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Beef quality is a complex phenotype that can be evaluated only after animal slaughtering. Previous research has investigated the potential of genetic markers or muscle-derived proteins to assess beef tenderness. Thus, the use of low-invasive biomarkers in living animals is an issue for the beef sector. We hypothesized that publicly available data may help us discovering candidate plasma biomarkers. Thanks to a review of the literature, we built a corpus of articles on beef tenderness. Following data collection, aggregation, and computational reconstruction of the muscle secretome, the putative plasma proteins were searched by comparison with a bovine plasma proteome atlas and submitted to mining of biological information. Of the 44 publications included in the study, 469 unique gene names were extracted for aggregation. Seventy-one proteins putatively released in the plasma were revealed. Among them 13 proteins were predicted to be secreted in plasma, 44 proteins as hypothetically secreted in plasma, and 14 additional candidate proteins were detected thanks to network analysis. Among these 71 proteins, 24 were included in tenderness quantitative trait loci. The in-silico workflow enabled the discovery of candidate plasma biomarkers for beef tenderness from reconstruction of the secretome, to be examined in the cattle plasma proteome.

In this paper, we describe a new computational methodology to select the best regression model to predict a numerical variable of interest Y and to select simultaneously the most interesting numerical explanatory variables strongly linked to Y. Three regression models (parametric, semi-parametric and non-parametric) are considered and estimated by multiple linear regression, sliced inverse regression and random forests. Both the variables selection and the model choice are computational. A measure of importance based on random perturbations is calculated for each covariate. The variables above a threshold are selected. Then a learning/test samples approach is used to estimate the Mean Square Error and to determine which model (including variable selection) is the most accurate. The R package modvarsel (MODel and VARiable SELection) implements this computational approach and applies to any regression datasets. After checking the good behavior of the methodology on simulated data, the R package is used to select the proteins predictive of meat tenderness among a pool of 21 candidate proteins assayed in semitendinosus muscle from 71 young bulls. The biomarkers were selected by linear regression (the best regression model) to predict meat tenderness. These biomarkers, we confirm the predominant role of heat shock proteins and metabolic ones.

For several years, studies conducted for discovering tenderness biomarkers have proposed a list of 20 candidates. The aim of the present work was to develop an innovative methodology to select the most predictive among this list. The relative abundance of the proteins was evaluated on five muscles of 10 Holstein cows: gluteobiceps, semimembranosus, semitendinosus, Triceps brachii and Vastus lateralis. To select the most predictive biomarkers, a multi-block model was used: The Data-Driven Sparse Partial Least Square. Semimembranosus and vastus lateralis muscles tenderness could be well predicted (R&sup2, = 0.95 and 0.94 respectively) with a total of 7 out of the 5 times 20 biomarkers analyzed. An original result is that the predictive proteins were the same for these two muscles: &micro, calpain, m-calpain, h2afx and Hsp40 measured in m. gluteobiceps and &micro, calpain, m-calpain and Hsp70-8 measured in m. Triceps brachii. Thus, this method is well adapted to this set of data, making it possible to propose robust candidate biomarkers of tenderness that need to be validated on a larger population.

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

The present study explored the potential use of decision trees on rearing factors (q = 10) and carcass characteristics (q = 12) for the development of prediction model rules of beef tenderness prediction/categorization. Accordingly, 308 young bulls were used by a sensory panel to evaluate the tenderness potential of ribeye steaks grilled at 55 °C. A classification and regression tree method was implemented and allowed the prediction of tenderness using (i) rearing factors, (ii) carcass characteristics or (iii) both.The resultant tree models yielded predictive accuracies of 70.78% (with four rearing factors: concentrate percentage; fattening duration; initial body weight and dry matter intake); 67.21% (with four carcass characteristics: fatness carcass score; carcass weight; dressing percentage and muscle carcass percentage) and 84.41% (with six rearing factors and carcass characteristics) compared to the k-means clustering of tenderness. In the final and robust regression tree, from the 22 attribute information, two carcass characteristics (fatness carcass score and muscle carcass percentage) and four rearing factors (fattening duration; concentrate percentage; dry matter intake and initial body weight) were retained as predictors. The first splitter of the 308 ribeye steaks in accordance with their tenderness scores was fatness carcass score, followed by fattening duration and concentrate percentage.The trial in the preset study highlights the importance of thresholding approach for efficiently classifying ribeye steaks in accordance with their tenderness potential. The overall prediction model rule was: IF (fatness carcass score ≥ 2.88) AND (concentrate ≥ 82%) [AND (muscle carcass ≥ 71%)] THEN meat was [very] tender. © 2018 Society of Chemical Industry.

Just Accepted Manuscript; This study is based on an integromic approach of 71 young bulls’ data from farmgate-to-meat continuum including omics-based biomarkers, to understand beef tenderness variability in two muscle cuts that differ by their contractile and metabolic properties. By the means of chemometrics using partial least squares (PLS) and principal component regressions (PCR), important variables from a list of 49 that characterize 4 levels of the continuum (rearing factors – carcass – muscle – meat) were identified to explain tenderness of Longissimus thoracis (LT) and Semitendinosus (ST) muscles evaluated by sensory panel and instrumental Warner-Bratzler shear force (WBSF). The PLS and PCR analyses validated 16 and 15 variables for LT, and 12 and 14 for ST from the whole continuum to explain sensory tenderness and WBSF, respectively. Among the explanatory variables in the 4 models and in line with the role of apoptosis in tenderness determinism, HSP70-1A/B (a heat shock protein) was retained to explain beef tenderness irrespective of muscle and evaluation method. Similarly, dressing percentage from the carcass level was another robust predictor but in a muscle-dependent direction manner. HSP20, ENO3, MyHC-I as three muscle protein biomarkers and dry matter intake (DMI) as a rearing factor, were involved in 3 models to explain beef tenderness. This study highlighted also that several variables were muscle-specific irrespective of the evaluation method of tenderness. For LT muscle, 6 variables including 3 carcass traits (fatness score, fat carcass % and muscle carcass %), 2 muscle biomarkers (HSP70-8 and MyHC-IIx/b) and one meat quality trait (pH3h) were found. For ST muscle, 5 variables were validated from which 2 rearing factors (average daily gain and feed efficiency) and 3 structural protein biomarkers (α-actin, MyBP-H and CapZ-β). Finally, for WBSF only, lactate dehydrogenase chain B (LDH-B), was retained positively for LT and negatively for ST muscles. Overall, this trial showed that tenderness of LT and ST muscle-cuts are influenced by variables belonging to the whole continuum with relationships that depend on both the muscle type and the evaluation method. It further highlighted the potential of integromic/chemometric approaches on the farmgate-to-meat continuum data to better understand the sophisticated biological processes that orchestrate the conversion of muscle into meat and tenderness determinism.

International audience; The aim of this study was to evaluate the carcass and meat characteristics of eight muscles from bulls with distinct growth paths. A total of 40 Alentejana male calves were allocated to two distinct feeding regimes. In the continuous growth (CG) system, the animals were fed concentrates plus hay and were slaughtered at 18 months of age. On the other hand, in the discontinuous growth (DG) system, the animals were fed hay until 15 months of age; the cattle were then fed the same diet provided to the CG group from 15 to 24 months of age. The DG reduced hot carcass weight, fatness and dressing %, but the proportions of fat, bone and muscle tissues in the leg were not affected. In contrast, there was a positive impact of compensatory growth on supraspinatus, triceps brachii, semitendinosus, biceps femoris muscle tenderness, overcoming the negative effects of age at slaughter. The reasons for such improvement in meat tenderness were not related to intra-muscular fat content or myofibrillar protein degradation values. An association between tenderness and muscle collagen properties was not established. The results indicate that the compensatory growth has a muscle-dependent effect.

This work used K-means (k=3) after PCA analysis on 109 PDO Maine-Anjou cows according to the abundances of small and large heat shock proteins (HSPs) in the Longissimus thoracis muscle. Classes LP (n=24) and SP (n=33) were characterized by greater abundances of large and small HSPs, respectively, while class IP (n=52) was intermediate. The classes were compared for the abundance of other proteins in the same muscle and for meat tenderness. The effects of pre-slaughter factors (transport and lairage durations) were also investigated. Meat tenderness did not differ for any comparison. Certain proteins were influenced by pre-slaughter conditions. Among them, H2AFX and µ-calpain were impacted by both factors. The possible role of H2AFX (H2A histone family, member) in the balance of various processes involved in meat tenderization is discussed.

Bulls and steers (n = 60) were assigned to a pre-finishing grazing period and subsequently finished on concentrates or offered concentrates without grazing until slaughter (19 months). Colour and pH of longissimus thoracis were measured (48 h post-slaughter), and samples collected for proximate composition, collagen, sarcomere length, muscle fibre and enzymatic profile analysis. Steaks for texture, cook loss and sensory were aged (14 days). Castration increased intramuscular fat content, cook loss and myosin isoforms IIa and I proportions, and decreased IIx proportion (P < 0.05). Steer meat was positively correlated to overall tenderness, texture and acceptability (P < 0.05). The presence of a pre-finishing grazing period decreased intramuscular fat and increased the proportion of IIa compared with animals on concentrates, while no differences were found in sensory. Muscle colour, collagen, sarcomere length and instrumental texture were not modified by diet or castration. In conclusion, beef sensory characteristics were unaffected by diet, whereas castration resulted in a small improvement; however all the treatments produced an acceptable product.

