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基于电子鼻的猪肉新鲜度的检测
引用本文:周红标,张宇林,李珊,夏云. 基于电子鼻的猪肉新鲜度的检测[J]. 现代食品科技, 2013, 29(6): 1386-1389
作者姓名:周红标  张宇林  李珊  夏云
作者单位:淮阴工学院电子与电气工程学院,江苏淮安 223003;淮阴工学院电子与电气工程学院,江苏淮安 223003;淮阴工学院电子与电气工程学院,江苏淮安 223003;淮阴工学院电子与电气工程学院,江苏淮安 223003
基金项目:国家自然科学基金(61203056)
摘    要:为了探索电子鼻对猪肉新鲜度检测的可能性,以STM32和CC2430为核心设计了新型无线电子鼻,并对5种不同新鲜度的猪肉样品进行了分析。对数据进行平滑处理后提取稳态响应值,并分别利用主成分分析和概率神经网络建立新鲜度识别模型。结果表明,主成分分析的前2个主元累计贡献率达92.79%,分类效果明显;概率神经网络模型识别率达到100%。

关 键 词:电子鼻;猪肉新鲜度;主成分分析;概率神经网络
收稿时间:2013-01-10

Detection of Pork Freshness using a Novel Wirless Electronic Nose
ZHOU Hong-biao,ZHANG Yu-lin,LI Shan and XIA Yun. Detection of Pork Freshness using a Novel Wirless Electronic Nose[J]. Modern Food Science & Technology, 2013, 29(6): 1386-1389
Authors:ZHOU Hong-biao  ZHANG Yu-lin  LI Shan  XIA Yun
Affiliation:Faculty of Electronic and Electrical Engineering,Huaiyin Institute of Tech.,Huaian 223003,China;Faculty of Electronic and Electrical Engineering,Huaiyin Institute of Tech.,Huaian 223003,China;Faculty of Electronic and Electrical Engineering,Huaiyin Institute of Tech.,Huaian 223003,China;Faculty of Electronic and Electrical Engineering,Huaiyin Institute of Tech.,Huaian 223003,China
Abstract:The detecting possibility of a novel wineless electronic nose were explored for 5 different freshness pork samples, which was designed with the STM32 and CC2430. Data processing included extracting the steady-state response after smoothing, and using principal component analysis and probabilistic neural network to establish model for freshness recognition. The results showed that contribution rate of the first two principal components total reached 92.79%. Classification effect is obvious and the identification rate of probabilistic neural network model achieved 100%.
Keywords:electronic nose   pork freshness   principal component analysis   probabilistic neural network
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