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 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 mutation and separated for their genotype group in carriers of the mutant E allele (FecG, FecG) 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 (94.31%) compared to FecG (63.15%) and FecG (61.90%) (P < 0.05), whereas fecundity rate of FecG ewes (50.76%) was significantly higher than FecG (18.96%) and FecG (32.53%) (P < 0.05). We determined in this study that the response to superovulation and embryo production can be discriminated between FecG and FecG 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.