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Flavor Characterization and Imitation Flavor Identification Using Gas Chromatography-Orbitrap Mass Spectrometry Fingerprinting

Author(s): Mingyao Gao, Xiangxu Li, Huan Chen, Xinsheng Wang, Hongwei Hou* and Qingyuan Hu
Institute of Biomedical Engineering, College of Life Sciences, Qingdao, Shandong 266100, 1China National Tobacco Quality Supervision and Test Center, 2Key Laboratory of Tobacco Biological Effects, Zhengzhou, Henan 450001, 3Beijing Life Science Academy, 4Key Laboratory of Tobacco Biological Effects and Biosynthesis, Beijing 100000, China

Correspondence Address:
Hongwei Hou, Key Laboratory of Tobacco Biological Effects and Biosynthesis, Beijing 100000, China, E-mail:

Flavor is commonly used as a food additive to impart a distinctive taste. Minor differences in the chemical profile of imitation flavors may severely affect the final food quality. Thus, similarity evaluation of flavor compounds is key to maintaining quality control in the food industry. In this study, a similarity evaluation method was developed, which incorporates non-targeted gas chromatography-Orbitrap for high-resolution mass-based fingerprinting and multivariate statistical analysis, including the Pearson product-moment correlation coefficient, hierarchical cluster analysis, and principal component analysis. Pearson product-moment correlation coefficient of historical batches greater than 0.8 were integrated to the chromatographic fingerprint, while hierarchical cluster analysis and principal component analysis were used to evaluate the similarities between the reference samples and imitation flavors. Eight batches of samples were tested, and the results of all samples were included in the chromatographic fingerprint. Three imitation samples were successfully identified by hierarchical cluster analysis and principal component analysis. The developed method provides a tool for the accurate evaluation of the quality of imitation flavor compounds in food.

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Google scholar citation report
Citations : 66710

Indian Journal of Pharmaceutical Sciences received 66710 citations as per google scholar report