dc.contributor.author | Pérez González, Clara | |
dc.contributor.author | Salvo Comino, Coral | |
dc.contributor.author | Martín Pedrosa, Fernando | |
dc.contributor.author | Guimarães Dias, Luís | |
dc.contributor.author | Rodríguez Pérez, Miguel Ángel | |
dc.contributor.author | García Cabezón, Ana Cristina | |
dc.contributor.author | Rodríguez Méndez, María Luz | |
dc.date.accessioned | 2021-10-19T08:33:14Z | |
dc.date.available | 2021-10-19T08:33:14Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Frontiers in Chemistry, 2021, vol. 9 | es |
dc.identifier.issn | 2296-2646 | es |
dc.identifier.uri | https://uvadoc.uva.es/handle/10324/49160 | |
dc.description | Producción Científica | es |
dc.description.abstract | A portable potentiometric electronic tongue (PE-tongue) was developed and applied to
evaluate the quality of milk with different fat content (skimmed, semi-skimmed, and whole)
and with different nutritional content (classic, calcium-enriched, lactose-free, folic
acid–enriched, and enriched in sterols of vegetal origin). The system consisted of a
simplified array of five sensors based on PVC membranes, coupled to a data logger.
The five sensors were selected from a larger set of 20 sensors by applying the genetic
algorithm (GA) to the responses to compounds usually found in milk including salts (KCl,
CaCl2, and NaCl), sugars (lactose, glucose, and galactose), and organic acids (citric acid
and lactic acid). Principal component analysis (PCA) and support vector machine (SVM)
results indicated that the PE-tongue consisting of a five-electrode array could successfully
discriminate and classify milk samples according to their nutritional content. The PEtongue
provided similar discrimination capability to that of a more complex system formed
by a 20-sensor array. SVM regression models were used to predict the physicochemical
parameters classically used in milk quality control (acidity, density, %proteins, %lactose,
and %fat). The prediction results were excellent and similar to those obtained with a much
more complex array consisting of 20 sensors. Moreover, the SVM method confirmed that
spoilage of unsealed milk could be correctly identified with the simplified system and the
increase in acidity could be accurately predicted. The results obtained demonstrate the
possibility of using the simplified PE-tongue to predict milk quality and provide information
on the chemical composition of milk using a simple and portable system. | es |
dc.format.mimetype | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Frontiers Media | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject.classification | Potentiometric electronic tongue | es |
dc.subject.classification | Milk | es |
dc.subject.classification | Dairy | es |
dc.subject.classification | Fat content | es |
dc.subject.classification | Lactose | es |
dc.title | Analysis of milk using a portable potentiometric electronic tongue based on five polymeric membrane sensors | es |
dc.type | info:eu-repo/semantics/article | es |
dc.rights.holder | © 2021 Frontiers Media | es |
dc.identifier.doi | 10.3389/fchem.2021.706460 | es |
dc.relation.publisherversion | https://www.frontiersin.org/articles/10.3389/fchem.2021.706460/full | es |
dc.identifier.publicationtitle | Frontiers in Chemistry | es |
dc.identifier.publicationvolume | 9 | es |
dc.peerreviewed | SI | es |
dc.description.project | Ministerio de Asuntos Económicos y Transformación Digital y FEDER (grant RTI 2018-097990-B-100) | es |
dc.description.project | Junta de Castilla y Leon-FEDER (grant VA275P18) and (Infraestructuras Red de Castilla y León (INFRARED UVA01) | es |
dc.identifier.essn | 2296-2646 | es |
dc.rights | Atribución 4.0 Internacional | * |
dc.type.hasVersion | info:eu-repo/semantics/publishedVersion | es |
dc.subject.unesco | 22 Física | es |
dc.subject.unesco | 23 Química | es |