Predicting the technological quality of chicken meat : new approaches of phenotyping and high-throughput biological and genomic analyzes | OPTIVIANDE Prédiction de la qualité technologique de la viande de poulet : apport de nouvelles approches de phénotypage et des analyses biologiques et génomiques à haut-débit.

Even though meat is increasingly consumed in elaborated form, consumers are sensitive to naturality of the products. This trend is largely taken into account by agribusiness company seeking to reduce additives (flavor enhancers or texturizing agents) or preservatives (in particular salt). This shows the importance of upstream control of quality of the raw material for elaborated products. This issue particularly affects chicken meat, mostly consumed in cut or processed but whose technological quality is highly variable. The objective of the CASDAR OPTIVIANDE project was to develop new phenotyping tools and biological or genetic markers that could be used for selection or evaluation of the impact of breeding factors. The approaches implemented concerned the use of near-infrared spectrometry (NIRS) as well as high-throughput biological and genomic analyzes. The study was based on an original animal model composed of two chicken lines selected in a divergent manner on the ultimate pH of the filet and whose technological and sensory characteristics of meat were very different. Near-infrared spectrometry is fast to implement and makes it possible to predict several technological quality criteria such as ultimate pH, water loss during storage and hardness after cooking. Transcriptomic and metabolomics analyzes made it possible to develop first prediction models based on a limited number of metabolites (blood and muscle) or muscle transcripts. At the genetic level, analyzes made possible to identify the main regions controlling the ultimate pH of the filet and revealed several genes of interest. In conclusion, the project led to significant advances in understanding the genetic and physiological mechanisms involved in the establishment of quality defects in chicken. It opens perspectives of application thanks to the development of prediction tools for selection whose genericity will have to be validated on other populations and in conditions of production