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Cluster analysis application identifies muscle characteristics of importance for beef tenderness

Overview of attention for article published in BMC Molecular and Cell Biology, December 2012
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Title
Cluster analysis application identifies muscle characteristics of importance for beef tenderness
Published in
BMC Molecular and Cell Biology, December 2012
DOI 10.1186/1471-2091-13-29
Pubmed ID
Authors

Sghaier Chriki, Graham E Gardner, Catherine Jurie, Brigitte Picard, Didier Micol, Jean-Paul Brun, Laurent Journaux, Jean-Francois Hocquette

Abstract

An important controversy in the relationship between beef tenderness and muscle characteristics including biochemical traits exists among meat researchers. The aim of this study is to explain variability in meat tenderness using muscle characteristics and biochemical traits available in the Integrated and Functional Biology of Beef (BIF-Beef) database. The BIF-Beef data warehouse contains characteristic measurements from animal, muscle, carcass, and meat quality derived from numerous experiments. We created three classes for tenderness (high, medium, and low) based on trained taste panel tenderness scores of all meat samples consumed (4,366 observations from 40 different experiments). For each tenderness class, the corresponding means for the mechanical characteristics, muscle fibre type, collagen content, and biochemical traits which may influence tenderness of the muscles were calculated.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Korea, Republic of 1 1%
Brazil 1 1%
Unknown 72 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 19%
Student > Master 11 15%
Student > Doctoral Student 10 14%
Researcher 5 7%
Student > Bachelor 5 7%
Other 14 19%
Unknown 15 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 45%
Medicine and Dentistry 7 9%
Veterinary Science and Veterinary Medicine 3 4%
Biochemistry, Genetics and Molecular Biology 2 3%
Engineering 2 3%
Other 6 8%
Unknown 21 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 April 2013.
All research outputs
#17,302,400
of 25,394,764 outputs
Outputs from BMC Molecular and Cell Biology
#778
of 1,233 outputs
Outputs of similar age
#193,856
of 289,127 outputs
Outputs of similar age from BMC Molecular and Cell Biology
#13
of 22 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,233 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 289,127 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.