COMBINING ARTIFICIAL NEURAL NETWORK AND MOTH-FLAME OPTIMIZATION ALGORITHM FOR OPTIMIZATION OF ULTRASOUND-ASSISTED AND MICROWAVE-ASSISTED EXTRACTION PARAMETERS: BARK OF Pinus brutia

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dc.contributor.authorGurgen, Aysenur
dc.contributor.authorAtilgan, Basak
dc.contributor.authorYildiz, Sibel
dc.contributor.authorGonultas, Oktay
dc.contributor.authorImamoglu, Sami
dc.date.accessioned2026-02-12T21:05:04Z
dc.date.available2026-02-12T21:05:04Z
dc.date.issued2022
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractIn this study, the extraction parameters of Pinus brutia bark were optimized using a hybrid artificial intelligence technique. Firstly, the bark samples were extracted by ultrasound-assisted extraction and microwave-assisted extraction which are defined as 'green' extraction methods at different conditions. The selected extraction parameters for ultrasound-assisted extraction were 0:100; 20:80; 40:60; 80:20 (%) ethanol: water ratios; 40 degrees C, 60 degrees C extraction temperatures and 5 min, 10 min, 15 min, 20 min extraction times and for microwave-assisted extraction were 90, 180, 360, 600, 900 (W) microwave power, 0:100; 20:80; 40:60; 60:40; 80:20 (%) ethanol: water ratios. Then Stiasny number, condensed tannin content and reducing sugar content of all extracts were determined. Next, the prediction models were developed for each studied parameter using Artificial Neural Network. Finally, the extraction parameters were optimized using Moth-Flame Optimization Algorithm. After that optimization process, while the extraction time was the same (5 min), the ethanol: water ratio and extraction temperature values differed for the optimization of all studied assays of ultrasound-assisted extraction. Also, microwave power and ethanol: water ratio variables were found in different values for each assay of microwave-assisted extraction. The results showed that the Artificial Neural Network and Moth-Flame Optimization could be a novel and powerful hybrid approach to optimize the extraction parameters of Pinus brutia barks with saving time, cost, chemical and effort.
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [115R068]
dc.description.sponsorshipThe data used in this study was supported The Scientific and Technological Research Council of Turkey (TUBITAK) 115R068.
dc.identifier.doi10.4067/s0718-221x2022000100424
dc.identifier.issn0717-3644
dc.identifier.issn0718-221X
dc.identifier.scopus2-s2.0-85130046100
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.4067/s0718-221x2022000100424
dc.identifier.urihttps://hdl.handle.net/20.500.12885/6771
dc.identifier.volume24
dc.identifier.wosWOS:000789423300001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherUniv Bio-Bio
dc.relation.ispartofMaderas-Ciencia Y Tecnologia
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WoS_20260212
dc.subjectMicrowave-assisted extraction
dc.subjectmodelling
dc.subjectoptimization
dc.subjectPinus brutia
dc.subjectultrasound-assisted extraction
dc.titleCOMBINING ARTIFICIAL NEURAL NETWORK AND MOTH-FLAME OPTIMIZATION ALGORITHM FOR OPTIMIZATION OF ULTRASOUND-ASSISTED AND MICROWAVE-ASSISTED EXTRACTION PARAMETERS: BARK OF Pinus brutia
dc.typeArticle

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