基于GC-MS和快速气相电子鼻对我国东北地区代表性粳米香气组分分析
Analysis of Aroma Components of Representative Japonica Rice in Northeast China Based on GC-MS and Flash GC E-Nose
蒋森涛 1段晓亮 2张东 2商博 2刘辉 2马航 2杨潮锋 1刘兴泉1
作者信息
- 1. 浙江农林大学食品与健康学院,临安 311300
- 2. 国家粮食和物资储备局科学研究院,北京 100000
- 折叠
摘要
为探究我国东北地区4种代表性粳米(香米五优稻4号、绥粳18和非香米龙粳31、盐丰47)香气组分差异,通过顶空-固相微萃取-气相色谱-质谱联用(HS-SPME-GC-MS)和快速气相电子鼻(Flash GC e-nose)技术对粳米香气组分进行鉴定.研究采用正交偏最小二乘法-判别分析(OPLS-DA)和层次聚类分析(HCA)等方法对4种粳米香气组分进行分析,结果表明,4种粳米的主要香气组分构成类似,以己醛、壬醛等醛类为主;五优稻4号主要香气成分含量显著(P≤0.05)高于其他3个品种粳米,使得其香气更加浓郁;关于粳米香气组分鉴定技术,GC-MS技术的准确度和检测范围优于电子鼻技术,而检测效率低于电子鼻技术.
Abstract
In order to explore the difference of aroma components of four representative japonica rice varieties(fragrant rice Wuyou No.4,Suijing 18,non-fragrant rice Longjing31,Yanfeng47)in Northeast China,the aroma components of japonica rice were identified by Headspace-solid phase microextraction-gas chromatography mass spectrometry(HS-SPME-GC-MS)and Flash gas chromatography electronic nose(Flash GC e-nose).In this study,orthogonal partial least-squares discriminant analysis(OPLS-DA)and hierarchical cluster analysis(HCA)were used to analyze and identify four aroma components of japonica rice.The results indicated that the main aroma components of the four kinds of japonica rice were similar,with hexanal,nonanal and other aldehydes as the main components;the content of main aroma components of Wuyou No.4 was significantly higher(P≤0.05)than that of other three varieties of japonica rice,making its aroma more intense;with regard to the identification technology of two japonica rice aroma components,the accuracy and detection range of GC-MS technology were better than that of electronic nose technology,while the detection efficiency was lower than that of electronic nose technology.
关键词
东北粳米/香气组分/顶空-固相微萃取-气相色谱-质谱联用(HS-SPME-GC-MS)/快速气相电子鼻(Flash/GC/e-nose)/正交偏最小二乘法-判别分析(OPLS-DA)/层次聚类分析(HCA)Key words
Japonica rice in Northeast China/aroma components,headspace-solid phase microextraction-gas chromatography-mass spectrometry(HS-SPME-GC-MS)/flash gas chromatography electronic nose(Flash GC e-nose)/orthogonal partial least squares-discriminant analysis(OPL引用本文复制引用
基金项目
"十四五"国家重点研发计划项目(2022YFE0117800)
浙江省"三农九方"科技协作计划项目(2022SNJF011)
出版年
2024
NETL
NSTL
万方数据