Evidence map›Paper›PMID 39229587›Full record

ArticleFrontiers in nutrition2024

Characterization of flavor profile of Steamed beef with rice flour using gas chromatography-ion mobility spectrometry combined with intelligent sensory (Electronic nose and tongue).

Tianyang Wang, Lian Yang, Yiling Xiong, Baozhu Wu, Yang Liu, Mingfeng Qiao, Chenglin Zhu, Huachang Wu, Jing Deng, Ju Guan

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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0cells of the map it votes in
5citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Tianyang WangCuisine Science Key Laboratory of Sichuan Province, Sichuan Tourism University, Chengdu, Sichuan, China.
Lian YangCuisine Science Key Laboratory of Sichuan Province, Sichuan Tourism University, Chengdu, Sichuan, China.
Yiling XiongCuisine Science Key Laboratory of Sichuan Province, Sichuan Tourism University, Chengdu, Sichuan, China.
Baozhu WuCuisine Science Key Laboratory of Sichuan Province, Sichuan Tourism University, Chengdu, Sichuan, China.
Yang LiuCuisine Science Key Laboratory of Sichuan Province, Sichuan Tourism University, Chengdu, Sichuan, China.
Mingfeng QiaoCuisine Science Key Laboratory of Sichuan Province, Sichuan Tourism University, Chengdu, Sichuan, China.
Chenglin ZhuCollege of Food Science and Technology, Southwest Minzu University, Chengdu, Sichuan, China.
Huachang WuCuisine Science Key Laboratory of Sichuan Province, Sichuan Tourism University, Chengdu, Sichuan, China.
Jing DengCuisine Science Key Laboratory of Sichuan Province, Sichuan Tourism University, Chengdu, Sichuan, China.
Ju GuanCuisine Science Key Laboratory of Sichuan Province, Sichuan Tourism University, Chengdu, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The intelligent senses (Electronic nose and tongue), were combined with headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) and free amino acid were used in combination to determine the aroma and taste components during the processing of Chinese traditional dish Steamed beef with rice flour (SBD). The findings revealed that E-nose and E-tongue, could clearly distinguish and identify the aroma and taste of SBD. A total of 66 volatile substances and 19 free amino acids were identified by HS-GC-IMS and amino acid analyzer, respectively. The highest contribution to aroma in the production of SBD was alcohols, esters and aldehydes. Further analysis of relative odor activity showed that 3-Methylbutanol-D, 3-Methylbutanol-M and 3-Methylthio propanal is the marinating stage (T2) main aroma components. Ethyl 3-methylbutanoate-M and Ethyl 3-methylbutanoate-D were the main aroma components in the seasoning stage (T3). Additionally, the calculation of the taste activity value showed that Glutamic contributed significantly to the umami of SBD. Alanine was a representative taste component in the marinating stage (T2), while Proline, Aspartic, Lysine, Glutamic, Valine, Arginine, and Histidine were characteristic amino acids of the seasoning stage (T3). Consequently, this study offers valuable insights into the industrial-scale production and flavor regulation of SBD products.

Indexed as

chemometricsfree amino acidGC-IMSintelligent sensesSteamed beef with rice flour

Identifiers

PMID39229587
PMCPMC11368871

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.