Title |
Cluster analysis application identifies muscle characteristics of importance for beef tenderness
|
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Published in |
BMC Molecular and Cell Biology, December 2012
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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
Geographical breakdown
Country | Count | As % |
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France | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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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% |