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食品与发酵工业  2020, Vol. 46 Issue (6): 250-255    DOI: 10.13995/j.cnki.11-1802/ts.022672
  分析与检测 本期目录 | 过刊浏览 | 高级检索 |
基于GC-IMS技术分析糙米储藏过程中风味物质变化
王熠瑶1, 张烝彦2, 孙俊3, 常亚飞3, 吕飞1, 丁玉庭1, 周绪霞1*
1(浙江工业大学 食品工程与质量控制研究所,浙江 杭州,310014)
2(杭州市粮油中心检验监测站,浙江 杭州,310014)
3(杭州市粮食收储有限公司,浙江 杭州,310014)
Analysis of flavor changes of brown rice during storage based on gas chromatography-ion mobility spectrometry
WANG Yiyao1, ZHANG Zhengyan2, SUN Jun3, CHANG Yafei3, LYU Fei1, DING Yuting1, ZHOU Xuxia1*
1(Institute of Food Engineering and Quality Control, Zhejiang University of Technology, Hangzhou 310014, China)
2(Hangzhou Grain and Oil Center Inspection Station, Hangzhou 310014, China)
3(Hangzhou Grain Storage Co., Ltd., Hangzhou 310014, China)
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摘要 通过分析糙米在储藏过程中风味物质变化规律,建立一种新的快速判断糙米储藏期和新鲜度的方法。研究通过气相离子迁移谱技术(gas chromatography-ion mobility spectrometry, GC-IMS)采集糙米储藏过程中特征挥发性有机物组成及含量的变化,采用动态主成分分析对不同储藏时间糙米的挥发性有机物(volatile organic compounds, VOCs)数据降维处理并利用K均值聚类分析建立判别模型。研究表明,GC-IMS联用技术可有效分离不同储藏时间和不同包装方式的8组糙米样品中VOCs的单倍体和二倍体,快速筛选出59种离子峰强度变化明显的VOCs,通过二维数据可视化方式可直观区分不同糙米样品中VOCs的差异性。经数据降维处理后所构建的聚类判别模型,可将糙米样品根据储藏时间的不同归类到对应的时间簇,为糙米储藏期和新鲜度的快速鉴定提供新的思路和方法。
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王熠瑶
张烝彦
孙俊
常亚飞
吕飞
丁玉庭
周绪霞
关键词:  糙米  气相离子迁移谱  挥发性有机物  聚类分析  PCA    
Abstract: A novel detection method to quickly judge the storage time and freshness of brown rice by analyzing the changes of flavor substances of brown rice was established. Gas chromatography-ion mobility spectrometry (GC-IMS) was used to collect the volatile organic compounds of brown rice at different storage time. Dynamic principal component analysis (PCA) was used to reduce the dimensionality of volatile organic compounds (VOCs) data and the processed data were applied to establish clustering analysis model by K-means algorithm. The results showed that the GC-IMS combination technique could effectively separate haploid and diploid of the VOCs in 8 groups of brown rice samples with different storage time and different packaging methods. Meanwhile, it could rapidly screen out 59 characteristic ion peaks with significant intensity changes and also discriminated the VOCs differences in different brown rice samples by two-dimensional data visualization. The clustering discriminant model constructed by data dimensionality reduction can classify brown rice samples into corresponding time clusters according to different storage time, which provides new ideas and methods for rapid identification of brown rice storage period and freshness.
Key words:  brown rice    gas chromatography-ion mobility spectrometry (GC-IMS)    volatile organic compounds    cluster analysis    PCA
收稿日期:  2019-10-31                出版日期:  2020-03-25      发布日期:  2020-04-24      期的出版日期:  2020-03-25
基金资助: 浙江省重大科技专项重点农业项目(2015C02045)
作者简介:  硕士研究生(周绪霞教授为通讯作者,E-mail: xzhou@zjut.edu.cn)
引用本文:    
王熠瑶,张烝彦,孙俊,等. 基于GC-IMS技术分析糙米储藏过程中风味物质变化[J]. 食品与发酵工业, 2020, 46(6): 250-255.
WANG Yiyao,ZHANG Zhengyan,SUN Jun,et al. Analysis of flavor changes of brown rice during storage based on gas chromatography-ion mobility spectrometry[J]. Food and Fermentation Industries, 2020, 46(6): 250-255.
链接本文:  
http://sf1970.cnif.cn/CN/10.13995/j.cnki.11-1802/ts.022672  或          http://sf1970.cnif.cn/CN/Y2020/V46/I6/250
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