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Citation: LIU Hai-Chen, ZHUO Jin-Wu, WU Guo-Guang. Optimization of Extraction Conditions of Caffeine in Tea Based on Artificial Neural Network[J]. Chinese Journal of Applied Chemistry, ;2007, 24(4): 457-460. shu

Optimization of Extraction Conditions of Caffeine in Tea Based on Artificial Neural Network

1.
School of Chemical Engineering and Technology, China University of Mining & Technology, Xuzhou 221008

Corresponding author: LIU Hai-Chen,
Received Date: 3 June 2006
Available Online: 25 July 2006
Fund Project: 中国矿业大学科研基金赞助项目(2006B014) (2006B014)

This paper reports the influences of extraction time,the ratio of solid-liquid,solvent pH and experiment temperature of caffeine extraction yield from tea.Orthogonal experiment was implemented based on single factor experiment.The optimum extraction parameters are 80℃,90 minutes,a liquid-feed ratio of 30:1 and pH=7.Experimental data were subjected to multivariate first-order regression and multivariate quadratic regression,and two regressing equations were obtained.At last,a neural network model based on the orthogonal experiment data was established to obtain the optimum extraction parameters, namely,100℃,115 minutes,a liquid-feed ratio of 41:1 and pH=4.5,and the experimental result based on the parameters from the artificial neural network is better than that based on orthogonal experiment.
- caffeine,
- extraction conditions,
- optimization,
- artificial nerve network
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