Optimization of maceration conditions for improving the extraction of phenolic compounds and antioxidant effects of Momordica Charantia L. leaves through response surface methodology (RSM) and artificial neural networks (ANNs)

Basit Öğe Kaydı
dc.authorid0000-0003-4562-1719
dc.authorid0000-0001-5621-1788
dc.authorid0000-0002-5165-6013
dc.authorid0000-0001-6548-7823
dc.contributor.authorUysal, Şengül
dc.contributor.authorCvetanovic, Aleksandra
dc.contributor.authorZengin, Gökhan
dc.contributor.authorZekovic, Zoran
dc.contributor.authorMahomoodally, Mohamad Fawzi
dc.contributor.authorBera, Oskar
dc.date.accessioned2020-03-26T20:19:06Z
dc.date.available2020-03-26T20:19:06Z
dc.date.issued2019
dc.departmentSelçuk Üniversitesi, Fen Fakültesi, Biyoloji Bölümüen_US
dc.description.abstractThe main goals of this research were the chemical and biological characterization of the bitter melon (Momordica charantia) isolate obtained by traditional (maceration) extraction, as well as optimization of this process using response surface methodology (RSM) and artificial neural networks (ANNs). Experiments were performed using Box-Behnken experimental design on three levels and three variables: extraction temperature (20 degrees C, 40 degrees C, and 60 degrees C), solvent concentration (30%, 50%, and 70%) and extraction time (30, 60, and 90 min). The measurements consisted of 15 randomized runs with 3 replicates in a central point. The antioxidant activity of obtained extracts was determined by the 1,1-diphenyl-2-picrylhydrazyl (DPPH), cupric ion reducing antioxidant capacity (CUPRAC) and ferric reducing antioxidant power (FRAP) assays while chemical characterization was done in terms of the total phenolic content (TPC). The methodology shows positive influence of solvent concentration on all four observed outputs, while temperature showed a negative impact. RSM showed that the optimal extraction conditions were 20 degrees C, 70% methanol, and an extraction time of 52.2 min. Under these conditions, the TPCs were 20.66 milligrams of gallic acid equivalents (mg GAE/g extract), DPPH 30.22 milligrams of trolox equivalents (mg TE/g extract), CUPRAC 67.78 milligrams of trolox equivalents (mg TE/g extract), and FRAP 45.48 milligrams of trolox equivalents (mg TE/g extract). The neural network coupled with genetic algorithms (ANN-GA) was also used to optimize the conditions for each of the outputs separately. It is anticipated that results reported herein will establish baseline data and also demonstrate that that the present model can be applied in the food and pharmaceutical industries.en_US
dc.identifier.citationUysal, Ş., Cvetanović, A., Zengin, G., Zeković, Z., Mahomoodally, M. F., Bera, O. (2019). Optimization of Maceration Conditions for Improving the Extraction of Phenolic Compounds and Antioxidant Effects of Momordica Charantia L. Leaves Through Response Surface Methodology (RSM) and Artificial Neural Networks (ANNs). Analytical Letters, 52(13), 2150-2163.
dc.identifier.doi10.1080/00032719.2019.1599007en_US
dc.identifier.endpage2163en_US
dc.identifier.issn0003-2719en_US
dc.identifier.issn1532-236Xen_US
dc.identifier.issue13en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage2150en_US
dc.identifier.urihttps://dx.doi.org/10.1080/00032719.2019.1599007
dc.identifier.urihttps://hdl.handle.net/20.500.12395/38064
dc.identifier.volume52en_US
dc.identifier.wosWOS:000465997300001en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorZengin, Gökhan
dc.institutionauthorMahomoodally, Mohamad Fawzi
dc.language.isoenen_US
dc.publisherTAYLOR & FRANCIS INCen_US
dc.relation.ispartofANALYTICAL LETTERSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectMomordica charantiaen_US
dc.subjectAntioxidant propertiesen_US
dc.subjectArtificial neural network-genetic algorithmen_US
dc.subjectResponse surface methodologyen_US
dc.subjectTotal phenolic contenten_US
dc.titleOptimization of maceration conditions for improving the extraction of phenolic compounds and antioxidant effects of Momordica Charantia L. leaves through response surface methodology (RSM) and artificial neural networks (ANNs)en_US
dc.typeArticleen_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim
İsim:
Sengul UYSAL.pdf
Boyut:
2.46 MB
Biçim:
Adobe Portable Document Format
Açıklama:
Full Text Access
İndir

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Biyoloji/Makale Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu