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dc.contributor.author | Umaña, Mónica | es_ES |
dc.contributor.author | Llull, Laura | es_ES |
dc.contributor.author | Bon Corbín, José | es_ES |
dc.contributor.author | Eim, Valeria Soledad | es_ES |
dc.contributor.author | Simal, Susana | es_ES |
dc.date.accessioned | 2023-05-26T18:02:04Z | |
dc.date.available | 2023-05-26T18:02:04Z | |
dc.date.issued | 2022-12 | es_ES |
dc.identifier.issn | 2304-8158 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/193645 | |
dc.description.abstract | [EN] The use of artificial neural networks (ANNs) is proposed to optimize the formulation of stable oil-in-water emulsions (oil 6% w/w) with a flour made from orange by-products (OBF), rich in pectins (21 g/100 g fresh matter), in different concentrations (0.95, 2.38, and 3.40% w/w), combined with or without soy proteins (0.3 and 0.6% w/w). Emulsions containing OBF were stable against coalescence and flocculation (with 2.4 and 3.4% OBF) and creaming (3.4% OBF) for 24 h; the droplets' diameter decreased up to 44% and the viscosity increased up to 37% with higher concentrations of OBF. With the protein addition, the droplets' diameter decreased by up to 70%, and flocculation increased. Compared with emulsions produced with purified citrus pectins (0.2 and 0.5% w/w), OBF emulsions exhibited up to 32% lower viscosities, 129% larger droplets, and 45% smaller Z potential values. Optimization solved with ANNs minimizing the droplet size and the emulsion instability resulted in OBF and protein concentrations of 3.16 and 0.14%, respectively. The experimental characteristics of the optimum emulsion closely matched those predicted by ANNs demonstrating the usefulness of the proposed method. | es_ES |
dc.description.sponsorship | The authors would like to acknowledge the Spanish research agency (AEI) MCIN/AEI/10.13039/501100011033 for the financial support for the projects (PID2019-106148RR-C43 and PID2019-106148RRC42). | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation.ispartof | Foods | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Orange by¿products | es_ES |
dc.subject | Pectins | es_ES |
dc.subject | Emulsions | es_ES |
dc.subject | Artificial neural network | es_ES |
dc.subject | Optimization | es_ES |
dc.subject.classification | TECNOLOGIA DE ALIMENTOS | es_ES |
dc.title | Artificial Neural Networks to Optimize Oil-in-Water Emulsion Stability with Orange By-Products | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3390/foods11233750 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-106148RR-C42/ES/INTEGRACION DE SUBPRODUCTOS AGROALIMENTARIOS REVALORIZADOS EN UN MODELO DE ECONOMIA CIRCULAR: INTENSIFICACION DE PROCESOS Y EVALUACION DE SOSTENIBILIDAD/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-106148RR-C43/ES/INTEGRACION DE SUBPRODUCTOS AGROALIMENTARIOS REVALORIZADOS EN UN MODELO DE ECONOMIA CIRCULAR. ALIMENTOS VEGANOS CON VALOR AÑADIDO PARA LOS SECTORES AGROINDUSTRIAL Y HORECA/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural - Escola Tècnica Superior d'Enginyeria Agronòmica i del Medi Natural | es_ES |
dc.description.bibliographicCitation | Umaña, M.; Llull, L.; Bon Corbín, J.; Eim, VS.; Simal, S. (2022). Artificial Neural Networks to Optimize Oil-in-Water Emulsion Stability with Orange By-Products. Foods. 11(23):1-25. https://doi.org/10.3390/foods11233750 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3390/foods11233750 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 25 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 11 | es_ES |
dc.description.issue | 23 | es_ES |
dc.identifier.pmid | 36496559 | es_ES |
dc.identifier.pmcid | PMC9739075 | es_ES |
dc.relation.pasarela | S\481244 | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |