食品科学2024，Vol.45Issue(8)：228-237,10.DOI:10.7506/spkx1002-6630-20230514-122
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
摘要
Abstract
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.关键词
黑椒牛肉/60Co-γ射线/品质/反向传播-人工神经网络/预测模型Key words
black pepper beef/60Co-γ radiation/quality/backpropagation-artificial neural network/predictive model分类
轻工纺织引用本文复制引用
游云,黄晓霞,肖斯立,刘巧瑜,蓝碧锋,胡昕,吴俊师,杨娟,曾晓房..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[J].食品科学,2024,45(8):228-237,10.基金项目
广东省重点领域研发计划项目(2019B020212002) （2019B020212002）
广东省普通高校重点领域专项(2022ZDZX4016) （2022ZDZX4016）
广东省教育厅2020年广东省研究生教育创新计划项目(粤教研函[2020]1号) （粤教研函[2020]1号）
