Discrimination of sweet cherry cultivars based on electronic tongue potentiometric fingerprints
Autor(a) principal: | |
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Data de Publicação: | 2020 |
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/1822/67672 |
Resumo: | 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 fingerprintssweet cherrybiometric dataCIELAB color scalechemical datapotentiometric taste sensoranalysis of variancelinear discriminant analysissimulated annealing algorithmcultivar discriminationScience & TechnologySweet 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 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), funded by the European Regional Development Fund under the scope of Norte2020—Programa Operacional Regional do Norte. Nuno Rodrigues also thanks the national funding by FCT–Foundation for Science and Technology, P.I., through the Institutional scientific employment program contract.info:eu-repo/semantics/publishedVersionMDPIUniversidade do MinhoRodrigues, IsabelRodrigues, NunoMarx, Ítala M. G.Veloso, Ana C. A.Ramos, Ana CristinaPereira, José AlbertoPeres, António M.20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/67672engRodrigues, Isabel; Rodrigues, Nuno; Marx, Ítala M. G.; Veloso, Ana C. A.; Ramos, Ana Cristina; Pereira, José Alberto; Peres, António M., Discrimination of sweet cherry cultivars based on electronic tongue potentiometric fingerprints. Applied Sciences-Basel, 10(20), 7053, 20202076-341710.3390/app10207053https://www.mdpi.com/2076-3417/10/20/7053info: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:RCAAP2023-07-21T12:48:55Zoai:repositorium.sdum.uminho.pt:1822/67672Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:47:15.637847Repositório 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 sweet cherry biometric data CIELAB color scale chemical data potentiometric taste sensor analysis of variance linear discriminant analysis simulated annealing algorithm cultivar discrimination Science & Technology |
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 M. G. Veloso, Ana C. A. Ramos, Ana Cristina Pereira, José Alberto Peres, António M. |
author_role |
author |
author2 |
Rodrigues, Nuno Marx, Ítala M. G. Veloso, Ana C. A. Ramos, Ana Cristina Pereira, José Alberto Peres, António M. |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Rodrigues, Isabel Rodrigues, Nuno Marx, Ítala M. G. Veloso, Ana C. A. Ramos, Ana Cristina Pereira, José Alberto Peres, António M. |
dc.subject.por.fl_str_mv |
sweet cherry biometric data CIELAB color scale chemical data potentiometric taste sensor analysis of variance linear discriminant analysis simulated annealing algorithm cultivar discrimination Science & Technology |
topic |
sweet cherry biometric data CIELAB color scale chemical data potentiometric taste sensor analysis of variance linear discriminant analysis simulated annealing algorithm cultivar discrimination Science & Technology |
description |
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 |
2020 |
dc.date.none.fl_str_mv |
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/1822/67672 |
url |
http://hdl.handle.net/1822/67672 |
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, António M., Discrimination of sweet cherry cultivars based on electronic tongue potentiometric fingerprints. Applied Sciences-Basel, 10(20), 7053, 2020 2076-3417 10.3390/app10207053 https://www.mdpi.com/2076-3417/10/20/7053 |
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.publisher.none.fl_str_mv |
MDPI |
publisher.none.fl_str_mv |
MDPI |
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 |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799133045800828928 |