食品科学 ›› 2017, Vol. 38 ›› Issue (18): 310-316.doi: 10.7506/spkx1002-6630-201718048

• 安全检测 • 上一篇    下一篇

基于电子鼻和改进无监督鉴别投影算法的大闸蟹新鲜度识别方法

朱培逸,徐本连,鲁明丽,施健,吕岗   

  1. (常熟理工学院电气与自动化工程学院,江苏?常熟 215500)
  • 出版日期:2017-09-25 发布日期:2017-09-04
  • 基金资助:
    江苏省产学研前瞻性联合研究项目(BY2016050-02);江苏省“六大人才高峰”项目(2014-NY-021); 常熟理工学院产学研前瞻性专项(QZ1502);常熟市科技发展计划项目(CR201711)

Application of Electronic Nose for Identifying the Freshness of Chinese Mitten Crab (Eriocheir sinensis) Based on Modified Unsupervised Discriminant Projection Algorithm

ZHU Peiyi, XU Benlian, LU Mingli, SHI Jian, Lü Gang   

  1. (School of Electric and Automatic Engineering, Changshu Institute of Technology, Changshu 215500, China)
  • Online:2017-09-25 Published:2017-09-04

摘要: 通过自制电子鼻系统采集活体大闸蟹的气味信息,采用流行学习算法对大闸蟹样本的多维特征响应进行降维,提取样本的低维特征向量,再利用反向传播神经网络实现对大闸蟹新鲜度的识别,并与理化指标挥发性盐基氮进行比较。结果表明,基于该算法的大闸蟹新鲜度识别的准确度可达到98.1%,且依据电子鼻技术与依据理化指标判断结果基本一致,因此采用电子鼻技术的大闸蟹新鲜度无损识别方法是可行的。

关键词: 大闸蟹, 新鲜度, 电子鼻, 无监督鉴别投影算法, 反向传播神经网络

Abstract: An electronic nose was designed to collect odor data of live Chinese mitten crab (Eriocheir sinensis) using a sensor array consisting of 7 commercial tin oxide gas sensors. To obtain a better feature vector for identifying different crabs, a modified unsupervised discriminant projection coupled with sample label information was proposed which could maintain the local and global structure and take advantage of the important label information to achieve optimal linear geometric projection. Then back-propagation neural network was used for modeling the quality changes of crabs during storage. At the same time, the total volatile basic nitrogen (TVB-N) of crab meat was measured and used as an indicator of crab freshness. The results showed that a high degree of accuracy in nondestructive identification of crab freshness was achieved with electronic nose based on this algorithm.

Key words: Chinese mitten crab, freshness, electronic nose, unsupervised discriminant projection algorithm, back-propagation neural network

中图分类号: