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中国精品科技期刊2020
陈通,高晓惠,杨菊,等. 基于GC-IMS技术的香米共享风味指纹谱构建[J]. 食品工业科技,2022,43(10):351−356. doi: 10.13386/j.issn1002-0306.2021090010.
引用本文: 陈通,高晓惠,杨菊,等. 基于GC-IMS技术的香米共享风味指纹谱构建[J]. 食品工业科技,2022,43(10):351−356. doi: 10.13386/j.issn1002-0306.2021090010.
CHEN Tong, GAO Xiaohui, YANG Ju, et al. Sharing Flavour Fingerprints Analysis of Fragrant Rice Based on GC-IMS Technology[J]. Science and Technology of Food Industry, 2022, 43(10): 351−356. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2021090010.
Citation: CHEN Tong, GAO Xiaohui, YANG Ju, et al. Sharing Flavour Fingerprints Analysis of Fragrant Rice Based on GC-IMS Technology[J]. Science and Technology of Food Industry, 2022, 43(10): 351−356. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2021090010.

基于GC-IMS技术的香米共享风味指纹谱构建

Sharing Flavour Fingerprints Analysis of Fragrant Rice Based on GC-IMS Technology

  • 摘要: 为提取广西香米中的共享风味指纹信息,实现广西、五常区域香米样品的快速判别,本研究采用气相离子迁移谱(Gas chromatography-ion mobility Spectrometry,GC-IMS)分析53个香米样品的挥发性风味物质成分,采用图谱预处理结合自动阈值分割方法提取二维图谱中能够表征广西香米中共有风味成分变量,并进行主成分分析(Principal component analysis,PCA),并使用二次线性判别分析(Quadratic discriminant analysis, QDA)建立2类区域香米样品的判别模型。结果表明,采用自动阈值分割方法共提取了广西香米样品中285个共享特征变量,2类样品在主成分得分图中均有各自的归属区域,QDA判别结果表明2类香米样品的识别率达到100%,可实现2类香米样品的准确判别。综上,数字图像处理结合化学计量学方法可有效提取GC-IMS二维图谱中的特征信息变量,实现香米品质的快速、无损、准确分析,也为其他类似联用仪器的多维特征信息提取提供了一种分析方法。

     

    Abstract: In order to extract the shared flavour fingerprint information from Guangxi fragrant rice and to rapidly realize the discrimination of fragrant rice between Guangxi and Wuchang regions, a total of 53 fragrant rice samples were collected and gas chromatography-ion mobility spectrometry (GC-IMS) technology was used to analyze the volatile flavor components. Based on the image pretreatment and automatic threshold segmentation algorithm, the shared flavour components of Guangxi fragrant rice were extracted in the two-dimensional map, and quadratic discriminant analysis (QDA) combined with principal component analysis (PCA) was applied to establish the qualitative model for distinguishing two different regions of fragrant rice. The results showed that 285 shared characteristic variables were extracted from fragrant rice by using the automatic threshold segmentation method. The first two principal component scores showed that each region of fragrant rice had their own corresponding areas. The discriminant model indicated that the recognition rate of two regions of fragrant rice could reach 100%, which could be used to estimate the discrimination between fragrant rice samples. In conclusion, digital image processing technology combined with chemometrics could effectively extract characteristic flavour variables from the two-dimensional map, which could achieve the rapid, non-destructive and accurate analysis in fragrant rice quality based on GC-IMS technology, and also provide an analysis method for multi-dimensional information for other similar instruments.

     

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