Prediction of the Contents of Four Polycyclic Aromatic Hydrocarbons in Smoked Sausage Using Back Propagation Neural Network Optimized by Particle Swarm Optimization Algorithm
XING Wei, LIU Xingyun, XU Zhaoyang, HUI Teng, WANG Shiyu, CAI Kezhou, ZHOU Hui, CHEN Conggui, XU Baocai
1.Engineering Research Center of Agricultural Bio-Chemicals, Ministry of Education, Hefei University of Technology, Hefei 230009, China; 2.Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Abstract：A predictive model based on a back propagation artificial neural network (BP-ANN) optimized by particle swarm optimization (PSO) algorithm was developed to predict the contents of four polycyclic aromatic hydrocarbons (PAHs) (benzo(a)pyrene, benzo(a)anthracene, benzo(b)fluoranthene, and chrysene) in smoked sausage. Smoking temperature, smoking time, fat/lean meat ratio and smoked sausage color (a* and b* values) were used as input layer parameters, and the measured contents of four PAHs as output layer parameters. The PSO-BP-ANN model was used to optimize the initial weight and threshold to obtain the best parameters. The results showed that the mean square error (MSE) of the proposed predictive model was 0.018, and the correlation coefficients (R2) for training, validation, test and global data sets were 0.951, 0.929, 0.933 and 0.940 respectively. All these parameters were better that those of the BP-ANN model, indicating that the PSO-BP-ANN model had better accuracy and robustness.
邢 巍，刘兴运，许朝阳，惠 腾，王石宇，蔡克周，周 辉，陈从贵，徐宝才. 利用粒子群算法优化反向传播人工神经网络模型预测熏肠中4种多环芳烃含量[J]. 肉类研究, 2022, 36(1): 34-40.
XING Wei, LIU Xingyun, XU Zhaoyang, HUI Teng, WANG Shiyu, CAI Kezhou, ZHOU Hui, CHEN Conggui, XU Baocai. Prediction of the Contents of Four Polycyclic Aromatic Hydrocarbons in Smoked Sausage Using Back Propagation Neural Network Optimized by Particle Swarm Optimization Algorithm. Meat Research, 2022, 36(1): 34-40.
2022, Vol. 36 
