Use of logistic models to evaluate the response of superovulation treatment and embryo production in Santa Inês ewes.

The study aimed to verify the influence of the FecG E mutation in superovulated ewes and to evaluate the probability of logistic models to determine the response capacity of these ewes to superovulatory treatment. Santa Inês ewes (n = 29) were genotyped for the FecG E mutation and separated for their genotype group in carriers of the mutant E allele (FecG E/E , FecG +/E ) and non-carrier (FecG +/+ ) alleles. The ewes underwent hormonal treatment for superovulation. Aside from the genotypes, variables included in the statistical model were reproductive status (empty, early lactation, or late lactation), age (> or < 6 years), and number of births (nulliparous, primiparous, multiparous). The carriers of the mutation could be discriminated from the non-carriers based on the number of corpora lutea, rate of frozen embryos, and fecundity. Recovery rate was significantly higher (P < 0.05) in FecG E/E (94.31%) compared to FecG +/E (63.15%) and FecG +/+ (61.90%) (P < 0.05), whereas fecundity rate of FecG +/+ ewes (50.76%) was significantly higher than FecG +/E (18.96%) and FecG E/E (32.53%) (P < 0.05). We determined in this study that the response to superovulation and embryo production can be discriminated between FecG E/E and FecG +/E ewes in relation to the FecG +/+ genotype. Logistic models that included reproductive status and mutation, or reproductive status and age, or reproductive status and number of births were effective in predicting the response to superovulatory treatment.