For the whole beef sector, from producers to consumers, the uncontrolled variability of beef tenderness is a major concern. For 10 years, functional genomics and proteomics studies have been conducted to better understand the origin of this variability and to identify protein biomarkers that can be used to predict the tenderness of a piece of meat at slaughter or of a live animal. This chapter provides a comprehensive review on beef tenderness as provided by proteomics. Proteins representative of the major biological functions, heat shock proteins, energy metabolism, oxidative stress, structural proteins, proteolysis, transport, signaling, and apoptosis, are described. The new knowledge thus produced are presented and discussed.

Cette étude publiée dans Animal (2015) 9:1, pp 179–190 a porté sur la possibilité de prédire la qualité sensorielle de la viande bovine de différents muscles de la carcasse ou d’un muscle donné à partir des teneurs en fer héminique, lipides intramusculaires, eau, e t collagène total, soluble ou insoluble. Au total, 540 consommateurs français naïf s ont noté sur une échelle de 0 à 100 la tendreté, l’appréciati on de la flaveur, la jutosité et l’appréciation globale de six muscles grillés : le gîte noix ( biceps femoris ), le tende de tranche ( semimembranosus ), le faux-filet ( longissimus ), le rumsteck ( gluteus medius ), le paleron ( infraspinatus ) et le filet ( psoas major ) prélevés sur 18 bovins français et 18 bovins australiens. Les quatre notes issues de l’analyse sensorielle o nt été combinées en une note sy nthétique appelée MQ4 (« Meat Qu ality 4 »). Tous muscles confondus (n = 6), les caractéristiques biochimiques me surées sauf la teneur en collagène soluble ont un effet signifi catif sur les 4 notes sensorielles et sur la note globa le MQ4. Les teneurs en lipides intramusculaires font varier en moyenne de 34,9 points (sur l’ échelle de 100) les 4 notes sensorielles renseignées par les consommateurs, le fer héminique de 5,1 points, l’eau de 7,2 points, le collagène tota l de 36,3 points et le collagène insoluble de 41,3 points. En revanche, quand la varia bilité entre muscles est prise en compte, seules les teneurs en lipides intramusculaires et en eau ont u n effet significatif pour un mu scle donné sur l’appréciation globale (5,9 et 6,2 points sur 10 0 respectivement) et la flaveur (6,1 et 6,4, points respectivement)., In this study published in Animal (2015) 9:1, pp 179–190, the ability of the biochemical measure ments, heme Iron, IMF% (intramuscular fat), moisture content and total, soluble and insoluble collage n contents, to predict untrained consumer sensory scores both across different muscles and within the same muscle from different carcasses wer e investigated. Sensory scores from 540 untrained French consum ers for tenderness, flavour liking, jui ciness and overall liking were obtained on a 100-point scale for six muscles; outside ( m. biceps femoris ), topside ( m. semimembranosus ), striploin ( m. longissimus ), rump ( m. gluteus medius ), oyster blade ( m. infraspinatus ) and tenderloin ( m. psoas major ) from each of 18 French and 18 Australian studied cattle. The four sensory scores were weighted and combined into a single score termed MQ4 (« Meat Quality 4 ») which was al so analysed. When evaluated ac ross the six different muscles, a ll biochemical measurements, e xcept soluble collagen content, had a significant effect on all of the sensor y scores and MQ4. The average ma gnitude of impact of IMF%, heme iron, moisture content, total and insoluble collagen contents across the four different sensory scores were 34.9, 5.1, 7.2, 36.3 and 41.3 points respectively. When evaluated within the same muscle, only IMF% and moisture conten ts had a significant effect on overall liking (5.9 and 6.2 resp ectively) and flavour liking (6.3 and 6.4 respectively).

Some proteins have been revealed as biomarkers for beef tenderness and adiposity by previous studies. The abundanceof these biomarkers could be affected by muscle, animal type (age, gender, breed) and the production system. Thisstudy analyzed the effects of animal and muscle type on the abundance of 20 biomarkers of meat tenderness andadiposity. The studied animals were 15 steers and 86 cows of the Maine Anjou PDO, and muscles were Longissimusthoracis, Rectus abdominis, Semimembranosus, Semitendinosus, Triceps brachii. The results showed that the abundanceof the majority of tenderness or adiposity biomarkers varied significantly between muscles. Rectus abdominis is themost different from other muscles. Gender had an effect on the abundance of several biomarkers in four muscles. InTriceps brachii no effect of gender was observed. These results are valuable and should be considered when predictingmeat tenderness and/or adiposity from the biomarker abundance and also when choosing the best predictor muscle.

