反向传播-人工神经网络在辐照黑椒牛肉品质预测中的应用

Application of Backpropagation-Artificial Neural Network in Quality Prediction of Irradiated Black Pepper Beef

为探究不同辐照处理对贮藏过程中黑椒牛肉品质变化的影响,建立基于理化指标的多种品质预测模型。3~4 kGy的辐照剂量能够有效延缓黑椒牛肉在贮藏过程中的汁液流失、脂质氧化和蛋白质降解,保持其硬度和微观结构,在一定程度上增加呈鲜味(Asp)和甜味(Gly、Ala、Ser)游离氨基酸的含量。以辐照黑椒牛肉的汁液流失率、硫代巴比妥酸反应产物值、总挥发性盐基氮值、原肌球蛋白条带强度比率、肌球蛋白重链条带强度比率和总游离氨基酸含量为输入变量,优化了反向传播-人工神经网络(backpropagation-artificial neural network,BP-ANN)模型。训练函数为ReLU函数,隐藏层神经元个数为14个,迭代次数100次。结果表明,6-14-6 BP-ANN模型可以较好地预测辐照黑椒牛肉的品质变化,该模型在预测辐照肉制品的多种品质方面具有很大潜力。

To investigate the effects of different irradiation treatments on the quality of black pepper beef during storage,a backpropagation-artificial neural network(BP-ANN)model for predicting various quality attributes of black pepper beef was developed based on physicochemical indicators.Irradiation at a dose of 3–4 kGy effectively delayed the loss of juice,lipid oxidation,and protein degradation in black pepper beef during storage,maintained its hardness and microstructure,and increased the contents of umami(Asp)and sweet(Gly,Ala and Ser)amino acids.The BP-ANN model was optimized with the juice loss,thiobarbituric acid reactive substances(TBARS)value,total volatile basic nitrogen(TVB-N)content,tropomyosin band intensity ratio,myosin heavy chain band intensity ratio,and total free amino acid content of irradiated black pepper beef as input variables.The ReLU function was used as the activation function,with 14 neurons in the hidden layer and 100 iterations.The results showed that the 6-14-6 BP-ANN model could predict the quality changes of irradiated black pepper beef well,and have great potential in predicting various qualities of irradiated meat products.