Using of a comprehensive indicator for estimating productivity parameters in Russian meat merino sheep

Evaluation of animals simultaneously for several economically useful traits is necessary to identify the relationship between genotype and phenotype. It allows to obtain a complex numerical indicator, on the basis of which the ranking of animals is possible. This approach makes it possible to identify the most significant traits for the formation of the phenotype and productivity of animals, the best individuals, and also to determine an effective strategy for breeding work. The method of principal components was used to form a complex indicator of animal productivity. From the used samples of initial data, the maximum, minimum and median values were determined. Then, in the space of the main components, the coordinates of the vectors corresponding to all evaluated animals were determined, and the proximity of these vectors to the reference points was calculated, followed by the formation of the groups: "Head", "Nucleus" and "Tail". The calculations were carried out using the integrated mathematical package MATLAB. It was found out that 82% of the dispersion explains the first six main components. The calculation of the "communality" indicator revealed two of the most significant indicators involved in the formation of meat productivity: the thickness of the fat and femoral muscle determined by ultrasound. The results of calculating the complex indicator of productivity made it possible to identify three groups. Four individuals were assigned to the group "Head", two to the group "Tail", and the rest of the animals in the sample belonged to the group “Nucleus”. The presented algorithm for the formation of a complex indicator of animal productivity makes it possible to evaluate them simultaneously by several economically useful traits for subsequent study of its relationship with the genotype. At the same time, such an assessment does not impose significant restrictions on the number of characteristics used. However, it allows to identify the most significant features in the formation of meat productivity.