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To characterize carcass and meat attributes, such as beef eating quality in specific farming conditions, 31 young grass-fed crossbred Angus x Salers cattle in two farming systems (a mono-cattle system versus a mixed system with beef cattle and sheep) were used in this study. Three muscle cuts (striploin- m. longissimus dorsi et thoracis ; bolar blade- m. triceps brachii caput longum ; internal flank plate- m. obliquus internus abdominis ) were used for consumer eating quality testing and striploin was used for panelist eating quality assessment, and objective measurements [Warner-Bratzler shear force (WBSF) and fatty acid (FA) and antioxidant contents]. Results indicated that the farming system had no impact on carcass characteristics or meat quality, but it tended to affect FA content, which is likely explained by between-system differences in animal maturity (assessed by ossification score). Animal gender had significant effects on three eating quality traits evaluated by untrained consumers, with higher flavor liking, overall liking, and overall meat eating quality (MQ4) scores in females than in males. Additionally, FA contents were correlated with sensory quality traits to varying extents: consumer-scored tenderness, flavor, and overall liking were mainly positively correlated with ω-3 and ω-6 polyunsaturated fatty acid (PUFA) contents, and panelist-evaluated tenderness and abnormal flavor were more positively correlated with total lipids, saturated fatty acid (SFA), and monounsaturated fatty acid (MUFA) contents. Overall, this study showed that specific grass-fed crossbred Angus x Salers cattle can produce lean meat rich in ω-3 PUFAs with a low ω-6/ω-3 ratio and with "better than average" beef eating quality.

The aim of this study was to determine the percentage of healthy veal calves carrying mcr -positive E. coli strains at the time of slaughter in France. Fecal samples were selectively screened for mcr -positive E. coli isolates using media supplemented with colistin. Screening for mcr genes was also carried out in E. coli isolates resistant to critically important antimicrobials used in human medicine recovered from the same fecal samples. Overall, 28 (16.5%) out of the 170 veal calves tested carried mcr -positive E. coli . As some calves carried several non-redundant mcr -positive strains, 41 mcr -positive E. coli were recovered. Thirty-one and seven strains were positive for mcr-1 and mcr-3 genes, respectively, while no strain was positive for the mcr-2 gene. Co-carriage of mcr-1 and mcr-3 was identified in three strains. All mcr -positive E. coli isolates, except one, were multidrug-resistant, with 56.1% being ciprofloxacin-resistant and 31.7% harboring bla CTX-M genes. All mcr-3 -positive E. coli carried bla CTX-M genes, mainly bla CTX-M-55 . This study highlights the high prevalence of mcr -positive E. coli strains in feces of veal calves at the time of slaughter. It also points out the multidrug (including ciprofloxacin) resistance of such strains and the co-occurrence of mcr-3 genes with bla CTX-M-55 genes.

This review is aimed at providing an overview of recent advances made in the field of meat quality prediction, particularly in Europe. The different methods used in research labs or by the production sectors for the development of equations and tools based on different types of biological (genomic or phenotypic) or physical (spectroscopy) markers are discussed. Through the various examples, it appears that although biological markers have been identified, quality parameters go through a complex determinism process. This makes the development of generic molecular tests even more difficult. However, in recent years, progress in the development of predictive tools has benefited from technological breakthroughs in genomics, proteomics, and metabolomics. Concerning spectroscopy, the most significant progress was achieved using near-infrared spectroscopy (NIRS) to predict the composition and nutritional value of meats. However, predicting the functional properties of meats using this method-mainly, the sensorial quality-is more difficult. Finally, the example of the MSA (Meat Standards Australia) phenotypic model, which predicts the eating quality of beef based on a combination of upstream and downstream data, is described. Its benefit for the beef industry has been extensively demonstrated in Australia, and its generic performance has already been proven in several countries.

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 2 = 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: µ-calpain, m-calpain, h2afx and Hsp40 measured in m. gluteobiceps and µ-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.

The beef cattle industry is facing multiple problems, from the unequal distribution of added value to the poor matching of its product with fast-changing demand. Therefore, the aim of this study was to examine the interactions between the main variables, evaluating the nutritional and organoleptic properties of meat and cattle performances, including carcass properties, to assess a new method of managing the trade-off between these four performance goals. For this purpose, each variable evaluating the parameters of interest has been statistically modeled and based on data collected on 30 Blonde d'Aquitaine heifers. The variables were obtained after a statistical pre-treatment (clustering of variables) to reduce the redundancy of the 62 initial variables. The sensitivity analysis evaluated the importance of each independent variable in the models, and a graphical approach completed the analysis of the relationships between the variables. Then, the models were used to generate virtual animals and study the relationships between the nutritional and organoleptic quality. No apparent link between the nutritional and organoleptic properties of meat ( r = -0.17) was established, indicating that no important trade-off between these two qualities was needed. The 30 best and worst profiles were selected based on nutritional and organoleptic expectations set by a group of experts from the INRA (French National Institute for Agricultural Research) and Institut de l'Elevage (French Livestock Institute). The comparison between the two extreme profiles showed that heavier and fatter carcasses led to low nutritional and organoleptic quality., Competing Interests: The authors declare no conflict of interest.