- Gazi University Journal of Science Part A: Engineering and Innovation
- Volume:8 Issue:4
- Artificial Neural Network Predictive Modelling of luffa cylindrica Seed Oil Antioxidant Yield
Artificial Neural Network Predictive Modelling of luffa cylindrica Seed Oil Antioxidant Yield
Authors : Kenechi NWOSUOBİEOGU
Pages : 494-504
Doi:10.54287/gujsa.972137
View : 64 | Download : 9
Publication Date : 2021-12-30
Article Type : Research Paper
Abstract :This study applied artificial neural network insert ignore into journalissuearticles values(ANN); in evaluating the models for terpineol and polyphenol yield from luffa cylindrica seed oil. The experiment was carried out at a temperature insert ignore into journalissuearticles values(60-80oC);, time insert ignore into journalissuearticles values(4-6 hours);, and solvent/seed ratio insert ignore into journalissuearticles values(8-12 ml/g); with response as antioxidant yield. FTIR insert ignore into journalissuearticles values(Fourier Transform Infra-red Spectroscopy); revealed the presence of terpineol and polyphenol at peaks of 1461.1cm-1 and 3008.0cm-1 respectively. The ANN prediction indices are thus; terpineol insert ignore into journalissuearticles values(R2= 9.9999E-1, MSE=2.25766E-9); and polyphenol insert ignore into journalissuearticles values(R2=9.9999E-1, MSE=4.42588E-10);. This study reveals that the ANN technique can successfully predict antioxidants from luffa cylindrica seed oil.Keywords : ANN, Terpineol, Polyphenol, Antioxidant
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