Cette revue a pour objectif de faire un point sur les avancées récentes obtenues dans le domaine de la prédiction de la qualité des viandes. Elle aborde différentes démarches menées au sein des principales filières de production pour développer des équations puis des outils prédictifs basés sur différents types de marqueurs biologiques (génomiques ou phénotypiques) ou physiques (spectroscopiques). Au travers des différents exemples présentés, il apparaît que l’identification de marqueurs biologiques se confronte au déterminisme complexe des paramètres de qualité qui rend encore difficile la mise au point de tests moléculaires génériques utilisables sur le terrain. Toutefois, les avancées ont été notables ces dernières années bénéficiant des récents développements technologiques en génomique, protéomique et métabolomique. Les premières équations de prédiction de la qualité sensorielle et du potentiel technologique des viandes laissent entrevoir des possibilités d’applications dans les années à venir. Concernant la spectroscopie, les principaux résultats ont été obtenus dans le domaine de la Spectroscopie Proche Infrarouge (SPIR) avec des développements aboutis pour prédire la composition et la valeur nutritionnelle des viandes. La prédiction du potentiel technologique des viandes à l’aide de cette méthode et surtout de la qualité sensorielle est en revanche plus difficile. Enfin, l’exemple du modèle phénotypique MSA (« Meat Standards Australia ») de prévision de la qualité sensorielle de la viande bovine basée sur une combinaison de données d’amont et d’aval et dont la plus-value pour la filière a été démontrée en Australie, présente une généricité qui a déjà été éprouvée dans plusieurs pays., This review was aimed at providing an overview of recent advancements obtained in the field of meat quality prediction. The different methods used in the production sectors for the development of equations and the tools used based on different types of biological markers (genomic or phenotypic) or physical (spectroscopy) are discussed. Through the different examples that are presented, it appears that the identification of biological markers is confronted with the complex determinism of quality parameters. This makes the development of generic molecular tests to be used on the field even more difficult. However, in recent years, progress has been made, benefitting from genomics, proteomics and metabolomics technological developments. The first equations that predict the sensorial quality and the technological potential of meat hint to possible applications in the near future. Concerning spectroscopy, the main results were obtained using Near Infrared Spectroscopy (NIR) with developments obtained for the prediction of the composition and nutritional value of meats. The prediction of the technological potential of meats using this method and mainly the sensorial quality is, however, more difficult. Finally, the example of the MSA (« Meat Standards Australia ») phenotypic model which predicts the sensorial quality of bovine meat based on a combination of upstream and downstream data and whose added-value for the sector has been identified in Australia, presents a genericness that has already been proven in several countries.

Cette revue a pour objectif de faire un point sur les avancées récentes obtenues dans le domaine de la prédiction de la qualité des viandes. Elle aborde différentes démarches menées au sein des principales filières de production pour développer des équations puis des outils prédictifs basés sur différents types de marqueurs biologiques (génomiques ou phénotypiques) ou physiques (spectroscopiques). Au travers des différents exemples présentés, il apparaît que l’identification de marqueurs biologiques se confronte au déterminisme complexe des paramètres de qualité qui rend encore difficile la mise au point de tests moléculaires génériques utilisables sur le terrain. Toutefois, les avancées ont été notables ces dernières années bénéficiant des récents développements technologiques en génomique, protéomique et métabolomique. Les premières équations de prédiction de la qualité sensorielle et du potentiel technologique des viandes laissent entrevoir des possibilités d’applications dans les années à venir. Concernant la spectroscopie, les principaux résultats ont été obtenus dans le domaine de la Spectroscopie Proche Infrarouge (SPIR) avec des développements aboutis pour prédire la composition et la valeur nutritionnelle des viandes. La prédiction du potentiel technologique des viandes à l’aide de cette méthode et surtout de la qualité sensorielle est en revanche plus difficile. Enfin, l’exemple du modèle phénotypique MSA (« Meat Standards Australia ») de prévision de la qualité sensorielle de la viande bovine basée sur une combinaison de données d’amont et d’aval et dont la plus-value pour la filière a été démontrée en Australie, présente une généricité qui a déjà été éprouvée dans plusieurs pays., This review was aimed at providing an overview of recent advancements obtained in the field of meat quality prediction. The different methods used in the production sectors for the development of equations and the tools used based on different types of biological markers (genomic or phenotypic) or physical (spectroscopy) are discussed. Through the different examples that are presented, it appears that the identification of biological markers is confronted with the complex determinism of quality parameters. This makes the development of generic molecular tests to be used on the field even more difficult. However, in recent years, progress has been made, benefitting from genomics, proteomics and metabolomics technological developments. The first equations that predict the sensorial quality and the technological potential of meat hint to possible applications in the near future. Concerning spectroscopy, the main results were obtained using Near Infrared Spectroscopy (NIR) with developments obtained for the prediction of the composition and nutritional value of meats. The prediction of the technological potential of meats using this method and mainly the sensorial quality is, however, more difficult. Finally, the example of the MSA (« Meat Standards Australia ») phenotypic model which predicts the sensorial quality of bovine meat based on a combination of upstream and downstream data and whose added-value for the sector has been identified in Australia, presents a genericness that has already been proven in several countries.

