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| 基于电子鼻技术的稻米气味检测与品种识别 | |
| 引用本文： | 胡桂仙,王俊,王建军,王小骊. 基于电子鼻技术的稻米气味检测与品种识别[J]. 浙江大学学报(农业与生命科学版), 2011, 37(6). DOI: 10.3785/j.issn.1008-9209.2011.06.012 |
| 作者姓名： | 胡桂仙 王俊 王建军 王小骊 |
| 作者单位： | 1. 浙江省农业科学院农产品质量标准研究所,浙江杭州,310021 2. 浙江大学生物系统工程与食品科学学院生物系统工程系,浙江杭州,310058 3. 浙江省农业科学院作物与核技术利用研究所,浙江杭州,310021 |
| 基金项目： | 浙江省农业科学院创新提升工程资助项目，国家高技术研究发展计划"863"资助项目，国家科技支撑计划资助项目 |
| 摘 要： | 采用商用PEN2电子鼻,通过分析测定样品质量、项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:10g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. |
| 关 键 词： | 稻米 电子鼻 气味检测 品种识别 |
Detection for rice odors and identification of varieties based on electronic nose technique. |
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| HU Gui-xian,WANG Jun,WANG Jian-jun,WANG Xiao-li. Detection for rice odors and identification of varieties based on electronic nose technique.[J]. Journal of Zhejiang University(Agriculture & Life Sciences), 2011, 37(6). DOI: 10.3785/j.issn.1008-9209.2011.06.012 | |
| Authors: | HU Gui-xian WANG Jun WANG Jian-jun WANG Xiao-li |
| Affiliation: | 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 310058,3.Institute of Crops and Utilization of Nuclear Technology,China) |
| Abstract: | An investigation was made to distinguish five rice varieties with PEN2 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 an... |
| Keywords: | rice electronic nose detection for odors identification of variety |
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