文章摘要
熊子怡,王小梅,潘嘹,卢立新,唐亚丽,王军.塑料包装材料表面大肠杆菌滋生影响因素研究[J].包装工程,2024,45(7):31-37.
XIONG Ziyi,WANG Xiaomei,PAN Liao,LU Lixin,TANG Yali,WANG Jun.Factors Affecting the Growth of Escherichia Coli on Plastic Packaging Surface[J].Packaging Engineering,2024,45(7):31-37.
塑料包装材料表面大肠杆菌滋生影响因素研究
Factors Affecting the Growth of Escherichia Coli on Plastic Packaging Surface
投稿时间:2024-01-05  
DOI:10.19554/j.cnki.1001-3563.2024.07.005
中文关键词: 大肠杆菌  塑料包装材料  正交试验  BP神经网络  生物膜
英文关键词: Escherichia coli  plastic packaging material  orthogonal experiment  BP neural network  biofilm
基金项目:江苏省食品先进制造装备技术重点实验室自主研究课题(FMZ202202)
作者单位
熊子怡 江南大学江苏 无锡 214122 
王小梅 江南大学江苏 无锡 214122 
潘嘹 江南大学江苏 无锡 214122
江苏省食品先进制造装备技术重点实验室江苏 无锡 214122 
卢立新 江南大学江苏 无锡 214122
江苏省食品先进制造装备技术重点实验室江苏 无锡 214122 
唐亚丽 江南大学江苏 无锡 214122
江苏省食品先进制造装备技术重点实验室江苏 无锡 214122 
王军 江南大学江苏 无锡 214122
江苏省食品先进制造装备技术重点实验室江苏 无锡 214122 
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中文摘要:
      目的 选择大肠杆菌为典型致病菌,分析不同塑料包装材料(聚乙烯、聚丙烯、聚酰胺、聚对苯二甲酸乙二酯)、营养状况与温湿度下包装表面大肠杆菌的滋生情况。方法 通过正交试验法分析各因素对大肠杆菌在包装表面滋生的影响规律。着重研究不同塑料材料表面大肠杆菌生物膜附着的影响因素,通过相关性分析确定模型输入参数;并基于这些参数采用反向传播神经网络(BP神经网络)建立不同塑料材料表面大肠杆菌菌落数的预测模型。结果 温度对大肠杆菌在材料表面的生长影响最大,其次为营养状况,材料和相对湿度的影响相对较小。塑料材料的水接触角、表面能、粗糙度和营养肉汤接触角是影响材料表面大肠杆菌生物膜附着的主要因素,基于这些因素建立的塑料材料表面大肠杆菌菌落数的神经网络预测模型的R²超过0.95,具有极高的预测精度。结论 该研究提出了塑料包装材料表面大肠杆菌滋生的关键环境控制因素,并为食品包装材料的选择提供了参考,从而为提升食品安全提供理论依据。
英文摘要:
      The work aims to select Escherichia coli (E. coli) as the typical pathogen to study the effect of different plastic packaging materials (polyethylene, polypropylene, polyamide, polyethylene terephthalate), nutritional status and temperature and humidity on the growth of E. coli on the plastic packaging surface. The effects of various factors on the growth of E. coli on the packaging surface were analyzed by orthogonal experimental method. Focusing on the factors affecting the attachment of E. coli biofilm on the surface of different plastic materials, the model input parameters were determined by correlation analysis. Based on these factors, a prediction model for the number of E. coli colonies on the surface of different plastic materials was established with back propagation neural network (BP neural network). The temperature had the greatest effect on the growth of E. coli on the material, followed by the nutritional status, and the material and relative humidity had relatively small effect. Water contact angle, surface energy, roughness and nutrient broth contact angle of plastic materials were the main factors affecting E. coli biofilm attachment on material surfaces. The BP neural network prediction model for the number of E. coli colonies on the surface of plastic materials based on these factors had a goodness-of-fit of more than 0.95, which had a very high prediction accuracy. This study proposes key environmental control factors for the growth of E. coli on the surface of plastic packaging materials and provides a reference for the selection of food packaging materials, thus providing a theoretical basis for enhancing food safety.
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