National audience; Ossification score and animal age are both used as proxies for maturity-related collagen crosslinking and consequently decreases in beef tenderness. Ossification score is strongly influenced by the hormonal status of the animal and may therefore better reflect physiological maturity and consequently eating quality. As part of a broader cross-European study, local consumers scored 18 different muscle types cooked in three ways from 482 carcasses with ages ranging from 590 to 6135 days and ossification scores ranging from 110 to 590. These scores were analysed with a linear mixed effects model using the full range of data and then again separately for carcasses with lesser and greater maturity. Across all the data, and for the carcasses with greater maturity, animal age had a greater magnitude of effect on eating quality than ossification score. In contrast, age had no relationship with eating quality for carcasses with lesser maturity leaving ossification score as the more appropriate measure. This is likely due to a loss of sensitivity in mature carcasses where ossification scores are approaching the maximum value. Therefore ossification score is more appropriate for most commercial beef carcasses however it is inadequate for carcasses with greater maturity such as cull cows.

National audience

National audience; Relationships with CIE-L*a*b* colour traits of protein biomarkers known to be related to tenderness were studied in Longissimus thoracis muscles from 21 French Blonde Aquitaine young bulls. L*, a* and b* coordinates were correlated with 9, 5 and 8 of the 21 biomarkers, respectively. Regression models explained between 47 and 65% of the variability between individuals in L*a*b* values. Results suggest that development of colour and tenderness may share common biological pathways. They further show that inducible Hsp70s and μ-calpaïn influence the three colour parameters interactively.

Beef quality

Numéro Hors Série ; Session : Différenciation de l'offre par la qualitéPartenaires des JSMTV 2014 : Polytech Clermont-Ferrand, France.VetAgro Sup, Institut d'Enseignement Supérieur et de Recherche en Alimentation, Santé Animale, Sciences Agronomiques et de l'Environnement, France.ADIV, Association pour le Développement de l'Institut de la Viande, France.IDELE, Institut de l'Elevage, France.IFIP, Institut du Porc, France.ITAVI, Institut Technique de l'Aviculture et des Elevages de Petits Animaux, France.CTPA, Centre Technique des Productions Animales et agroalimentaires, France.CIV, Centre d'Information des Viandes, France.; In order to examine the role of Hsp27 in the molecular mechanisms underlying tenderness, we generated an HspB1-null mouse (Kammoun et al., 2013). The mutant mouse was viable, fertile and showed neither apparent morphological noranatomical alterations. The macroscopic or microscopic muscle phenotype was not altered. However, there was evidence for a muscle-type specific alteration of the molecular phenotype in relation to 1) apoptosis, Hsp status and anti-oxidant status in an oxidative muscle and 2) Hsp status and calcium homeostasis in a glycolytic muscle. Lastly, a preliminary transmission electron microscopy experiment revealed ultrastructural abnormalities in the myofibrillar structure of mutant mice. These data suggest that Hsp27 could directly impact the organisation of the muscle cytoskeleton and contribute to the determinism of tenderness at the molecular and ultrastructural levels.

Muscle connective tissue is found at three levels of scale: the epimysium, which surrounds the muscle; the perimysium, which surrounds bundles of muscle fibers; and the endomysium, which surrounds muscle fibers. It is mainly composed of collagen and is recognized as responsible for the basal toughness of moderately cooked meat. Meat texture increases with amount and extent of collagen cross-links. These parameters are variable in the muscles, which causes broad variability in meat tenderness. This article is an overview of knowledge on intramuscular connective tissue properties that contribute to meat quality, particularly texture.

