Cluster analysis application identifies muscle characteristics of importance for beef tenderness
Identifieur interne : 005438 ( Main/Exploration ); précédent : 005437; suivant : 005439Cluster analysis application identifies muscle characteristics of importance for beef tenderness
Auteurs : Sghaier Chriki [France] ; Graham E. Gardner [Australie] ; Catherine Jurie [France] ; Brigitte Picard [France] ; Didier Micol [France] ; Jean-Paul Brun [France] ; Laurent Journaux [France] ; Jean-Francois Hocquette [France]Source :
- BMC Biochemistry [ 1471-2091 ] ; 2012.
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.
Our results indicated that lower shear force values were associated with more tender meat. In addition, muscles in the highest tenderness cluster had the lowest total and insoluble collagen contents, the highest mitochondrial enzyme activity (isocitrate dehydrogenase), the highest proportion of slow oxidative muscle fibres, the lowest proportion of fast-glycolytic muscle fibres, and the lowest average muscle fibre cross-sectional area. Results were confirmed by correlation analyses, and differences between muscle types in terms of biochemical characteristics and tenderness score were evidenced by Principal Component Analysis (PCA). When the cluster analysis was repeated using only muscle samples from
Our results show that increased meat tenderness is related to lower shear forces, lower insoluble collagen and total collagen content, lower cross-sectional area of fibres, and an overall fibre type composition displaying more oxidative fibres than glycolytic fibres.
Url:
DOI: 10.1186/1471-2091-13-29
PubMed: 23259756
PubMed Central: 3544649
Affiliations:
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<front><div type="abstract" xml:lang="en"><sec><title>Background</title>
<p>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.</p>
</sec>
<sec><title>Results</title>
<p>Our results indicated that lower shear force values were associated with more tender meat. In addition, muscles in the highest tenderness cluster had the lowest total and insoluble collagen contents, the highest mitochondrial enzyme activity (isocitrate dehydrogenase), the highest proportion of slow oxidative muscle fibres, the lowest proportion of fast-glycolytic muscle fibres, and the lowest average muscle fibre cross-sectional area. Results were confirmed by correlation analyses, and differences between muscle types in terms of biochemical characteristics and tenderness score were evidenced by Principal Component Analysis (PCA). When the cluster analysis was repeated using only muscle samples from <italic>m. Longissimus thoracis</italic>
(LT), the results were similar; only contrasting previous results by maintaining a relatively constant fibre-type composition between all three tenderness classes.</p>
</sec>
<sec><title>Conclusion</title>
<p>Our results show that increased meat tenderness is related to lower shear forces, lower insoluble collagen and total collagen content, lower cross-sectional area of fibres, and an overall fibre type composition displaying more oxidative fibres than glycolytic fibres.</p>
</sec>
</div>
</front>
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</div1>
</back>
</TEI>
<affiliations><list><country><li>Australie</li>
<li>France</li>
</country>
<region><li>Auvergne (région administrative)</li>
<li>Auvergne-Rhône-Alpes</li>
<li>Île-de-France</li>
</region>
</list>
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</region>
<name sortKey="Brun, Jean Paul" sort="Brun, Jean Paul" uniqKey="Brun J" first="Jean-Paul" last="Brun">Jean-Paul Brun</name>
<name sortKey="Brun, Jean Paul" sort="Brun, Jean Paul" uniqKey="Brun J" first="Jean-Paul" last="Brun">Jean-Paul Brun</name>
<name sortKey="Chriki, Sghaier" sort="Chriki, Sghaier" uniqKey="Chriki S" first="Sghaier" last="Chriki">Sghaier Chriki</name>
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<name sortKey="Hocquette, Jean Francois" sort="Hocquette, Jean Francois" uniqKey="Hocquette J" first="Jean-Francois" last="Hocquette">Jean-Francois Hocquette</name>
<name sortKey="Hocquette, Jean Francois" sort="Hocquette, Jean Francois" uniqKey="Hocquette J" first="Jean-Francois" last="Hocquette">Jean-Francois Hocquette</name>
<name sortKey="Journaux, Laurent" sort="Journaux, Laurent" uniqKey="Journaux L" first="Laurent" last="Journaux">Laurent Journaux</name>
<name sortKey="Jurie, Catherine" sort="Jurie, Catherine" uniqKey="Jurie C" first="Catherine" last="Jurie">Catherine Jurie</name>
<name sortKey="Jurie, Catherine" sort="Jurie, Catherine" uniqKey="Jurie C" first="Catherine" last="Jurie">Catherine Jurie</name>
<name sortKey="Micol, Didier" sort="Micol, Didier" uniqKey="Micol D" first="Didier" last="Micol">Didier Micol</name>
<name sortKey="Micol, Didier" sort="Micol, Didier" uniqKey="Micol D" first="Didier" last="Micol">Didier Micol</name>
<name sortKey="Picard, Brigitte" sort="Picard, Brigitte" uniqKey="Picard B" first="Brigitte" last="Picard">Brigitte Picard</name>
<name sortKey="Picard, Brigitte" sort="Picard, Brigitte" uniqKey="Picard B" first="Brigitte" last="Picard">Brigitte Picard</name>
</country>
<country name="Australie"><noRegion><name sortKey="Gardner, Graham E" sort="Gardner, Graham E" uniqKey="Gardner G" first="Graham E" last="Gardner">Graham E. Gardner</name>
</noRegion>
</country>
</tree>
</affiliations>
</record>
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