METHODOLOGY OF MODERN SELECTION PROGRAMS IN DAIRY CATTLE

The importance of analytics in dairy farming remains a key factor in the fields of macroeconomics, scientific research, management at the level of individual breeds, farms (herds), ensuring the efficiency of production and animal welfare. Knowledge of such a methodology remains crucial when it is included in a specific scientific and production process in real time. Emphasizing the global potential of the conducted and future research, it is necessary to imagine a competitive environment that is intensively created through the integration of scientific schools, institutions, countries, and as a result of the combination of Database (databases), Knowledge base (knowledge bases), modeling tools with machine learning and artificial intelligence methods. The article is devoted to the analysis of the current state and prospects of dairy cattle breeding. Focusing on ways to achieve a high level of genetic progress through the implementation of effective selection programs, an example of the work of the Animal Genomics and Improvement Laboratory at the United States Department of Agriculture – AGIL (from the English. Animal Genomics and Improvement Laboratory) is given. Being a successful world scientific center, AGIL researches and develops advanced methods of genetic and genomic evaluation of large dairy and small ruminants, directing such research to improve their health, productivity, as well as environmental safety and quality of the resulting products for the world community. Presenting data on the state of the breeding (controlled) livestock in Ukraine of dairy and dual-purpose breeds of cattle, as well as in European countries, the conclusion is made about the need to use existing practices and experience at the level of domestic production. A description of existing methods for evaluation of breeding values and calculating genetic correlations between economically important traits proves the possibility of modeling and predicting such results in selection programs. Examples of the use of feed efficiency assessments, which are beginning to dominate in selection indices, demonstrate the need to revise sometimes traditional approaches that do not take into account the importance of saving energy resources, reducing environmental pollution, losses of “feed” nitrogen and the need to improve the welfare (health) of animals. The principles of building information systems and methods of using artificial intelligence for breeding purposes are presented. Data on the use of the genome editing technique in dairy cattle, as well as the prospects for the application of Omics technologies in the field of dairy cattle breeding, are presented.