Animal Molecular Breeding 2024, Vol.14, No.1, 27-35 http://animalscipublisher.com/index.php/amb 34 For example, by analyzing historical breeding data, machine learning models can identify key genetic factors that affect milk yield and provide guidance for breeding. In addition, big data analytics can be used to monitor and predict the occurrence of diseases and provide decision support for the health management of dairy cows. 4.3 Sustainable breeding strategies and ethical considerations Sustainable breeding strategies and ethical considerations are increasingly emphasized in the pursuit of increased cow yield and efficiency. Breeding strategies need to take into account environmental protection, such as reducing the impact of animal husbandry on the environment and protecting biodiversity; the breeding process also needs to pay attention to animal welfare to ensure that the health and welfare of dairy cows are not neglected. The application of emerging technologies such as gene editing has also triggered discussions on ethics and social acceptance, and how to balance technological advances with ethical considerations to ensure the responsible use of technology has become a non-negligible issue in breeding research. With the continuous progress of science and technology, emerging technologies, big data and machine learning will play an increasingly important role in dairy cattle breeding research. Sustainable breeding strategies and ethical considerations will also guide the direction and methods of breeding. In the future, through the application and comprehensive consideration of these high technologies, dairy cattle breeding will be able to improve yield and efficiency while protecting the environment In the field of modern dairy cattle breeding, with the rapid development of science and technology, the application of emerging technologies, such as CRISPR/Cas9 gene editing, big data analytics, and machine learning, as well as the emphasis on sustainable breeding strategies and ethical considerations are becoming the key factors that will drive progress in the field. of the field. The combined application of these technologies and methods will not only improve the efficiency and accuracy of breeding, but also realize the sustainable development of the dairy industry while safeguarding animal welfare and ecological balance. 5 Conclusion The application of genome-wide association studies (GWAS) technology in the field of milk yield improvement has demonstrated its great contribution and potential. By accurately identifying genes and genetic variants associated with economically important traits such as milk yield, milk fat content and milk protein content, GWAS technology provides a strong scientific basis for breeding and greatly facilitates the development of dairy cattle breeding practices. This study will summarize the contribution of GWAS technology in improving milk yield and provide an outlook for future research and application (Yang et al., 2023). GWAS technology emphasizes the importance of integrating scientific research with actual breeding practices. In the past, breeders often relied on traditional phenotypic selection and family line selection methods, which were effective but limited in accuracy and efficiency.The application of GWAS technology allows breeders to directly target specific genes affecting milk yield, greatly improving the accuracy and efficiency of selection. For example, variants in genes such as DGAT1 and GHR identified by GWAS have been shown to be closely associated with milk yield and milk fat content, making them important markers for breeding selection. The application of GWAS technology has also provided new strategies and directions for breeding. By comprehensively analyzing the entire genome, GWAS not only identifies genes known to affect traits, but also reveals previously unrecognized related genes and genetic mechanisms. This offers the potential for a deeper understanding of the genetic basis of milk yield, as well as the development of new breeding goals and strategies. For example, recent studies have identified a number of new genes affecting mammary gland development and milk synthesis pathways that may be important breeding targets for improving milk yield in the future. Looking ahead, there is still tremendous scope for the application of GWAS technology in improving milk yield. With the advancement of sequencing technology and the reduction of cost, it is possible to sequence the whole genome of more individual dairy cows, which will provide richer and more precise genetic information for GWAS and further improve the precision and efficiency of the study. Meanwhile, in combination with other emerging technologies, such as gene editing, GWAS discoveries can be translated into actual breeding results more quickly.
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