作　　者： ; ; ; ;

机构地区： 浙江省农业科学院

出　　处： 《浙江大学学报（农业与生命科学版）》 2011年第6期670-676,共7页

摘　　要： 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. 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 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 general detection for the comprehensive volatile substance with high content,thus it afforded the experimental data based on e-nose technique for rice odor detection.

关 键 词： 稻米 电子鼻 气味检测 品种识别

领　　域： [自动化与计算机技术] [自动化与计算机技术]