Optimization of Extraction Parameters of Ethanol Extracts of Propolis Samples Using Artificial Neural Network and Moth-Flame Optimization Algorithm

Basit Öğe Kaydı
dc.authoridKARA, Yakup/0000-0003-3121-5023
dc.contributor.authorGurgen, Aysenur
dc.contributor.authorSerencam, Huseyin
dc.contributor.authorKara, Yakup
dc.contributor.authorCan, Zehra
dc.contributor.authorYildiz, Sibel
dc.date.accessioned2024-10-04T18:52:33Z
dc.date.available2024-10-04T18:52:33Z
dc.date.issued2021
dc.departmentBayburt Üniversitesien_US
dc.description.abstractIn this study, the optimum values of propolis ethanol extracts parameters were determined with the use of single and multi-objective optimization procedures. The euclidean distance approach was used in the multi-objective optimization process. Firstly, propolis was extracted using water with ethanol contents 40, 50, 60, 70 and 80% for 8, 10, 12, 16, 20 and 24 h. Then, total phenolic content (TPC) and ferric reducing antioxidant power (FRAP) activities of all extracts were determined. With the obtained data a prediction model was produced with the use of artificial neural networks (ANN), and optimization was performed using a moth-flame (MFO) algorithm. The best prediction models for the TPC and FRAP were observed in 2-5-1 and 2-5-1 network architecture with the mean absolute percentage error (MAPE) values, 5.126 and 2.451%, respectively. For maximum TPC, the extraction parameters were determined as ethanol content 57.5% and extraction time 13.56 h. To maximize FRAP, the optimized extraction parameters were ethanol content 72.03% and extraction time 18.04 h. The optimum extraction conditions for both maximum values of the studied assays were ethanol content 70.03% and extraction time 16.93 h. The study concluded that the integrated ANN and MFO algorithm system can be used in single and multi-objective optimization of extraction parameters. The established optimization model can save time, money, labor and energy.en_US
dc.identifier.doi10.2478/jas-2021-0018
dc.identifier.endpage241en_US
dc.identifier.issn1643-4439
dc.identifier.issn2299-4831
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85118476588en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage229en_US
dc.identifier.urihttps://doi.org/10.2478/jas-2021-0018
dc.identifier.urihttp://hdl.handle.net/20.500.12403/3550
dc.identifier.volume65en_US
dc.identifier.wosWOS:000735473300003en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSciendoen_US
dc.relation.ispartofJournal of Apicultural Scienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectartificial neural networken_US
dc.subjectextraction parametersen_US
dc.subjectmodellingen_US
dc.subjectoptimizationen_US
dc.subjectpropolisen_US
dc.titleOptimization of Extraction Parameters of Ethanol Extracts of Propolis Samples Using Artificial Neural Network and Moth-Flame Optimization Algorithmen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu