Artificial Neural Network Predictive Modelling of luffa cylindrica Seed Oil Antioxidant Yield

This study applied artificial neural network (ANN) in evaluating the models for terpineol and polyphenol yield from luffa cylindrica seed oil. The experiment was carried out at a temperature (60-80oC), time (4-6 hours), solvent/seed ratio (8-12 ml/g) with response as antioxidant yield. FTIR (Fourier Transform Infra-red Spectroscopy) revealed presence of peaks 1461.1cm-1 3008.0cm-1 respectively. ANN prediction indices are thus; (R2= 9.9999E-1, MSE=2.25766E-9) (R2=9.9999E-1, MSE=4.42588E-10). reveals that technique can successfully predict antioxidants