Aquaculture

Genetic Improvement of Feed Efficiency Performance in Large Yellow Croaker

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Abstract

Large yellow croaker (Larimichthys crocea) is an economically important marine aquaculture species in China. Feed costs constitute a substantial proportion of production expenditures, making improvement of feed efficiency essential to sustainable development. Yet quantifying individual feed intake in schooling fish under group-rearing conditions remains a persistent barrier to genetic improvement. To overcome this barrier, we developed an integrated deep learning-based phenotypic measurement platform comprising two modules. The first module quantifies individual feed intake by fusing computer vision with RFID: a restricted feeding station admits a single fish for PIT tag identification and real-time feed pellet detection, achieving 94.5% average accuracy in laboratory validation. The second module performs PIT tag identification and automated measurement of body morphological traits, with correlation coefficients >0.99 relative to manual measurements. Using this platform, we quantified feed efficiency phenotypes in large yellow croaker and conducted genetic analyses. Heritability estimates for feed conversion ratio (FCR) and residual feed intake (RFI) ranged from low to moderate (h² = 0.10-0.24), depending on temperature conditions. Genome-wide association studies implicated loci involved in nutrient absorption and transport, lipid and amino acid metabolism, appetite and energy-balance regulation, and insulin signaling pathways. Genomic selection based on RFI produced a breeding line that, in common-garden evaluation, showed improved performance, including 10.05% reduction in FCR, 0.067 g·day⁻¹ reduction in RFI, and enhanced stress resilience. Additionally, feeding behavior traits showed moderate heritability (h² = 0.23-0.26) and moderate to strong genetic correlations with RFI (rg = 0.53-0.79), indicating their value as auxiliary selection criteria. While the platform demonstrates high accuracy, practical deployment faces constraints as it is currently applicable only to specific controlled environments and fish of particular size ranges. Future scaling efforts will need to address adaptation to diverse environmental conditions and broader size ranges to enhance applicability across commercial aquaculture operations. In summary, we present an intelligent phenotyping approach for feed efficiency traits and its application to genomic selection in fish, achieving genetic improvement in large yellow croaker and offering a practical pathway to lower costs and more sustainable aquaculture.

Keywords: 2026

How to Cite:

Xu, P., Jiang, P., Feng, M., Li, N. & Zhou, T., (2026) “Genetic Improvement of Feed Efficiency Performance in Large Yellow Croaker”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2283150. doi: https://doi.org/10.31274/wcgalp.23488

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