EXTRACTION OF PHENOLIC COMPOUNDS FROM FENUGREEK SEEDS: MODELLING AND ANALYSIS USING ARTIFICIAL NEURAL NETWORKS

Authors : Selami BEYHAN, Hilal İŞLEROĞLU

Pages : 312-323

Doi:10.36306/konjes.1208658

View : 94 | Download : 92

Publication Date : 2023-06-01

Article Type : Research Paper

Abstract :This study introduces the modeling and analysis of the extraction process of bioactive compounds from fenugreek seeds in different solid-to-solvent ratios insert ignore into journalissuearticles values(0.5-60 g/L); and extraction times. Maceration was applied with agitation for the extraction processes and total phenolic compounds, total flavonoid content and antioxidant activity of the extracts were measured as experimental data. The amount of extractable phenolic compounds having antioxidant effect was increased by adjusting the solid-to-solvent ratio. According to obtained results, the highest values were determined as 12564.08±376.88 mg gallic acid/100 g dry sample, 7540.44±39.67 mg quercetin/100 g dry sample and 1904.80±17.43 mM Trolox/100 g dry sample for total phenolic compounds, total flavonoid content, and antioxidant activity, respectively. The extraction process was modeled using standard Artificial Neural Networks insert ignore into journalissuearticles values(ANN); and Pi-Sigma Neural-Networks insert ignore into journalissuearticles values(PSNN);. The PSNN model had a higher prediction efficiency with lower RMSE insert ignore into journalissuearticles values(%); values varied between 0.94% and 1.30% for both training and testing.
Keywords : Çemen otu tohumu, fenolik bileşikler, antioksidan aktivitesi, modelleme, yapay sinir ağları