Chinese Journal of Lasers, Volume. 42, Issue 5, 515004(2015)
Application of Fluorescence Spectroscopy and PSO-BP Neural Network in the Detection of Potassium Sorbate Concentration
Potassium sorbate, one of preservatives, has been used widely, but it will do harm to human health if it is overtaken. Fluorescence spectrum properties of potassium sorbate in aqueous solution and orange juice are studied. The results show that the fluorescence characteristic peak of potassium sorbate in aqueous solution exists at λex /λem = 375 nm/485 nm , the mixture of potassium sorbate and orange juice has a side peak at λex /λem = 470 nm/540 nm besides the fluorescence characteristic peak. In the mixture, there is mutual interference of fluorescence characteristic between potassium sorbate and orange juice, which makes the concentration detection of potassium sorbate more difficult. To determine the concentration of potassium sorbate in the mixture, back propagation neural network optimized by particle swarm optimization (PSO- BP) is applied. The average recovery rate of the 3 prediction samples is 98.97%, and the range in which the PSO-BP neural network can accurately measure the concentration of potassium sorbate in the mixture is 0.1~2.0 g/L. The prediction results indicate that the method combining fluorescence spectrum and PSO-BP neural network can effectively detect the concentration of potassium sorbate in orange juice.
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Wang Shutao, Chen Dongying, Wei Meng, Wang Xinglong, Wang Zhifang, Wang Jialiang. Application of Fluorescence Spectroscopy and PSO-BP Neural Network in the Detection of Potassium Sorbate Concentration[J]. Chinese Journal of Lasers, 2015, 42(5): 515004
Category: Spectroscopy
Received: Dec. 11, 2014
Accepted: --
Published Online: May. 6, 2015
The Author Email: Wang Shutao (wangshutao@ysu.edu.cn)