Evidence map›Paper›PMID 31970332›Full record

ArticleFood science of animal resources2020

Texture Characteristics of Horse Meat for the Elderly Based on the Enzyme Treatment.

Dah-Sol Kim, Nami Joo

Open access · diamondAbstract read
In one paragraph

Article in Food science of animal resources, 2020. 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
0.7field-weighted citation impact, top 34% of its field
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, 7 citations in OpenAlex.

  1. Article
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  7. Review
  8. Nutritional Composition of Tonka Bean (Gels (Basel, Switzerland) · 2022
    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

2 authors at 1 institution in 1 country.

Dah-Sol KimDepartment of Food and Nutrition, Sookmyung Women's University, Seoul 04310, Korea.ORCID https://orcid.org/0000-0002-2103-3106
Nami JooDepartment of Food and Nutrition, Sookmyung Women's University, Seoul 04310, Korea.ORCID https://orcid.org/0000-0002-8205-0399
Sookmyung Women's University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Horse meat is nutritionally adequate to the elderly, but it has a comparatively hard texture in contrast to most of the food. In practice, the meat intake in the elderly is generally bated because the relatively difficult texture of the meat can diminish mastication. Thus, strategies are being developed to produce meat products remanding detracted mastication exertion and possibly exalt ingestion and nutritional stand, in the elderly. Hence, the effects of enzymes on textural characteristics of horse meat were studied, because they have well-known favorable efficacy on the meat tenderness by causing important demotion of the myo-fibrillar protein and collagen. Four treatments namely, papain, bromelin, pepsin, and pancreatin, alongside one control were invoked to the horse meat. Their effects on the texture parameters were determined. All the above enzymatic treatments significantly reduced hardness and resilience (p<0.001). These results present opportunities to produce essential fatty acids fortified horse meat with soft texture and satisfied technological characteristics. The intake of the essential fatty acids intensified horse meat could aid the elderly to get their aimed essential fatty acid demands. Results also suggest that horse meat tenderized through enzymatic processing stand for auspicious options for the comprehension of texture-revised diets in the elderly population.

Indexed as

elderlyfatty acidshorse meatmasticationtexture

Identifiers

PMID31970332
PMCPMC6957448
OpenAlexW2988000444

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.