International Journal of Modern Science and Technology
June 2018, Vol. 3, No. 6, pp 138-144.
Ultrasonic assisted extraction of biooil from Ricinus communis seeds: Optimization using Response Surface Methodology and Artificial Neural Network
G. Baskar¹՚*, N. Mohanapriya¹, S. Roselin Nivetha¹, R. Saravanathamizhan²
¹Department of Biotechnology, St. Joseph’s College of Engineering, Chennai – 600 119. India.
²Department of Chemical Engineering, A. C. Technology, Anna University, Chennai- 600025. India.
*Corresponding author’s e-mail: firstname.lastname@example.org
Currently, there is high energy demand due to fast depletion of fossil fuel resources. Biofuels are the best alternative sources to meet the future energy demand. The present work was focused on optimization of ultrasonic assisted extraction of biooil from Ricinus communis seeds using Response Surface Methodology (RSM) and Artificial Neural Network (ANN) linked Genetic Algorithm (GA). Extraction parameters such as solvent concentration, mass of seed, extraction time and temperature were optimized under the constant influence of ultrasonic bath at 50 KHz. The RSM and ANN predicted biooil yields were compared to the experimental yield. The ANN model was found more efficient than RSM. The maximum biooil yield of 55.23% was obtained for optimal solvent concentration of 8 (v/w), mass of seed of 4 g, extraction time of 40 min at 40°C under the ultrasonic bath.
Keywords: Ultrasonic extraction; Ricinus communis seeds; Biooil; Optimization; Artificial Neural Network.
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