Open AccessOPTIMIZATION OF OIL EXTRACTION FROM GARCINIA KOLA USING ARTIFICIAL NEURAL NETWORK AND RESPONSE SURFACE METHODOLOGY
Author(s) -
Sylvester Uwadiae,
Faith Oviesu,
Bamidele Victor Ayodele
Publication year - 2020
Publication title -
journal of engineering studies and research
Language(s) - English
Resource type - Journals
eISSN - 2344-4932
pISSN - 2068-7559
DOI - 10.29081/jesr.v26i2.171
Subject(s) - response surface methodology , extraction (chemistry) , artificial neural network , box–behnken design , garcinia kola , chromatography , volume (thermodynamics) , materials science , process engineering , biological system , mathematics , computer science , chemistry , artificial intelligence , engineering , physics , biology , quantum mechanics , genetics
The target of this investigation was to model and optimize selected process parameters when extracting oil from Garcinia kola. Artificial neural network (ANN) and Box-Behnken design (BBD) in response surface methodology (RSM) were used for the modelling and optimization of the process parameters. The optimized process values were 397.86 mL and 399.99 mL for solvent volume; 109.32 min and 107.55 min for extraction time; 72.64 g and 70 g for sample mass and maximum yields of 20.839 wt% and 20.488 wt% for RSM and ANN respectively. The highly positively correlated experimental and anticipated values validated the models.