Evidence map›Paper›PMID 40077494›Full record

ReviewFoods (Basel, Switzerland)2025

Challenges in Applying Multimodal Imaging Technologies to Quantify In Vivo Glycogen and Intramuscular Fat in Livestock.

Tharcilla I R C Alvarenga, Peter McGilchrist, Marianne D Keller, David W Pethick

Abstract readReview
In one paragraph

Review in Foods (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Tharcilla I R C AlvarengaArmidale Livestock Industries Centre, NSW Department of Primary Industries and Regional Development, Armidale, NSW 2351, Australia.ORCID 0000-0002-8260-0477
Peter McGilchristSchool of Environmental and Rural Science, University of New England, Armidale, NSW 2351, Australia.ORCID 0000-0003-3265-1134
Marianne D KellerSydney School of Veterinary Science, University of Sydney, Camperdown, NSW 2050, Australia.
David W PethickFood Futures Institute, Murdoch University, Murdoch, WA 6150, Australia.

Funding

Australian Meat Processor Corporation AMPC (2017-1040)
6 · The paper itself

Abstract

Predicting meat quality, especially dark, firm and dry meat, as well as muscle fat prior to slaughter, presents a challenge in practice. Medical as well as high-frequency ultrasound applications can be utilized to predict body composition and meat quality aspects. Ultrasounds are non-invasive, rapid-to-operate in vivo and show high correlations to the animal production traits being estimated. Farm animal ultrasounds are used to predict intramuscular fat content in the beef cattle industry. Challenges are identified in applying ultrasound technology to detect glycogen content in farm animals due to a wide range of fat, muscle and water composition. Other technologies and methods are reported in this literature review to overcome issues in the practicability and accuracy of ultrasound technology when estimating muscle glycogen levels in cattle. The discussion of other tools such as hyperspectral imaging, microwave sensor technology and digital infrared thermal imaging were addressed because of their superior accuracy in estimating moisture and fat components.

Indexed as

glycogen concentrationintramuscular fatlive animalmuscle hydrationultrasound frequency

Identifiers

PMID40077494
PMCPMC11898907

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.