L'évaluation du « grain de viande » est une appréciation subjective, utilisée par certains chevillards et bouchers pour sélectionner et orienter les carcasses, un grain extrêmement fin étant synonyme de qualité. Pour évaluer la pertinence de cette notion quatre études ont permis i) d’objectiver la notion de grain de viande par une approche ethnologique, ii) de formaliser ce savoir-faire dans une grille de notation en vif et en carcasse, iii) d’évaluer les propriétés physicochimiques des quatre muscles utilisés par les experts pour juger une carcasse, et iv) d’évaluer l’existence d’un lien entre l’évaluation du grain de viande et la qualité sensorielle des viandes. Les seize indicateurs consignés dans la grille établie sur la carcasse sont répétables et facilement utilisables en abattoir. Sur le muscle longissimus thoracis, les grains fins ont été caractérisés par des teneurs en lipides intramusculaires significativement plus faibles que les grains grossiers, conduisant à des notes d’intensité de flaveur également significativement plus faibles, mais sans répercussions sur les notes de jutosité. Il n’est pas apparu de différence significative de tendreté entre les muscles à grains fins et grossiers. Au niveau physicochimique, le grain fin a été associé à des muscles nécessitant une moindre force de cisaillement sur la viande cuite et présentant une moindre teneur en collagène, sans différence sur sa solubilité, laissant supposer un effet favorable sur les propriétés sensorielles. Les écarts sont cependant très dépendants du muscle étudié et méritent d’être confirmés à plus grande échelle., The assessment of the meat “grain” size is an empirical method used by some butchers in France to predict the tenderness of meat: the finer the grain the higher the quality. Four studies are presented here. After a characterization of this notion using an ethnological approach, two grids were built to objectivate the way of evaluating grain of meat on live animals and carcasses. The second aim was to characterize the main muscles used by the experts to rate the grain of meat. The last aim was to establish the relation between the score of meat grain estimated on the carcass and the tenderness of the longissimus thoracis muscles estimated by sensory evaluations. A group of 16 criteria were identified on the carcass as effective to anticipate overall “grain of meat” score. “Fine grain” carcasses were associated with lower lipid content than “coarse grain” in longissimus thoracis muscles, leading to significantly lower scores of flavor intensity without any impact on juiciness scores. No significant relation appeared between grain of meat and tenderness. The shear force needed to cut a broiled sample was found significantly higher for “coarse grain” carcasses than for “fine grain” ones. The total collagen in the “coarse grain” group was significantly higher than those from the “fine grain” group without any impact on collagen solubility. Taken together, these results allow hypothesizing that “fine grain” could have a positive impact on meat quality traits. The differences underlined are nevertheless very muscle-dependant and remain to be confirmed in larger trials.

