Evidence map›Paper›PMID 37969318›Full record

ReviewFood science of animal resources2023

Multi-Omics Approaches to Improve Meat Quality and Taste Characteristics.

Young-Hwa Hwang, Eun-Yeong Lee, Hyen-Tae Lim, Seon-Tea Joo

Abstract readReview
In one paragraph

Review in Food science of animal resources, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Big Data and AI-Powered Modeling: A Pathway to Sustainable Precision Animal Nutrition.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  8. Article
  9. Article
  10. Review
  11. Application of Omics in Donkey Meat Research: A Review.Animals : an open access journal from MDPI · 2025
    Review
  12. Article
  13. Review
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

4 authors.

Young-Hwa HwangInstitute of Agriculture & Life Science, Gyeongsang National University, Jinju 52828, Korea.ORCID https://orcid.org/0000-0003-3687-3535
Eun-Yeong LeeDivision of Applied Life Science (BK21 Four), Gyeongsang National University, Jinju 52828, Korea.ORCID https://orcid.org/0000-0002-3467-7349
Hyen-Tae LimInstitute of Agriculture & Life Science, Gyeongsang National University, Jinju 52828, Korea.ORCID https://orcid.org/0000-0001-6221-4942
Seon-Tea JooInstitute of Agriculture & Life Science, Gyeongsang National University, Jinju 52828, Korea.ORCID https://orcid.org/0000-0002-5483-2828

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With rapid advances in meat science in recent decades, changes in meat quality during the pre-slaughter phase of muscle growth and the post-slaughter process from muscle to meat have been investigated. Commonly used techniques have evolved from early physicochemical indicators such as meat color, tenderness, water holding capacity, flavor, and pH to various omic tools such as genomics, transcriptomics, proteomics, and metabolomics to explore fundamental molecular mechanisms and screen biomarkers related to meat quality and taste characteristics. This review highlights the application of omics and integrated multi-omics in meat quality and taste characteristics studies. It also discusses challenges and future perspectives of multi-omics technology to improve meat quality and taste. Consequently, multi-omics techniques can elucidate the molecular mechanisms responsible for changes of meat quality at transcriptome, proteome, and metabolome levels. In addition, the application of multi-omics technology has great potential for exploring and identifying biomarkers for meat quality and quality control that can make it easier to optimize production processes in the meat industry.

Indexed as

genomicsmetabolomicsmulti-omicsproteomicstranscriptomics

Identifiers

PMID37969318
PMCPMC10636221

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.