HS-GC-IMS with PCA to analyze volatile flavor compounds across different production stages of fermented soybean whey tofu. (1st June 2021)

• Record Type: Journal Article
• Authors: Yang, Yang; Wang, Bing; Fu, Yu; Shi, Yan-guo; Chen, Feng-lian; Guan, Hua-nan; Liu, Lin-lin; Zhang, Chun-yan; Zhu, Peng-yu; Liu, Ying; Zhang, Na
• Is Part Of: Food chemistry. Volume 346(2021)
• Publication Date: 2021-06-01
• Subjects: Hexanal (PubChem CID6184) -- 1-Octen-3-ol (PubChem CID18827) -- Heptanal (PubChem CID8130) -- (E)-2-Hexenol (PubChem CID5318042) -- 2-Heptanone (PubChem CID8051) -- 2-Pentylfuran (PubChem CID19602) -- Pentanal (PubChem CID8063) -- 2, 3-Butanedione (PubChem CID650) -- Benzaldehyde (PubChem CID240) -- 1-Hexanol (PubChem CID8103); Fermented soybean whey tofu -- Flavor fingerprint -- Principal component analysis -- Volatile profile -- Headspace-gas chromatography-ion mobility spectrometry; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2020.128880
• Languages: English
• ISSNs: 0308-8146

Abstract

Highlights: Establishment of flavor fingerprint of soybean fermented whey tofu (FSWT). GC-IMS combined with PCA was applied to detect the flavor of fermented soybean products. The flavor changes during the processing of FSWT. Abstract: The variations in flavor substances across the different stages of fermented soybean whey tofu (FSWT) production were analyzed by headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) combined with principal component analysis (PCA). The results revealed 24 representative flavor compounds in the samples across all production stages. After heating, the signal intensity of hexanal, 1-octen-3-ol, heptanal, and (E)-2-hexenol, which are unpleasant flavor substances found in raw soymilk, weakened, whereas those of some aroma substances increased. Furthermore, fermented flavor compounds, namely, 2-heptanone, 2-pentylfuran, pentanal, and 2, 3-butanedione, were produced after the addition of fermented soybean whey as a coagulant. A PCA based on the signal intensity of the detected volatile compounds revealed effective differentiation of samples from different stages into comparatively independent spaces. These results showed that the flavor fingerprints of the samples from different stages of FSWT production can be successfully built using HS-GC-IMS and PCA based on the detected volatile compounds.