2018/02/20 by Sandrine Schwob, Antoine Vautier, Schwob, Sandrine +17
Agricultural and Biological Sciences · #Classement #Fermentation and Sensory Analysis #Filing #IRM #Imagerie par résonance magnétique #Lipide intramusculaire #Meat and Animal Product Quality #Muscle longissimus #Porc #Qualité de la viande #Rendement technologique #Spectroscopie de réflectance dans le proche infrarouge NIRS #Swine #Tranchage
paper · doi:10.15454/1.5191196642666567e12
openalex publication_date 2018/02/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/22
This project aimed at providing new early and non-invasive predictors of pork quality usable in slaughter houses, to orientate use of carcasses and cuts and optimize their economic value. For this purpose, the project included development, testing and validation of various methods under industrial conditions. Magnetic Resonance Imaging (MRI) technology was used to estimate the Longissimus muscle intramuscular fat (IMF) content and marbling. Image analysis method was automated to improve measurement rate (400 samples scanned per day) and ensure data traceability. MRI was also used to study the representativeness of IMF content determined at the 13th rib to assess average IMF of the whole Longissimus muscle. Results showed high repeatability and good predictive ability of Longissimus average IMF content with determination at the 13th rib level (R²=0.88). Near Infrared Spectroscopy (NIRS) was used to estimate cooking and slicing yields and structural defects. NIRS technology could predict slicing losses caused by paste-like and cohesion defects on processed loin slices. Finally, gene expressions quantified on Longissimus muscle were used to discriminate 3 pork quality classes: low, acceptable and extra technological and sensory quality levels. The best model to predict meat quality level of pork loins included expression levels of 12 genes.