L’objectif de ce travail a été d’évaluer le lien entre le type de vaches de réforme de l’AOP Maine Anjou, les pratiques de finition et la qualité de la viande. Pour cela, les muscles Longissimus Thoracis (LT) et Rectus Abdominis (RA) de 111 vaches de réforme de race Rouge des Prés ont été prélevés et caractérisés physico- chimiquement et sensoriellement (RA uniquement). Les pratiques de finition et les caractéristiques des vaches ont été renseignées par enquête individuelle. Des groupes de vaches et de finition ont été définis par classification ascendante hiérarchique et leurs effets sur la qualité de la viande ont été définis par analyse de variance. Trois types de vache ont été définis : des vaches jeunes et légères à aptitude laitière moyenne (J_leg ; n= 51) ; des vaches âgées et lourdes à bonne aptitude laitière (V_lait ; n= 32) ; des vaches jeunes et lourdes à faible aptitude laitière (J_lourde ; n= 13). Quatre pratiques de finition ont été définies : finition longue (142 j) avec un mélange foin/enrubanné et 5,8 kg/j de concentré (LonF, n= 17) ; finition courte (80 j) au foin ou enrubanné avec 8,0 kg/j de concentré (FoinF, n= 41) ; finition moyenne (107 j) au foin avec 9,7 kg de concentré (ConF, n= 18) ; finition courte (86 j) à l’herbe pâturée avec 7,6 kg/j de concentré (PatF, n= 21). Pour le muscle LT, les vaches V_lait se caractérisent par une taille de fibres, une teneur en lipides intra-musculaires (LIM) et un rapport gras/muscle (G/M) plus élevés ; la finition PatF augmente la proportion de fibres IIA (aux dépens des fibres IIX) et les indices de couleur a* et b* ; la finition ConF augmente fortement le rapport G/M. Pour le muscle RA, les vaches J_lourde se distinguent des J_leg par des proportions de fibres IIX et LIM plus faibles et une proportion de fibres I plus forte ; la tendreté est plus faible pour la viande des vaches J_leg ; les finitions ConF et PatF induisent les meilleures notes de tendreté et la finition LonF les meilleures notes de jutosité et de flaveur. Ces travaux permettent de proposer des adaptations de conduites de finition des vaches de réforme pour mieux maîtriser la qualité de la viande dans l’AOP Maine Anjou., Our objective was to study the link between the animal type of Maine-Anjou PDO culled cows, finishing practices and meat quality. Longissimus Thoracis (LT) and Rectus Abdominis (RA) muscles were collected from 111 Rouge des Prés culled cows. Physico-chemical characteristics (LT and RA) and sensory traits (RA) were measured. Individual surveys were led to collect finishing practices and animal characteristics. Animal type and finishing groups were created using a hierarchical ascendant clustering and their effects on meat quality were studied (procGLM). Three different culled cow types were defined: young and light cows with medium milking ability (Y_lig;n=51); old and heavy cows with good milking ability (O_Milk; n=32); young and heavy cows with low milking ability (Y_Heavy; n=17). Four finishing groups were defined: long period (142 d) / mix hay-haylage diet with 5.8 kg/d ofconcentrate (LonF, n= 17); short period (80 d) / hay or haylage with 8.0 kg/d of concentrate (HayF, n= 41); average period (107 d) / hay with 9.7 kg/d of concentrate (ConF, n= 18) ; short period (86 d) / pasture with 7.6 kg/d of concentrate (PastF, n=21). LT muscle results: O_Milk cows had higher fibre size, intramuscular fat (IMF) content and fat to muscle ratio ; PastF increased the proportion of IIA fibres (at the expense of IIX fibres) and a* and b* colour indexes; ConF increased the fat to muscle ratio. RA muscle results: Y_heavy cows, in comparison to Y_lig cows, had lower IIX fibre proportion and IMF content and higher I fibre proportion; tenderness was lower in Y_lig cows; Tenderness score was higher with ConF and PastF practices and Juiciness and flavor scores were higher with LonF practices. These results make modifications in culled cows finishing practices possible therefore improving Maine-Anjou PDO meat quality.

Un des enjeux de la filière bovine est la maîtrise et la prédiction de la tendreté de la viande, critère important pour les consommateurs. Ce travail avait pour objectif de mieux prédire la tendreté par méta-analyse à partir des caractéristiques biochimiques du muscle. Pour cela, nous nous sommes appuyés sur la base de données BIF-Beef regroupant des données individuelles issues de plusieurs programmes de recherche, allant de l’animal à la viande en passant par la carcasse et le muscle. Après avoir identifié par une approche par classe de tendreté les caractéristiques musculaires associées à la tendreté, nous avons montré que ces caractéristiques sont différentes entre muscles et types d’animaux. Dans le muscle Longissimus thoracis (entrecôte) des taurillons, la surface moyenne des fibres musculaires est la variable qui joue le principal rôle sur la tendreté sensorielle, l’ensemble des caractéristiques musculaires étudiées expliquant 7% de la variabilité des notes de tendreté. Principalement dans le muscle Semitendinosus (rond de gîte), les teneurs en collagène total et insoluble et l’activité du métabolisme glycolytique sont les principales variables associées à la force de cisaillement, l’ensemble des caractéristiques musculaires étudiées expliquant 21% de la variabilité de la force de cisaillement.

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Beef tenderness is characterised by a high and uncontrolled variability. This variability depends at least in part on differences in muscle characteristics. From data available in the BIF-Beef (Integrated and Functional Biology of beef) data warehouse, we aim to identify general laws between beef tenderness and muscle characteristics. Tenderness was evaluated by sensory method and shear force. The following muscle traits were measured on both Longissimus thoracis (LT) and Semitendinosus (ST) muscles: total and insoluble collagen contents, intramuscular fat content, mean muscle fibre area, glycolytic and oxidative enzyme activities and the proportion of the different types of muscle fibres. Mainly in ST muscle, total and insoluble collagen contents and the Lactate Dehydrogenase activity explain 6%, 6% and 4% respectively of the variation of shear force. However, in LT muscle only, the mean muscle fibre area explains 2% of the variability of sensory tenderness score.

