identifier.ciencia-idCF16-5443-F420
person.identifier.ciencia-id2F11-9092-FAAF
person.identifier.orcid0000-0001-6595-9165
person.identifier.orcid0000-0002-1210-4259
person.identifier.ridI-8470-2012
person.identifier.scopus-author-id7102331969
person.identifier.scopus-author-id23569169900
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication7d93be47-8dc4-4413-9304-5b978773d3bb
relation.isAuthorOfPublicationeac8c166-4056-4ed0-8d8d-7ecb2c4481a5
relation.isAuthorOfPublication.latestForDiscovery7d93be47-8dc4-4413-9304-5b978773d3bb
relation.isProjectOfPublication774297b8-449c-4471-8bbb-0cfe1f4c8275
relation.isProjectOfPublicationf3fc3f7e-17b1-488f-abea-2601a44654b1
relation.isProjectOfPublication.latestForDiscovery774297b8-449c-4471-8bbb-0cfe1f4c8275

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
tazi2018.pdf
Size:
1.09 MB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.75 KB
Format:
Item-specific license agreed upon to submission
Description: