Modeling and Optimization of the Hot Compressed Water Extraction of Palm Oil Using Artificial Neural Network

JOURNAL OF CHEMICAL ENGINEERING OF JAPAN

Yoshiyuki Yamashita⁴  Mustafa Kamal Abdul Aziz²  Mohd Sharizan Md Sarip¹  Mohd Azizi Che Yunus³  Noor Azian Morad¹ 

[1] Shizen Conversion and Separation Technology (SHiZEN), iKohza, 
Universiti Teknologi Malaysia;Department of Chemical & Environmental Engineering, 
University of Nottingham Malaysia;Centre of Lipid Engineering Applied Research, Faculty of Chemical Engineering, 
Universiti Teknologi Malaysia;Department of Chemical Engineering, 
Tokyo University of Agriculture and Technology

关键词: Hot Compressed Water Extraction;    Palm Oil;    Artificial Neural Network;   

DOI  :  10.1252/jcej.15we251

来源: Maruzen Company Ltd

【 摘 要 】

References(30)Hot compressed water extraction (HCWE) is a promising green alternative to the screw press in the palm oil processing. In this study, the steady-state characteristic of the HCWE was modeled by using an artificial neural network (ANN). The overall oil yield and other outputs; β-carotene, α-tocopherol and α-tocotrienol concentration, were described by the pressure and temperature in the HCWE. The results show that the predicted yield and concentrations agree well with experimental data. These models were used to estimate the optimum conditions of the HCWE process.

【 授权许可】

Unknown