超高压处理牡蛎灭菌实验研究及人工神经网络模拟
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摘要
超高压灭菌技术是一项具有广阔应用前景的食品加工新技术。本文以牡蛎为研究对象,通过实验对影响超高压灭菌效果的处理因素(压力、保压时间、温度、施压方式等)进行了考察与评价。实验结果表明:压力、保压时间对灭菌效果影响显著,随着压力的增大和时间的增长,细菌的灭活率增大。温度、施压方式等因素对牡蛎中菌群总数的灭活率影响不大。同时,本文将人工神经网络(ANN)应用到超高压食品处理研究中,利用BP网络模拟超高压灭菌效果,与实验结果比较,测试平均相对误差0.91%,模拟相对误差小于1.8%,模拟准确。研究结果对牡蛎的超高压处理工艺具有一定的参考价值。
The ultra-high pressure sterilization technology was used for elimination of microorganism in oysters. Effects of key factors on the efficiency of ultra-high pressure sterilization, including processing pressure, sustaining time, temperature and pressure-exerting mode, were studied. Results showed that that increase of the processing pressure and sustaining time improved the reductions of microorganisms. However, temperature and exertion of pressure showed little effects on the decrease of the total bacteria in oyster. Besides, the artificial neural network (ANN) was applied to the simulation of ultra-high pressure sterilization of oysters. Results showed that RSD of the experimental test were 0.91% and that of the ANN simulation was 1.8%, respectively. The study provided some valuable references for optimization of high pressure sterilization process.
The ultra-high pressure sterilization technology was used for elimination of microorganism in oysters. Effects of key factors on the efficiency of ultra-high pressure sterilization, including processing pressure, sustaining time, temperature and pressure-exerting mode, were studied. Results showed that that increase of the processing pressure and sustaining time improved the reductions of microorganisms. However, temperature and exertion of pressure showed little effects on the decrease of the total bacteria in oyster. Besides, the artificial neural network (ANN) was applied to the simulation of ultra-high pressure sterilization of oysters. Results showed that RSD of the experimental test were 0.91% and that of the ANN simulation was 1.8%, respectively. The study provided some valuable references for optimization of high pressure sterilization process.
引文
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[2]张智翠.太平洋牡蛎品质的季节性变化及贮藏过程中的生化变化(硕士学位论文)[D].中国海洋大学,2006
[3]Andrews W H,Diggs,C D,Presnell M H,et al.Comparative validity of members of the total coliform and fecal coliform group for indicating the presence of Salmonanella in the eastern oysters[J].Milk Food Technol,1975,38:453-458
[4]夏远景,薄纯智.超高压食品处理技术[J].食品与药品,2006,8(2):62-67
[5]励建荣,王泓.超高压技术在食品工业中的应用及前景[J].现代食品科技,2006,22(1):171-180
[6]于山,王海霞等.三层BP神经网络地震灾害人员伤亡预测模型[J].地震工程与工程振动,2005,25(6):113-117
[7]银建中.基于人工神经网络的超临界流体萃取模拟方法研究(博士学位论文)[D].大连:大连理工大学,2002
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