模糊神经网络应用于食用果酱的可行性研究

Feasibility Study on Application of Fuzzy Neural Network in Edible Jam

研究了pH值、萃取温度、萃取时间和样品中氯化钠浓度等不同参数萃取条件对果酱中防腐剂萃取效果的影响,并建立了模糊神经网络模型对果酱中的防腐剂种类进行预测。结果表明:在pH值为3.3,萃取温度为室温,样品中氯化钠浓度为34%,萃取时间达到90 min时,果酱中的防腐剂萃取效果最好。通过建立模糊神经网络模型,模型结构参数为输入层4,输出层5,最小训练速率0.1,动态参数0.6。对果酱中防腐剂的类型进行预测,试验结果表明模糊神经网络模型可以用于预测果酱中所含防腐剂的种类。

The effects of extraction conditions for different parameters such as pH value,extraction temperature,extraction time and NaCl concentration in sample on the extraction effect of preservatives in jam are studied.The fuzzy neutral network is established to predict the types of preservatives in jam.The results show that the extraction effect of preservatives in jam is the best when pH is 3.3,at room temperature,NaCl concentration is 34%,extraction time is 90 min.A fuzzy neural network model is established,the structural parameters of the model are input layer of 4,output layer of 5,the minimum training rate of 0.1 and dynamic parameter of 0.6.The experimental results show that the fuzzy neural network model can be used to predict the types of preservatives in jam.