Sensory quality of meat from eight different types of cattle in relation with their biochemical characteristics

Gagaoua, Mohammed; Terlouw, E.M.C.; Micol, Didier; Hocquette, Jean-François; Moloney, A.P.; Nuernberg, Karin; Bauchart, Dominique; Boudjellal, Abdelghani; Scollan, Nigel D.; Richardson, RI; Picard, Brigitte

doi:10.1016/s2095-3119(16)61340-0

Cited by 71 publications

(99 citation statements)

References 59 publications

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“…Although the chemically extracted fat content is not exactly the same as the fatness score, in that some fat deposits invisible on visual appraisal can be determined by chemical analysis, the relationship between them has been reported as linear . The involvement of fat in meat tenderness would be explained by the role that it plays during chewing though lubrication, such that fat present in and around the muscle fibres and perimysium during mastication results in a tenderer beef …”

Section: Discussionmentioning

confidence: 99%

“…For tenderness evaluation, the sensory protocol recently described by our group was used . Briefly, the steaks aged for 14 days were thawed at 5 °C for 48 h before cooking and sensory assessment at 55 °C, which end‐point cooking temperature that is usually employed in France . One hour before sensory assessment, the meat samples were cut into steaks (thickness of approximately 1.50 cm) and grilled on a double grooved plate griddle (SOFRACA, Morangis, France) heated to 300 °C for 30 min before cooking.…”

Section: Methodsmentioning

confidence: 99%

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Decision tree, a learning tool for the prediction of beef tenderness using rearing factors and carcass characteristics

2018

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Decision tree, a learning tool for the prediction of beef tenderness using rearing factors and carcass characteristics

2018

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“…It is assumed that variations in this quality trait partly result from differences in muscle characteristics . Among these characteristics, the proportion of different types of muscle fibres and intramuscular connective tissue (IMCT) composition with respect to total (TCol), insoluble (ICol) and soluble collagen (SCol) have been extensively investigated . Different chemical cross‐links (CLs) stabilize the molecule of collagen and consequently are involved in collagen solubilization and its mechanical properties after meat cooking .…”

Section: Introductionmentioning

confidence: 99%

Contribution of connective tissue components, muscle fibres and marbling to beef tenderness variability in longissimus thoracis, rectus abdominis, semimembranosus and semitendinosus muscles

et al. 2020

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BACKGROUND The present study aimed to identify relationships between components of intramuscular connective tissue, proportions of the different fiber types, intramuscular fat and sensory tenderness of beef cooked at 55 °C. Accordingly, four muscles differing in their metabolic and contractile properties, as well as in their collagen content and butcher value, were obtained from dairy and beef cattle of several ages and sexes and were then used to create variability. RESULTS Correlation analyses and/or stepwise regressions were applied on Z‐scores to identify the existing and robust associations. Tenderness scores were further categorized into tender, medium and tough classes using unsupervised learning methods. The findings revealed a muscle‐dependant role with respect to tenderness of total and insoluble collagen, cross‐links, and type IIB + X and IIA muscle fibers. The longissimus thoracis and semitendinosus muscles that, in the present study, were found to be extreme in their tenderness potential were also very different from each other and from the rectus abdominis (RA) and semimembranosus (SM). RA and SM muscles were very similar regarding their relationship for muscle components and tenderness. A relationship between marbling and tenderness was only present when the results were analysed irrespective of all factors of variation of the experimental model relating to muscle and animal type. CONCLUSION The statistical approaches applied in the present study using Z‐scores allowed identification of the robust associations between muscle components and sensory beef tenderness and also identified discriminatory variables of beef tenderness classes. © 2020 Society of Chemical Industry

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“…The metabolic muscle type was determined by measuring glycolytic and oxidative enzyme activities of respectively, lactate dehydrogenase (LDH; EC 1.1.1.27) and isocitrate dehydrogenase (ICDH; EC 1.1.1.42) . These enzymes are representative of different steps of energy metabolism used to characterize the metabolic types of beef muscles.…”

Section: Methodsmentioning

confidence: 99%

“…For total collagen, about 250 mg of muscle powder were weighed, acid hydrolyzed with 10 mL of 6 N hydrochloric acid (HCl), overnight at 110 °C in a screw‐capped glass tube. Then, the acid hydrolysate was diluted five times in 6 N HCl and the subsequent procedure was as described by Dubost et al For insoluble collagen, muscle powder was solubilized according to the method of Hill and hydrolyzed according to the same method . For both total and insoluble collagen, each sample was weighed and measured in triplicate and data were expressed in milligrams of hydroxyproline (OH‐prol) per gram of dry matter (DM).…”

Section: Methodsmentioning

confidence: 99%

Assessment of cattle inter‐individual cluster variability: the potential of continuum data from the farm‐to‐fork for ultimate beef tenderness management

2019

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BACKGROUND This study implemented a holistic approach based on the farm‐to‐fork data at the four levels of the continuum (farm – slaughterhouse – muscle – meat) to study the inter‐individual cluster variability of beef tenderness. For that, 171 young bulls were selected on a large database of 480 animals according to the industrial expectations based on animal and carcass characteristics. The targeted factors were age at slaughter (14; 20 months), carcass weight (370; 470 kg), EUROP conformation (7; 15) and fatness (2.5; 5) scores of the carcasses. Multivariate analyses and unsupervised learning tools were performed. RESULTS Principal component analysis combined to agglomerative hierarchical clustering allowed ten clusters to be identified that differed (P < 0.0001) for the four targeted factors. The clusters were further different for variables belonging to each level of the continuum. The results indicated an inter‐individual cluster variability rising in tenderness in link with the continuum data grouped according to industrial expectations. The associations of the whole variables of the continuum with tenderness were very important, but farm‐to‐fork continuum‐levels dependent. The findings showed that the variables contributing most to the inter‐individual cluster variability of tenderness seemed to be more related to the rearing practices, mainly feeding, and their consequences on carcass properties rather than to the muscle characteristics evaluated by enzyme metabolism and connective tissue. CONCLUSION It seems that considering the continuum data would allow possible trade‐off managements of tenderness to identify levers at different levels from the farm‐to‐meat. © 2019 Society of Chemical Industry

show abstract

Sensory quality of meat from eight different types of cattle in relation with their biochemical characteristics

Cited by 71 publications

References 59 publications

Decision tree, a learning tool for the prediction of beef tenderness using rearing factors and carcass characteristics

Decision tree, a learning tool for the prediction of beef tenderness using rearing factors and carcass characteristics

Contribution of connective tissue components, muscle fibres and marbling to beef tenderness variability in longissimus thoracis, rectus abdominis, semimembranosus and semitendinosus muscles

Assessment of cattle inter‐individual cluster variability: the potential of continuum data from the farm‐to‐fork for ultimate beef tenderness management

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