FIELD: biotechnology.
SUBSTANCE: invention relates to the field of biotechnology. Invention is a method for selection of embryo donor cows in the process of embryo transplantation and involves prediction of the embryo cow ovary response to polyovulation stimulation by exogenous gonadotrophins, wherein the ovarian response is predicted by carrying out an endorectal ovarian and yellow body examination in a donor cow using an ultrasonic sonography method and performing morphometric measurements of ovary and yellow body parameters. According to the method, the volume of the yellow body and the volume of the ovary are measured morphometrically, the relation of the volume of the yellow body to the volume of the ovary is calculated as a percentage, by the index of which the ovarian response is predicted in accordance with the following predictor criteria, where value of 30 % and less predicts a variability of the ovarian response in range of 0 to 2 yellow bodies, which is a prognostic probability of a negative or low ovarian response, at ratio of 31 to 40 %, the ovarian response in range of 3 to 9 of the yellow bodies is predicted, which is the prognostic probability of the average ovarian response, at ratio of 41 to 50 %, the ovarian response in range of 10 to 23 yellow bodies is predicted, which is the prognostic probability of high ovarian response, if the ratio is more than 50 %, the ovarian response of 0 yellow bodies is predicted, which is the prognostic probability of a negative ovarian response associated with ovarian pathology, and at ratio of 30 to 50 % corresponding to a range of yellow bodies of 3 to 23 pieces, the animal is selected to participate in embryo transplantation technology.
EFFECT: invention provides more accurate selection of animals exhibiting a positive poliovulatory reaction to introduced gonadotropins.
1 cl, 2 tbl, 4 ex
Title | Year | Author | Number |
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METHOD FOR PREDICTION OF OVARIAN RESPONSE OF EMBRYO DONOR COWS TO STIMULATION OF POLYOVULATION BY EXOGENOUS GONADOTROPHINS | 2018 |
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Authors
Dates
2019-09-05—Published
2018-12-25—Filed