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基于GC/MS的储藏粳稻谷挥发物质变化研究
引用本文:宋伟,张明,张婷筠. 基于GC/MS的储藏粳稻谷挥发物质变化研究[J]. 中国粮油学报, 2013, 28(11): 97
作者姓名:宋伟  张明  张婷筠
作者单位:南京财经大学食品科学与工程学院,南京财经大学食品科学与工程学院
基金项目:“十二五”国家科技支撑计划(2011BAD03B02)
摘    要:应用顶空固相微萃取-气质联用分析技术,对不同储藏条件下的稻谷样品挥发物质进行测定,用主成分分析法(PCA)研究不同稻谷样品间挥发物质的差异,进而找出能够反应稻谷储藏品质的特征性挥发物。测定结果表明,共检测到不同储藏条件下的稻谷样品挥发物质117种,从中筛选出贡献较大的83种成分进行分析,其中烃类29种,醛类17种,酮类10种,醇类8种,酸酯类10种,杂环类9种。主成分分析(PCA)结果表明,储藏期间稻谷的酸酯类、醇类、醛类、酮类、烷烃类、烯烃类挥发物质下降明显,且温度越高下降程度越大;苯类挥发物质随储藏时间的延长有上升趋势,温度越高上升的越明显;杂环类挥发物质受储藏时间以及温度的影响较小。各类挥发物质受储藏条件影响大小顺序为酸酯类 > 醇类 > 酮类 > 醛类 > 烃类 > 杂环类,同时得到评判稻谷品质的特征性挥发物质。

关 键 词:稻谷样品 储藏条件 挥发性物质 主成分分析
收稿时间:2012-12-31
修稿时间:2013-08-12

Study on the changes of volatile substances in the storage japonica based on GC / MS
Abstract:Volatile matters of the rice samples stored under different conditions were determined using SPME-GC/MS, principal component analysis (PCA) was used to study the differences of the rice samples of various types of volatile substances, and then found the characteristic volatiles which could represent the quality of the rice storage. The results showed that 117 kinds of rice samples volatile substances were detected, including 29 kinds of hydrocarbons, aldehydes 17 species, 10 kinds of ketones, alcohols 8 species, esters 10 species and 9 kings of heterocyclic. The principal component analysis (PCA) results showed that acid esters, alcohols, aldehydes, ketones, alkanes, olefins volatile substances decreased significantly during the storage time, and the higher the temperature was, the greater the degree was declined; benzene volatile substances were on the rise with the storage time, and they rose more obvious when the temperature was higher; heterocyclic volatile matters were less affected by storage time and temperature. The order of the volatile substances affected by storage conditions were esters> alcohols> ketones > aldehydes> hydrocarbons> heterocyclic, it also obtained the characteristic volatile substances evaluate the quality of rice.
Keywords:rice samples   storage conditions   volatile substances   principal component analysis
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