Discrimination of sweet cherry cultivars based on electronic tongue potentiometric fingerprints
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10198/23372 |
Resumo: | © 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. |
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Discrimination of sweet cherry cultivars based on electronic tongue potentiometric fingerprintsAnalysis of varianceBiometric dataChemical dataCIELAB color scaleCultivar discriminationLinear discriminant analysisPotentiometric taste sensorSimulated annealing algorithmSweet cherry© 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.The 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.Biblioteca Digital do IPBRodrigues, IsabelRodrigues, NunoMarx, ÍtalaVeloso, Ana C.A.Ramos, Ana CristinaPereira, J.A.Peres, António M.2018-01-19T10:00:00Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10198/23372engRodrigues, 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. 1-1110.3390/app10207053info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-21T10:52:15Zoai:bibliotecadigital.ipb.pt:10198/23372Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:14:22.718088Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Discrimination of sweet cherry cultivars based on electronic tongue potentiometric fingerprints |
title |
Discrimination of sweet cherry cultivars based on electronic tongue potentiometric fingerprints |
spellingShingle |
Discrimination of sweet cherry cultivars based on electronic tongue potentiometric fingerprints Rodrigues, Isabel Analysis of variance Biometric data Chemical data CIELAB color scale Cultivar discrimination Linear discriminant analysis Potentiometric taste sensor Simulated annealing algorithm Sweet cherry |
title_short |
Discrimination of sweet cherry cultivars based on electronic tongue potentiometric fingerprints |
title_full |
Discrimination of sweet cherry cultivars based on electronic tongue potentiometric fingerprints |
title_fullStr |
Discrimination of sweet cherry cultivars based on electronic tongue potentiometric fingerprints |
title_full_unstemmed |
Discrimination of sweet cherry cultivars based on electronic tongue potentiometric fingerprints |
title_sort |
Discrimination of sweet cherry cultivars based on electronic tongue potentiometric fingerprints |
author |
Rodrigues, Isabel |
author_facet |
Rodrigues, Isabel Rodrigues, Nuno Marx, Ítala Veloso, Ana C.A. Ramos, Ana Cristina Pereira, J.A. Peres, António M. |
author_role |
author |
author2 |
Rodrigues, Nuno Marx, Ítala Veloso, Ana C.A. Ramos, Ana Cristina Pereira, J.A. Peres, António M. |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Biblioteca Digital do IPB |
dc.contributor.author.fl_str_mv |
Rodrigues, Isabel Rodrigues, Nuno Marx, Ítala Veloso, Ana C.A. Ramos, Ana Cristina Pereira, J.A. Peres, António M. |
dc.subject.por.fl_str_mv |
Analysis of variance Biometric data Chemical data CIELAB color scale Cultivar discrimination Linear discriminant analysis Potentiometric taste sensor Simulated annealing algorithm Sweet cherry |
topic |
Analysis of variance Biometric data Chemical data CIELAB color scale Cultivar discrimination Linear discriminant analysis Potentiometric taste sensor Simulated annealing algorithm Sweet cherry |
description |
© 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. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-01-19T10:00:00Z 2020 2020-01-01T00:00:00Z |
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://hdl.handle.net/10198/23372 |
url |
http://hdl.handle.net/10198/23372 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Rodrigues, 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. 1-11 10.3390/app10207053 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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