Environmental and additive genetic factors that affect artificial insemination success in Latxa dairy sheep breed

In the Latxa breed, flocks within the breeding program make use of high genetic value rams to inseminate their ewes once per year. Despite the relevance of the insemination results in the genetic progress and on farms’ productivity, external and genetic factors that affect artificial insemination (AI) success have not been up to now explored in this sheep population. For that, 135,351 edited AI records from 63,480 inseminated Latxa Cara Negra from Euskadi ewes, using 853 service rams, collected between 2000 and 2021, were used. The outcome of an AI event was treated as a binary response of either success or failure in becoming pregnant. To identify the environmental factors influencing the AI result, a multiple logistic regression was first calculated on a selection of variables related to the ewes, to the ram, and to other non-sex-specific aspects. With relevant variables detected, a threshold model, including the pedigree information of the inseminated ewes and the service rams, was used to estimate the genetic components of the trait in both sexes. Findings show that the AI success is higher in ewes who had the previous parturition from an AI event, in those with a lambing-AI interval longer than 210d, with 3 years and 2 lambings, with high prolificacy and in those having their first parturition at 1 year of age rather than at 2 or 3 years of age. In counterpart, the higher the milk produced in the nearest record before AI date, the poorer the AI results. Furthermore, relevant variability was linked to the year of insemination, the herd and the technician in charge of the insemination procedure. Regarding genetic parameters, heritability values, on the observable scale, and repeatability were 0.057 ± 0.004 and 0.204±0.007 in females and 0.009 ± 0.037 and 0.032 ± 0.002 in males, respectively. These results evidence that the AI success is under moderately low additive genetic control, with the surrounding environmental variables being the strongest controlling factor. An effort to enhance some farm management practices should be encouraged to efficiently improve reproductive results. Although genetic selection on AI success is viable, the genetic progress may be scarce. An option to improve reproduction by means of selective breeding might be the development of a multi-trait index.