Evidence map›Paper›PMID 38756473›Full record

ArticleFood chemistry: X2024

Insights into the effects of saline forage on the meat quality of Tibetan sheep by metabolome and multivariate analysis.

Nana Ma, Lijuan Han, Shengzhen Hou, Linsheng Gui, Zhenzhen Yuan, Shengnan Sun, Zhiyou Wang, Baochun Yang, Chao Yang

Abstract read
In one paragraph

Article in Food chemistry: X, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

9 authors.

Nana MaCollege of Agriculture and Animal Husbandry, Qinghai University, Xining, China.
Lijuan HanCollege of Agriculture and Animal Husbandry, Qinghai University, Xining, China.
Shengzhen HouCollege of Agriculture and Animal Husbandry, Qinghai University, Xining, China.
Linsheng GuiCollege of Agriculture and Animal Husbandry, Qinghai University, Xining, China.
Zhenzhen YuanCollege of Agriculture and Animal Husbandry, Qinghai University, Xining, China.
Shengnan SunCollege of Agriculture and Animal Husbandry, Qinghai University, Xining, China.
Zhiyou WangCollege of Agriculture and Animal Husbandry, Qinghai University, Xining, China.
Baochun YangCollege of Agriculture and Animal Husbandry, Qinghai University, Xining, China.
Chao YangCollege of Agriculture and Animal Husbandry, Qinghai University, Xining, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This work aimed to investigate how two different types of forage (saline and alkaline) impact the meat quality and muscle metabolism of Tibetan sheep. An integrative multi-omics analysis of meat quality and different metabolites was performed using untargeted and targeted metabolomics approaches. The research results indicated that GG grass (saline and alkaline forage) possessed superior characteristics in terms of apparent quality and secondary metabolite content compared with HG grass (Non saline alkali forage), regardless of the targeted metabolites or non-targeted ones. Simultaneously, under stress conditions, the carbohydrates-rich salt-alkali grass play a significant role in slowing down the decline in pH, increasing the unsaturated fatty acid content and reducing the thawing loss in Tibetan sheep. This study provides an understanding of the impact of different salt-alkali grass on the quality of Tibetan sheep meat, while providing a scientific basis for the future development of salt-alkali livestock industry.

Indexed as

Forage qualityMeat qualityMetabolomicsSaline and alkalineTibetan sheep

Identifiers

PMID38756473
PMCPMC11096943

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.