Evidence map›Paper›PMID 36496627›Full record

ArticleFoods (Basel, Switzerland)2022

Chirasak Phoemchalard, Suthipong Uriyapongson, Tanom Tathong, Pitukpol Pornanek

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. The Effects of Fresh Hemp Leaf Supplementation (Animals : an open access journal from MDPI · 2023
    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

4 authors.

Chirasak PhoemchalardDepartment of Agriculture, Mahidol University, Amnatcharoen Campus, Amnatcharoen 37000, Thailand.ORCID 0000-0003-1473-2053
Suthipong UriyapongsonDepartment of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen 40002, Thailand.
Tanom TathongDepartment of Food Technology, Faculty of Agriculture and Technology, Nakhon Phanom University, Nakhon Phanom 48000, Thailand.
Pitukpol PornanekDepartment of Animal Science, Faculty of Natural Resources, Rajamangala University of Technology Isan, Sakon Nakhon Campus, Sakon Nakhon 47160, Thailand.

Funding

Khon Kaen University's Post-Doctoral Training Scholarship PD2563-02
6 · The paper itself

Abstract

The increasing need for effective analytical tools to evaluate beef quality has prompted the development of new procedures to improve the animal sector's performance. In this study, three beef breeds-Thai native (TN), crossbred Brahman × Thai native (BT), and crossbred Charolais × Brahman (CB)-were compared in terms of their physicochemical and metabolic profiles. The findings demonstrated that TN beef was lighter and tougher than other beef. Beef odor was stronger in BT. In addition, CB beef was the most tender and had the highest intramuscular fat content. Twenty-one different metabolites were found overall through NMR and chemometric approaches. The primary factors contributing to the difference in OPLS-DA loading plots were acetylcholine, valine, adenine, leucine, phosphocreatine, β-hydroxypyruvate, ethanol, adenosine diphosphate, creatine, acetylcholine, and lactate. The multivariate analysis indicated that these metabolites in beef cattle breeds could be distinguished using NMR spectroscopy. The results of this study provide valuable information on the quality and meat metabolites of different breeds. This could help in the development of a more accurate assessment of the quality of beef in future research.

Indexed as

beefmeat qualitymetabolic profiling

Identifiers

PMID36496627
PMCPMC9736620

What OpenQuestion holds

Textmetadata
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.