Evidence map›Paper›PMID 38790789›Full record

ArticleFoods (Basel, Switzerland)2024

Insights into the Volatile Flavor Profiles of Two Types of Beef Tallow via Electronic Nose and Gas Chromatography-Ion Mobility Spectrometry Analysis.

Ke Li, Liangyao Zhang, Danhui Yi, Yunxiao Luo, Chao Zheng, Yinglong Wu

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Enhanced Muscle Flavor in Male Chinese Mitten Crab (Animals : an open access journal from MDPI · 2025
    Article
  5. Article
  6. Article
  7. Article
4 · The record

Corrections and comments

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

6 authors.

Ke LiCollege of Food Science, Sichuan Agricultural University, Yaan 625014, China.ORCID 0000-0003-2936-2606
Liangyao ZhangCollege of Food Science, Sichuan Agricultural University, Yaan 625014, China.
Danhui YiCollege of Food Science, Sichuan Agricultural University, Yaan 625014, China.
Yunxiao LuoCollege of Food Science, Sichuan Agricultural University, Yaan 625014, China.
Chao ZhengCollege of Food Science, Sichuan Agricultural University, Yaan 625014, China.
Yinglong WuCollege of Food Science, Sichuan Agricultural University, Yaan 625014, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the current study, an electronic nose (E-nose) and gas chromatography-ion mobility spectrometry (GC-IMS) were employed to investigate the volatile flavor compounds (VFCs) of intense flavor beef tallow (L) and ordinary beef tallow (P). The study results indicate that an E-nose combined with an LDA and GC-IMS combined with an OPLS-DA can effectively distinguish between the two types of beef tallow. Compared with ordinary beef tallow, the E-nose sensors of intense flavor beef tallow have stronger response signals to sulfides, terpenes, and nitrogen oxides. A total of 22 compounds contribute to making the flavor of intense flavor beef tallow more typical and richer; in contrast, ethyl acetate was the main aroma-active compound found in the ordinary beef tallow. Sulfur-containing compounds and terpenoids might be the key substances that cause sensory flavor differences between the two types of beef tallow. In conclusion, the results of this study clarify the characteristics and differences of the two types of beef tallow and provide an enhanced understanding of the differences in the flavors of the two types of beef tallow.

Indexed as

beef tallowE-noseflavor profileGC-IMSOPLS-DA

Identifiers

PMID38790789
PMCPMC11119226

What OpenQuestion holds

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Registered trials

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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.