食品科学

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应用PEN3型电子鼻传感器快速检测食源性致病菌

陈丽萍1,徐茂琴2,何红萍1,李 晔1,*   

  1. 1.宁波大学海洋学院,浙江 宁波 315211;2.宁波城市职业技术学院,浙江 宁波 315100
  • 出版日期:2014-04-25 发布日期:2014-05-13
  • 通讯作者: 李 晔
  • 基金资助:

    海洋公益性行业科研专项(201005016;201105007)

Application of PEN3 Electronic Nose Sensor for Rapid Detection of Food-Borne Pathogenic Bacteria

CHEN Li-ping1, XU Mao-qin2, HE Hong-ping1, LI Ye1,*   

  1. 1. School of Marine Science, Ningbo University, Ningbo 315211, China;
    2. Ningbo City College of Vocational Technology, Ningbo 315100, China
  • Online:2014-04-25 Published:2014-05-13
  • Contact: LI Ye

摘要:

为研究化学传感器在食源性致病菌快速检测中的应用,利用基于金属氧化物传感元件阵列的PEN3型电子 鼻传感器,根据其对不同食源性致病菌产生代谢产物的差异响应。对金黄色葡萄球菌、大肠杆菌、粪链球菌、单增 李斯特菌这4 种常见食源性致病菌在培养2、4、6、8、10 h以及稀释103 、105、107 倍后进行PEN3化学传感器响应 实验,建立指纹图谱。通过聚类分析、主成分分析(principal component analysis,PCA)、线性判别式分析(linear discriminant analysis,LDA)等方法,确定化学传感器对不同培养时间、不同浓度细菌是否产生有效响应。结果表 明,PCA和LDA这两种模式识别方法能够很好地将不同培养时间的细菌培养液区分开来,使组间变异和组内变异的 比率达到最大,并在较低浓度条件下,4 种食源性致病菌仍有较高的区分度,这表明化学传感器技术检测低浓度致 病菌具有一定可行性。

关键词: PEN3型电子鼻, 食源性致病菌, 主成分分析, 线性判别式分析

Abstract:

Four species of common food-borne pathogenic bacteria including Staphylococcus aureus, Escherichia coli,
Streptococcus fecal and Listeria monocytogenes were detected using a metal oxide sensor-based portable electronic nose
(PEN3) according to its different response to bacterial metabolites. Various fingerprints were established for the four
bacteria cultured for 2, 4, 6, 8, and 10 h as well as diluted 103, 105 and 107 times, respectively. The responses of PEN3 to
bacteria under different conditions of incubation time and concentration were analyzed using cluster analysis, principal
component analysis (PCA) and linear discriminant analysis (LDA). Results showed that volatile bacterial metabolites at
different incubation times could be well distinguished by PCA and LDA with the smallest inter- to intra-group variation
ratio. Meanwhile, a significant distinction among these four bacteria was observed even at lower concentration. These results
suggest that chemical sensor technology is feasible in detecting pathogenic bacteria at low concentrations.

Key words: PEN3 electronic nose, food-borne pathogenic bacteria, principal component analysis, linear discriminant analysis

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