Ultrasound-Based Phenotyping for Genetic Selection of Carcass Traits in Oreochromis niloticus: Integrating Imaging Technology Into Aquaculture Breeding.

Recent years have witnessed a remarkable global surge in fish production, with Nile tilapia (Oreochromis niloticus) emerging as a prominent contributor owing to its high demand as a nutritious food source. However, unlike terrestrial species, maintaining genealogical control and collecting phenotypic data in fish farming poses significant challenges, necessitating advancements to support genetic improvement programmes. While conventional methods, such as body measurements using rulers and photographs are prevalent in data collection, the potential of ultrasound-a less invasive and efficient tool for fish measurement-remains underexplored. This study assesses the viability of ultrasonography for genetically selecting carcass characteristics in Nile tilapia. The investigation encompasses data from 897 animals representing 53 full-sib tilapia families maintained in the genetic improvement programme at the Federal University of Lavras. To measure carcass traits, the animals were sedated with benzocaine and ultrasound images were obtained at three distinct points. Subsequently, the animals were euthanised through medullary sectioning for further carcass processing. After evisceration, filleting and skinning, all weights were meticulously recorded. (Co)variance components and genetic parameters of the measured traits were estimated using the Bayesian approach by Gibbs sampling implemented in MTGSAM (Multiple Trait Gibbs Sampling in Animal Models) software. Heritabilities estimated for the studied carcass traits were moderate, ranging from 0.23 to 0.33. Notably, phenotypes derived from ultrasound images demonstrated substantial genetic correlations with fillet yield (0.83-0.92). In conclusion, this study confirms that indirect selection based on ultrasound images is effective and holds promise for integration into tilapia breeding programmes aimed at enhancing carcass yield.