The main goal of breeders today is the breeding of animals that provide the most effi cient and
profi table production. The paper presents the results of the assessment of the infl uence of genetic
and paratypic factors on the main economically signifi cant features of the Romanov sheep breed
bred in the Yaroslavl Oblast. It was found that the controlled signs are largely due to the infl uence
of genetic factors – the effects were 71.6% by live weight and 74.4% by fertility at the fi rst
lambing. In particular, the live mass of the proband is signifi cantly infl uenced by the effects of the
herd, the live mass of the father, the live mass of the mother and the effect of the tribe; fertility is
infl uenced by the effects of the herd, the live mass of the mother, the type of birth of the mother
and the level of the breeding nucleus. The monitoring of population-genetic parameters of productive
traits of the Romanov sheep breed has shown that the group of fathers of probands with
low genetic and average phenotypic variability in live weight is characterized as a good genetic
material. Further improvement is possible in the selection of the best individuals and the allocation
of new genealogical structures. Evaluation of the maternal basis for fertility has shown
that at a high phenotypic and low genetic variability, the effect of selection can be increased by
regulating environmental conditions that have real effects at the level of 25.6% with the effect of
the mother’s birth type of 22.6%. High genetic and low phenotypic variability for live weight in the herd in the fi rst and the last lambing has been revealed. With high phenotypic variability in
fertility, the heritability of the trait is low. Therefore, the effect of selection can be increased by
regulating environmental conditions. The obtained parameters can be used with high reliability
in breeding modeling, in particular, in the development of genotype assessment models
Keywords
fertility, romanov sheep breed, selection and genetic parameters, linear models, live weight, genotype evaluation models