食品科学 ›› 2019, Vol. 40 ›› Issue (2): 269-274.doi: 10.7506/spkx1002-6630-20180531-443

• 安全检测 • 上一篇    下一篇

基于顶空气相色谱-离子迁移谱技术的冷冻猪肉贮藏时间快速判别方法

王辉,田寒友,李文采,邹昊,刘飞,白京,李家鹏,陈文华,乔晓玲*   

  1. (中国肉类食品综合研究中心,肉类加工技术北京市重点实验室,北京食品科学研究院,北京 100068)
  • 出版日期:2019-01-25 发布日期:2019-01-22
  • 基金资助:
    “十三五”国家重点研发计划重点专项(2017YFC1600801); 北京市优秀人才培养资助项目(2017754154700G099);丰台区科技新星计划项目(KJXX201710)

Fast Discrimination of Frozen Pork Stored for Different Periods Using Headspace-Gas Chromatography-Ion Mobility Spectroscopy (HS-GC-IMS)

WANG Hui, TIAN Hanyou, LI Wencai, ZOU Hao, LIU Fei, BAI Jing, LI Jiapeng, CHEN Wenhua, QIAO Xiaoling*   

  1. (Beijing Key Laboratory of Meat Processing Technology, China Meat Research Center, Beijing Academy of Food Sciences, Beijing 100068, China)
  • Online:2019-01-25 Published:2019-01-22

摘要: 通过分析冷冻猪肉在贮藏过程中发生劣变的主因、位置、产生的物质及检测方法的繁简程度,选择顶空气相色谱-离子迁移谱(headspace-gas chromatography-ion mobility spectroscopy,HS-GC-IMS)技术作为冷冻猪肉气味劣变的检测手段,采集和分析冷冻猪IV号肉表层或浅表层脂肪氧化所产生的挥发性有机物(volatile organic compounds,VOCs),并采用主成分分析对不同贮藏时间冷冻猪肉的VOCs数据进行维度压缩,利用K均值聚类分析算法建立判别模型,以此作为判别冷冻猪肉贮藏时间的方法。研究表明,HS-GC-IMS可有效分离冷冻猪肉中极性相近的VOCs,对VOCs组分的数据采集及分析可在600?s内完成,并筛选出29?种离子峰强度变化明显的VOCs,通过二维数据可视化方式显示各VOCs离子峰的差异。经数据降维处理后所构建的聚类判别模型,可将冷冻猪肉检验样品根据贮藏时间的不同归类到对应的时间簇。

关键词: 顶空气相色谱-离子迁移谱, 冷冻猪肉, 贮藏时间, 品质劣变, 脂肪氧化

Abstract: Considering the main cause and positions of quality deterioration and the complexity of detecting newly generated compounds in pork during frozen storage, headspace-gas chromatography-ion mobility spectroscopy (HS-GC-IMS) was chosen as a method for odor deterioration analysis to acquire and analyze the volatile organic compounds (VOCs) generated from lipid oxidation on the surface layer and shallow layer of frozen pork. Dimensionality reduction of the VOCs data of frozen pork stored for different periods was performed by principal component analysis (PCA), and the processed data were applied to establish a discriminant analysis model by K-means algorithm. The model was used to assess frozen pork stored for different periods. The results showed that the VOCs with similar polarity in frozen pork were separated effectively, and the data acquisition and analysis of VOCs were completed within 600 s by HS-GC-IMS. After data screening, 29 VOCs showed obvious changes in ion peak intensity, which?could be displayed in the 2-dimension mode of data visualization. The model developed in this study could classify samples of frozen pork at different storage times into the corresponding clusters.

Key words: headspace-gas chromatography-ion mobility spectroscopy (HS-GC-IMS), frozen pork, storage time, quality deterioration, lipid oxidation

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