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浙江大学学报（农业与生命科学版）
  2011, Vol. 37 Issue (6): 670-676    DOI: 10.3785/j.issn.1008-9209.2011.06.012
Food sciences     
Detection for rice odors and identification of varieties based on electronic nose technique
HU Gui‐xian１ , WANG Jun２ , WANG Jian‐jun３ , WANG Xiao‐li１
1 . Institute of Quality and Standards for Agricultural Products , Zhejiang Academy of Agricultural Sciences , Hangzhou 310021 , China ; 2 . Department of Biosystems Engineering , School of Biosystems Engineering and Food Science , Zhejiang University , Hangzhou 310058 , China ; 3 . Institute of Crops and Utilization of Nuclear Technology , Zhejiang Academy of Agricultural Sciences , Hangzhou 310021 , China
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Abstract  An investigation was made to distinguish five rice varieties with PEN ２ electronic nose . The matched experiment factors including the sample mass , headspace volume and generated time were studied . The response signals of electronic nose (e‐nose) were analyzed in various sampling conditions by single‐factor analysis of variance . The results showed that the signals of e‐nose were stable under the condition with the sample mass of １０ g , headspace volume of ２００ mL and the generated time of ６０ min .Then the data were analyzed with principal component analysis method ( PCA) , linear discrimination analysis method (LDA) . The consistent results by LDA and PCA revealed that the grain and polished rice were superior to brown rice and cooked rice to identify at the same time . As a result , the different varieties of rice were classified precisely by e‐nose , which confirmed that e‐nose technique was a generaldetection for the comprehensive volatile substance with high content , thus it afforded the experimental data based on e‐nose technique for rice odor detection .

Published: 25 November 2011
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HU Gui‐xian
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Cite this article:

HU Gui‐xian, WANG Jun, WANG Jian‐jun, WANG Xiao‐li. Detection for rice odors and identification of varieties based on electronic nose technique. , 2011, 37(6): 670-676.

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http://www.zjujournals.com/agr/10.3785/j.issn.1008-9209.2011.06.012     OR     http://www.zjujournals.com/agr/Y2011/V37/I6/670


基于电子鼻技术的稻米气味检测与品种识别

采用商用PEN２ 电子鼻,通过分析测定样品质量、顶空空间及静置时间等匹配的试验参数,以及对传感器信号进行单因素方差分析,并采用主成分分析(PCA)和线性判别分析(LDA)方法,对５ 个不同水稻品种进行区分与识别研究.结果表明:１０ g 样品时以２００ mL 顶空空间、６０ min 静置时间的电子鼻响应值相对较稳定;PCA 和LDA 法均对谷物状态和精米状态区分效果较佳,对米饭状态区分欠佳.该实验能将样品进行较好的区分,验证了电子鼻检测是对稻米中所有含量较高的、可被检测到的挥发性物质的综合状态的识别,从而为利用电子鼻进行稻米气味检测技术提供了实验基础和科学依据.
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