Ultrasound Processing of Vinegar: Modelling the Impact on Bioactives and Other Quality Factors

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dc.authoridhttps://orcid.org/0000-0001-8694-0658en_US
dc.authoridhttps://orcid.org/0000-0002-7627-9867en_US
dc.contributor.authorYıkmış, Seydi
dc.contributor.authorAksu, Filiz
dc.contributor.authorSandıkçı Altunatmaz, Sema
dc.contributor.authorÇöl, Başak Gökçe
dc.date.accessioned2023-08-05T08:48:55Z
dc.date.available2023-08-05T08:48:55Z
dc.date.issued2021en_US
dc.departmentSağlık Bilimleri Fakültesien_US
dc.description.abstractIn recent years, non-thermal technology has been used for the enrichment of ultrasound bioactive components. For this purpose, it was applied to tomato vinegar and modeled with response surface methodology (RSM) and artificial neural network (ANN). At the end of the RSM, cupric reducing antioxidant capacity (68.64%), 1,1-diphenyl-2-picrylhydrazyl (62.47%), total flavonoid content (2.44 mg CE/mL), total phenolic content (12.22 mg GAE/mL), total ascorbic acid content (2.53 mg/100 mL) and total lycopene (5.44 µg/mL) were determined. The ANN model has higher prediction accuracy than RSM. The microstructure, microbiological properties, sensory analysis, ACE (angiotensin-converting–enzyme) inhibitor and antidiabetic effects of the ultrasound-treated tomato vinegar (UTV) (8.9 min and 74.5 amplitude), traditional tomato vinegar (TTV) and pasteurized tomato vinegar (PTV) samples were then evaluated. UTV was generally appreciated by the panelists. It was determined that the microbiological properties were affected by the ultrasound treatment. UTV was found to have more effective ACE inhibitor and antidiabetic properties than other vinegar samples. As a result, the bioactive components of tomato vinegar were enriched with ultrasound treatment and positive effects on health were determined.en_US
dc.identifier.doi10.3390/foods10081703en_US
dc.identifier.endpage15en_US
dc.identifier.issn2304-8158
dc.identifier.issue8en_US
dc.identifier.pmid34441481en_US
dc.identifier.scopus2-s2.0-85111646887en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1en_US
dc.identifier.urihttps://hdl.handle.net/11363/5165
dc.identifier.urihttps://doi.org/
dc.identifier.volume10en_US
dc.identifier.wosWOS:000689235300001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.institutionauthorÇöl, Başak Gökçe
dc.language.isoenen_US
dc.publisherMDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLANDen_US
dc.relation.ispartofFoodsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectresponse surface methodologyen_US
dc.subjectartificial neural networken_US
dc.subjectvinegaren_US
dc.subjectultrasounden_US
dc.subjectantidiabeticen_US
dc.subjectACE inhibitoren_US
dc.titleUltrasound Processing of Vinegar: Modelling the Impact on Bioactives and Other Quality Factorsen_US
dc.typeArticleen_US

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