Visible and near infrared (NIR) reflectance and transmission spectra (400 - 2500 nm) of various flesh foods in various presentations were examined for qualitative and quantitative analysis. Discriminant functions for muscle types and animal species were included. Lamb muscles (n: 306), chicken breast and thigh muscles (n: 48), bull and steer muscles (n: 103), raw fish (n: 80), fish meal (n: 700) and fish oil (n: 160) samples were examined in the experiments. INTACT and MINCED presentation to the instrument were compared, as well as type of muscle (<I>longissimus dorsi, infra spinatus, supra spinatus, semimembranosus, semitendinosus, rectus femoris</I>), effect of sex and both longitudinal (LS) and transverse section (TS) of the muscle on the optical properties and Partial Least Squares (PLS) calibrations for gross composition. MINCED presentation to the instrument gave the best results for the NIRS calibrations in all the muscle tissues utilized, while, INTACT presentation showed poorer calibrations. Muscle type and sex affect the calibrations. Raw fish and fish by-products, both fish meal and oil had good NIRS calibrations for the twelve parameters analyzed. The results show that NIRS is acceptable as a method for determining gross composition in a wide variety of flesh foods in MINCED presentation. Principal component analyses (PCA) and Soft Independent Modelling of Class Analogy (SIMCA) were used for the authentication and classification between muscles and among animal species. The conclusions of this work are that NIRS can successfully predict chemical composition in different muscles in MINCED rather than INTACT presentation. Classifications using PCA and SIMCA were excellent tools to authenticate flesh foods.

Un des enjeux de la filière bovine est la maîtrise et la prédiction de la tendreté de la viande, critère important pour les consommateurs. Inscrite dans le programme européen ProSafeBeef, ma thèse avait pour objectif de mieux prédire la tendreté par méta-analyse à partir des caractéristiques biochimiques du muscle. Pour cela, mon travail de thèse s’est appuyé 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. Une première méta-analyse a montré que le muscle Semitendinosus (ST) est de type plus rapide glycolytique que le Longissimus thoracis (LT) chez les mâles entiers et les femelles mais pas chez les mâles castrés. 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 LT des taurillons, la surface moyenne des fibres musculaires est la variable qui joue le principal rôle sur la tendreté sensorielle où elle explique 2% de la variabilité des notes de tendreté. Principalement dans le muscle ST, les teneurs en collagène total et insoluble et l’activité enzymatique du métabolisme glycolytique expliquent au plus 6% chacun de la variabilité de la force de cisaillement. Malgré ces faibles parts de variabilité expliquée de la tendreté, ces conclusions validées sur un grand volume de données sont importantes pour préparer de nouveaux projets visant à compléter cette démarche en prenant en compte d’autres caractéristiques telles que des biomarqueurs génomiques. / The control of beef tenderness is essential for beef producers and retailers to deliver a consistently high quality product to consumers. Being part of the European program ProSafeBeef, my thesis aimed to predict beef tenderness by meta-analysis approaches using biochemical characteristics of muscles. To achieve this goal, we used data available in the BIF-Beef data warehouse which contains animal, carcass, muscle and meat measurements from different research programs. From available data on Longissimus thoracis (LT) and Semitendinosus (ST) muscles, we demonstrated that ST was faster and more glycolytic than LT in both entire males and females but not in steers. With a cluster analysis, we identified muscle biochemical traits associated with meat tenderness. Then, we demonstrated that no specific muscle biochemical characteristic can be a predictor of tenderness for all muscles and animal types. In LT muscle of young bulls, mean muscle fibre area explained 2% of the variability in sensory tenderness score. Mainly in ST muscle, total and insoluble collagen content and enzymatic indicators of glycolytic metabolism each explained about 6% of the variation in shear force. Although we were only able to explain a relatively small proportion of the total variance in tenderness, these results will form an important basis for the design of future experiments and the identification of new genomic markers of tenderness to be combined with muscle biochemistry in order to better predict beef quality.

Electromyography (EMG) is a common tool in electrical muscle activity measurement and can be used in multiple areas of clinical and biomedical applications, mainly in identifying neuromuscular diseases, analyzing movement or in human machine interfaces. Traditionally a pair of electrodes were used to measure the signals, but in recent years the use of high density surface EMG (HD-sEMG) gained more popularity as it can sample myoelectric activities from multiple electrodes in an array on a single muscle and provide more information. In this thesis a measurement setup and protocol is proposed that can provide a reliably measurement, furthermore multiple features are extracted from the collected signals to characterise the major muscles around the ankle. 5 healthy subjects were tested using an ankle dynamometer with 5 HD-sEMG placed on the Tibialis Anterior, the Gastrocnemius Medialis, the Soleus, the Gastrocnemius Lateralis, and on the Peroneus Longus. Several tests were conducted using different initial angle of the ankle joint and different percentages of the maximum voluntary contraction. The reliability of the setup was assessed by comparing the variance between the collected signals of the same subject in a repeated test, and by comparing different subjects to each other. Results show a reasonably good reliability with less than $10\%$ variance, and adequate selectivity as well. To examine the muscle characteristics, 7 features were extracted from the collected and processed signals, then the features were plotted and compared to signs for muscle characteristics such as muscle fatigue, activation, and spatial distribution of activation. Correlations between features of mean average value (MAV) and zero crossing (ZC), and different muscle characteristics could be observed.