Evidence map›Paper›PMID 40150401›Full record

ArticleAnimals : an open access journal from MDPI2025

The Effectiveness of the Use of Ultrasound Methodology (Applied to Live Animals) to Assess the Quality of Meat.

Edita Meškinytė, Vigilijus Jukna, Vilma Zigmantaitė, Oksana Ilina, Audrius Kučinskas

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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

5 authors.

Edita MeškinytėAnimal Production Research and Innovation Center, Agriculture Academy Bioeconomy Research Institute, Vytautas Magnus University, K. Donelaičio g. 58, LT-44248 Kaunas, Lithuania.
Vigilijus JuknaAnimal Production Research and Innovation Center, Agriculture Academy Bioeconomy Research Institute, Vytautas Magnus University, K. Donelaičio g. 58, LT-44248 Kaunas, Lithuania.
Vilma ZigmantaitėAnimal Production Research and Innovation Center, Agriculture Academy Bioeconomy Research Institute, Vytautas Magnus University, K. Donelaičio g. 58, LT-44248 Kaunas, Lithuania.ORCID 0000-0002-0410-1533
Oksana IlinaAnimal Production Research and Innovation Center, Agriculture Academy Bioeconomy Research Institute, Vytautas Magnus University, K. Donelaičio g. 58, LT-44248 Kaunas, Lithuania.
Audrius KučinskasAnimal Production Research and Innovation Center, Agriculture Academy Bioeconomy Research Institute, Vytautas Magnus University, K. Donelaičio g. 58, LT-44248 Kaunas, Lithuania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of non-invasive technologies is among the most accurate methods for assessing meat quality parameters. Beef tenderness and palatability are strongly influenced by the amount of intramuscular fat, commonly referred to as marbling. Marbling is widely used in breeding programs to select animals with superior meat quality. In this study, we analyzed 236 Angus bulls and 22 Angus heifers from various farms in Lithuania, all aged 450 ± 112 days. Ultrasound examinations were performed using a linear transducer with a silicone standoff to evaluate the loin eye area. Key meat quality indicators, such as fat thickness, loin area and thickness, and intramuscular fat, were found to increase with the weight of bulls, ranging from 365 ± 12.70 kg to 825.57 ± 11.75 kg (

Indexed as

beef researchBlack Angusbullsintramuscular fatlongissimus dorsi muscleultrasound meat quality

Identifiers

PMID40150401
PMCPMC11939753

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.