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Discrimination of sweet cherry cultivars based on electronic tongue potentiometric fingerprints

2020Journal article Open access
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dc.contributor.authorRodrigues, Isabel
dc.contributor.authorRodrigues, Nuno
dc.contributor.authorMarx, Ítala
dc.contributor.authorVeloso, Ana C.A.
dc.contributor.authorRamos, Ana Cristina
dc.contributor.authorPereira, J.A.
dc.contributor.authorPeres, António M.
dc.date.accessioned2018-02-19T10:00:00Z
dc.date.accessioned2021-02-27T16:21:22Z
dc.date.available2018-01-19T10:00:00Z
dc.date.available2021-02-27T16:21:22Z
dc.date.issued2020
dc.description.abstract© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Sweet cherry is highly appreciated by its characteristic flavor, which conditions the consumer's preference. In this study, four sweet cherry cultivars (Durona, Lapins, Summit, and Van cultivars) were characterized according to biometric (fruit and stone weights, length, maximum and minimum diameters, pulp/stone mass ratio), physicochemical (CIELAB color, penetration force, titratable acidity, and total soluble solids), and potentiometric profiles (recorded by a lab-made electronic tongue with lipid polymeric membranes). Biometric and physicochemical data were significantly cultivar-dependent (p-value 0.0001, one-way ANOVA). Summit cherries had higher masses and dimensions. Lapins cherries had the highest penetration force values having, together with Summit cherries, the highest CIELAB values. Van cherries showed the highest total soluble solids contents. No significant differences were found for fruits' acidity (similar titratable acidities). The possibility of discriminating cherry cultivars was also evaluated using a linear discriminant analysis/simulated-annealing algorithm. A discriminant model was established based on nine non-redundant biometric-physicochemical parameters (using a low-level data fusion), with low sensitivity (75 ± 15% for the repeated K-fold cross-validation). On the contrary, a discriminant model, based on the potentiometric fingerprints of 11 selected sensors, allowed a better discrimination, with sensitivities of 88 ± 7% for the repeated K-fold cross-validation procedure. Thus, the electronic tongue could be used as a practical tool to discriminate cherry cultivars and, if applied by fruit traders, may reduce the risk of mislabeling, increasing the consumers' confidence when purchasing this high-value product.en_EN
dc.description.sponsorshipThe authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial J.A.P. All authors have read and agreed to the published version of the manuscript. support by national funds FCT/MCTES to CIMO (UIDB/00690/2020) and to CEB (UIDB/04469/2020) units, as well as BioTecNorte operation (NORTE-01-0145-FEDER-000004), FUNDEDE BY European Regional Development Fund under the scope of Norte2020-Programa Operacional Regional do Norte. Nuno Rodrigues also thanks support by national funds FCT/MCTES to CIMO (UIDB/00690/2020) and to CEB (UIDB/04469/2020) units, as the national funding by FCT–Foundation for Science and Technology, P.I., through the Institutional scientific well as BioTecNorte operation (NORTE-01-0145-FEDER-000004), funded by the European Regional employment program contract.en_EN
dc.description.versioninfo:eu-repo/semantics/publishedVersionen_EN
dc.identifier.citationRodrigues, Isabel; Rodrigues, Nuno; Marx, Ítala M.G.; Veloso, Ana C.A.; Ramos, Ana Cristina; Pereira, José Alberto; Peres, Antônio M. (2020). Discrimination of sweet cherry cultivars based on electronic tongue potentiometric fingerprints. Applied Sciences (Switzerland). ISSN 2076-3417. 10:20, p. 1-11en_EN
dc.identifier.doi10.3390/app10207053en_EN
dc.identifier.urihttp://hdl.handle.net/10198/23372
dc.language.isoeng
dc.peerreviewedyesen_EN
dc.relationMountain Research Center
dc.subjectAnalysis of varianceen_EN
dc.subjectBiometric dataen_EN
dc.subjectChemical dataen_EN
dc.subjectCIELAB color scaleen_EN
dc.subjectCultivar discriminationen_EN
dc.subjectLinear discriminant analysisen_EN
dc.subjectPotentiometric taste sensoren_EN
dc.subjectSimulated annealing algorithmen_EN
dc.subjectSweet cherryen_EN
dc.titleDiscrimination of sweet cherry cultivars based on electronic tongue potentiometric fingerprintsen_EN
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleMountain Research Center
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00690%2F2020/PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameRodrigues
person.familyNameRodrigues
person.familyNameMarx
person.familyNamePereira
person.familyNamePeres
person.givenNameIsabel
person.givenNameNuno
person.givenNameÍtala
person.givenNameJosé Alberto
person.givenNameAntónio M.
person.identifier1676851
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person.identifier.ciencia-idCF16-5443-F420
person.identifier.orcid0000-0002-4827-2115
person.identifier.orcid0000-0002-9305-0976
person.identifier.orcid0000-0002-7049-2114
person.identifier.orcid0000-0002-2260-0600
person.identifier.orcid0000-0001-6595-9165
person.identifier.ridGLV-5485-2022
person.identifier.ridL-6798-2014
person.identifier.ridI-8470-2012
person.identifier.scopus-author-id55258560600
person.identifier.scopus-author-id57191503603
person.identifier.scopus-author-id57204366348
person.identifier.scopus-author-id7102331969
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccessen_EN
rcaap.typearticleen_EN
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