Optimization of silver scat population breeding strategy and germplasm resource improvement based on genetic algorithm

Silverdrum fish is popular among farmers because of its fast growth and easy rearing, so it is important to study the optimization method of the artificial breeding strategy of silverdrum fish stock. In this study, according to the requirements of the breeding environment of silver scat and the experience of experts, the flow rate, water depth, water temperature and light market are the key factors of the optimization model of silver scat breeding, and the multi-objective optimization algorithm NSGA-II is selected as the main method of the optimization model, and the intersection operator and the variational operator in the algorithm are improved, and then the SDR algorithm is proposed as a substitute for the Pareto dominance relationship to enhance the solving ability of the algorithm. The SDR algorithm was found to be the most suitable environment for silver drum breeding when the temperature, flow rate, water depth and light duration were set to 22.5℃, 0.21m/s, 1.7m and 15h, respectively. The results of the breeding experiments showed that the growth and gonadal development of silver drum parents in the optimized breeding strategy group were better than those in the original breeding strategy group, and the survival and growth rates of juveniles were better, so that the breeding effect and germplasm resources of silver drum were improved. This study can provide a theoretical basis and technical support for the decision-making of artificial breeding and germplasm resources improvement of silver drum stock in the future, and also lays a data foundation for the establishment and improvement of silver drum stock breeding farm.