基于电子鼻的花生有害霉菌种类识别及侵染程度定量检测

针对花生霉变传统分析方法操作繁琐、时效性差等不足,该研究拟利用电子鼻气体传感技术建立起花生有害霉菌污染的快速检测方法。辐射灭菌花生籽粒分别接种5种谷物中常见有害霉菌（黄曲霉3.17、黄曲霉3.395 0、寄生曲霉3.395、寄生曲霉3.012 4和赭曲霉3.648 6）,并于26℃、80%相对湿度条件下储藏9 d至严重霉变。利用电子鼻气体传感器获取不同储藏时期（0、3、6、9 d）花生样品的整体挥发性气味信息。最后,结合多元统计分析方法对电子鼻传感器响应信号进行特征提取,建立了花生中有害霉菌污染程度的定性定量分析模型。结果显示,主成分分析法（principal component analys...

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Bibliographic Details
Published in农业工程学报 Vol. 32; no. 24; pp. 297 - 302
Main Author 沈飞 刘鹏 蒋雪松 邵小龙 万忠民 宋伟
Format Journal Article
LanguageChinese
Published 南京财经大学食品科学与工程学院，南京 210023 2016
江苏省现代粮食流通与安全协同创新中心，南京 210023%南京林业大学机械电子工程学院,南京,210037
Subjects
农作物
快速检测
有害霉菌
模型
特征提取
电子鼻
花生
models
电子鼻
模型
electronic nose
crops
有害霉菌
peanuts
harmful fungi
特征提取
农作物
feature extraction
快速检测
rapid detection
花生
Online AccessGet full text
ISSN1002-6819
DOI10.11975/j.issn.1002-6819.2016.24.040

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Summary:针对花生霉变传统分析方法操作繁琐、时效性差等不足,该研究拟利用电子鼻气体传感技术建立起花生有害霉菌污染的快速检测方法。辐射灭菌花生籽粒分别接种5种谷物中常见有害霉菌（黄曲霉3.17、黄曲霉3.395 0、寄生曲霉3.395、寄生曲霉3.012 4和赭曲霉3.648 6）,并于26℃、80%相对湿度条件下储藏9 d至严重霉变。利用电子鼻气体传感器获取不同储藏时期（0、3、6、9 d）花生样品的整体挥发性气味信息。最后,结合多元统计分析方法对电子鼻传感器响应信号进行特征提取,建立了花生中有害霉菌污染程度的定性定量分析模型。结果显示,主成分分析法（principal component analysis,PCA）可成功区分不同霉菌侵染程度的花生样品,线性判别分析（linear discriminant analysis,LDA）模型对样品不同储藏天数判别的准确率均达到或接近100%。花生中菌落总数的偏最小二乘回归分析（partial least squares regression,PLSR）模型的预测决定系数和预测相对均方根误差分别达到0.814 5和0.244 0 lg（CFU/g）。结果表明,应用电子鼻技术快速检测储藏期间花生霉变状况具有一定可行性,可为利用气味信息实现粮食霉菌污染的在线监测提供理论参考。
Bibliography:Shen Fei1,2, Liu Peng3, Jiang Xuesong3, Shao Xiaolong1,2, Wan Zhongmin1,2, Song Wei1,2 （1. College of Food Science and Engineering, Nanjing University of Finance and Economics, Nanjing 210023, China; 2. Collaborative Innovation Center for Modern Grain Circulation and Safety, Nanjing 210023, China; 3. College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China）
11-2047/S
crops; models; feature extraction; electronic nose; peanuts; harmful fungi; rapid detection
Current methods for fungi contamination determination in peanuts are usually labor-intensive and time-consuming.In this paper,a new method for rapid detection of the contamination by harmful fungi species in peanut kernels based on electronic nose（E-nose） technology was investigated.Peanut samples were firstly irradiated by Co-60 gamma radiation with a dose of 15 k Gy to kill all fungi on or within kernels.After irradiation,clean and sterile peanuts were placed in moist chambers and inoculated with 5 different spore
ISSN:1002-6819
DOI:10.11975/j.issn.1002-6819.2016.24.040