The objectives of the study were to evaluate allelic frequencies and to test the association of polymorphisms in the calpastatin (CAST) and μ-calpain (CAPN1) genes with meat tenderness in 3 French beef breeds. A total of 1,114 Charolais, 1,254 Limousin, and 981 Blonde d'Aquitaine purebred young bulls were genotyped for 3 SNP in the CAST gene and 4 SNP in the CAPN1 gene. Two of these markers, 1 in each gene, can be found in Australian or American commercial genetic tests. Others have previously been reported in American studies or are newly evidenced SNP. The quantitative traits studied were Warner-Bratzler shear force and a tenderness score evaluated by trained sensory panels. All the SNP were informative in the 3 breeds. Associations of individual markers or haplotypes with traits were analyzed. The results differed in the 3 breeds. The G allele of a CAST marker (position 97574679 on Btau4.0) was found to exert a significant effect on the shear force (+0.18 phenotypic SD; RSD) and tenderness score (-0.22 RSD) in the Blonde d'Aquitaine breed. In the same breed, this marker was associated with another CAST SNP (position 97576054 on Btau4.0) such that the GA haplotype appeared to be associated with tougher meat. Two CAPN1 markers (positions 45221250 and 45241089 on Btau4.0) had a significant effect on both traits in the Charolais breed (from |0.11| to |0.25| RSD). In the same breed, these markers were associated with another CAPNI SNP (position 45219395 on Btau4.0) such that the ACA and AGG haplotypes appeared to be associated with a tender meat and a tougher meat, respectively. Consequently, the present results indicate that the effects of the markers studied are breed-specific and cannot be extended to all Bos taurus breeds. Further studies are also required to identify other more appropriate markers for French beef breeds.

The aim of this work is to characterize muscular tissue by evaluating its quality from imaging data. More precisely, we intend to develop prediction tools of bovine meat tenderness based on arti cial vision process, by studing intramuscular connective tissue, which contributes in a signi cant manner to the intrinsic toughness of meat. The images of muscle slices were made using two types of lighting: polarized white light and ultraviolet. Our contribution to analyze the meat images is based on a multiscale approach. Two methods of segmentation were proposed, both based on discrete wavelet transform, in particular the "à trous" algorithm. The rst one is based on the universal thresholding and the second, on the k-means algorithm applied on the image resulting from the summation of wavelet planes. Another section of this work deals with parameters extraction and decision. Information retained is the distribution of considered object sizes of the meat connective network. Statistical tools which are the linear regression and neural networks were applied on data issued from stages of image processing. The nal model retained for tenderness prediction was determined according to a maximization criterion of R2. The choice of the number of parameters was based on a cross validation criterion (Leave one out). Prediction results, derived from data base of the study, are very encouraging highlighting an undoubtedly correlation between the images parameters and sensory quality of meat particulary tenderness., L'objectif de ce travail est de caractériser le tissu musculaire en évaluant sa qualité à partir de données d'imagerie. Plus précisement, on se propose de développer des outils de prédiction de la tendreté de la viande bovine, basés sur le processus de vision artificielle, en étudiant le tissu conjonctif intramusculaire qui contribue de manière significative à la dureté intrinsèque de la viande. Les images des coupes de muscles, ont été acquises avec deux types d'éclairage : lumière blanche polarisée et ultraviolet. Notre contribution pour analyser ces images est basée sur une approche multiéchelle. Deux méthodes de segmentation ont été proposées, elles sont basées sur la transformée en ondelettes discrète, notamment l'algorithme "à trous". La première repose sur le seuillage universel et la seconde sur l'algorithme de K-moyennes appliqué à l'image résultante d'une sommation sur les plans d'ondelettes. Un autre volet de ce travail concerne l'extraction des paramètres et la décision. L'information retenue est la distribution des tailles d'objets éléments de la trame conjonctive de viande. Les outils statistiques que sont la régression linéaire et les réseaux de neurones ont été appliqués aux données issues des étapes de traitement des images. Le modèle final qui a été retenu pour la prévision de la tendreté a été déterminé selon un critère de maximisation du R2. Le choix du nombre de paramètres a été basé sur un critère de validation croisée (Leave one out). Les résultats de prédiction, issus de la base de données d'étude, sont très encourageants, mettant en évidence une corrélation certaine entre les paramètres d'images et la qualité sensorielle de la viande en particulier la tendreté.

This study was carried out to evaluate muscle characteristics, meat ten derness and nutritional qualities of Benin indigenous cattle raised on natural pasture. Thus, 10 Zebu Fulani, 10 Borgou and 5 Lagunaire were slaughtered at 5 years old and their Longissimus thoracis muscle samples were collected for analyses. Lactate dehydrogenase activity of Zebu Fulani was higher (p0.05). As for isocitrate dehydrogenase, citrate synthase, cytochrome oxidase and phosphofructokinase, no significant difference was observe d between the three breeds (p>0.05). By contrast, the total collagen content of Borgou (5.2 mg OH - proline/mg dry matter) was higher (p0.05) while the Zebu Fulani had the highest values (p