Effects on quality characteristics of ultrasound-treated gilaburu juice using RSM and ANFIS modeling with machine learning algorithm

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dc.authorid, Aylin/0000-0002-5651-1366
dc.authoridYikmis, Seydi/0000-0001-8694-0658
dc.authoridTurkol, Melikenur/0000-0001-7354-9529
dc.authoridAadil, Rana Muhammad/0000-0002-0185-0096
dc.contributor.authorYikmis, Seydi
dc.contributor.authorAltan, Aylin Duman
dc.contributor.authorTurkol, Melikenur
dc.contributor.authorGezer, Goktug Egemen
dc.contributor.authorGanimet, Sennur
dc.contributor.authorAbdi, Gholamreza
dc.contributor.authorHussain, Shahzad
dc.date.accessioned2024-10-29T17:58:30Z
dc.date.available2024-10-29T17:58:30Z
dc.date.issued2024
dc.departmentTekirdağ Namık Kemal Üniversitesi
dc.description.abstractGilaburu (Viburnum opulus L.) is a red-colored fruit with a sour taste that grows in Anatolia. It is rich in various antioxidant and bioactive compounds. In this study, bioactive compounds and ultrasound parameters of ultrasound-treated gilaburu water were optimized by response surface methodology (RSM) and adaptive neurofuzzy inference system (ANFIS). As a result of RSM optimization, the independent ultrasound parameters were determined as an ultrasound duration of 10.7 min and an ultrasound amplitude of 53.3, respectively. The R2 values of the RSM modeling level were 99.93%, 98.54%, and 99.80%, respectively, and the R2 values of the ANFIS modeling level were 99.99%, 98.89%, and 99.87%, respectively. Some quality parameters of gilaburu juice were compared between ultrasound-treated gilaburu juice (UT-GJ), thermal pasteurized gilaburu juice (TPGJ), and control group (C-GJ). The quality parameters include bioactive compounds, phenolic compounds, minerals, and sensory evaluation. Bioactive compounds in the samples increased after ultrasound application compared to C-GJ and TP-GJ samples. The content of 15 different phenolic compounds was determined in Gilaburu juice samples, and the phenolic compound of UT-GJ samples increased compared to TP-GJ and C-GJ samples, except for gentisic acid. Ultrasound treatment applied to gilaburu juice enabled its bioactive compounds to hold more in the juice.
dc.description.sponsorshipKing Saud University, Riyadh, Saudi Arabia [RSPD2024R1073]
dc.description.sponsorshipThe authors appreciate the support from the Researchers Supporting Project number (RSPD2024R1073) , King Saud University, Riyadh, Saudi Arabia.
dc.identifier.doi10.1016/j.ultsonch.2024.106922
dc.identifier.issn1350-4177
dc.identifier.issn1873-2828
dc.identifier.pmid38805887
dc.identifier.scopus2-s2.0-85194130995
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.ultsonch.2024.106922
dc.identifier.urihttps://hdl.handle.net/20.500.11776/14358
dc.identifier.volume107
dc.identifier.wosWOS:001246202000002
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofUltrasonics Sonochemistry
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectGilaburu
dc.subjectUltrasound
dc.subjectANFIS
dc.subjectBioactive compounds
dc.subjectMachine learning
dc.titleEffects on quality characteristics of ultrasound-treated gilaburu juice using RSM and ANFIS modeling with machine learning algorithm
dc.typeArticle

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