Effect of the rate of artificial insemination and paternity knowledge on the genetic gain for French meat sheep breeding programs

Inseminate without hormonal treatment in dairy sheep farms: exploring the consequences on the sustainability of several contrasted production systems

Alternatives to hormonal treatments (HTs) in dairy sheep reproduction management are being explored in response to increasing societal concerns regarding animal welfare and food safety. However, hormone-free reproduction implies higher variability in flock performances and additional constraints for timely synchronised artificial insemination (AI) in the flock, impacting the diffusion of genetic progress. The use of the male effect, a well-known practice to induce synchronised oestrus, combined with precision tools (e.g., heat detector), is a plausible way to implement AI without HT in dairy sheep farms. To date, the consequences of such alternative reproduction management on the whole farm sustainability remain unknown. To anticipate these potential impacts, a multiagent model (REPRIN'OV) was used to simulate dairy sheep farms' sustainability indicators (biotechnical, economic, environmental and workload). A reproduction management scenario, including the use of the male effect followed by AI on the adult ewes (HFAI), was simulated and compared to the current reproduction management of four case study farms (Early_conv, Late_conv, Early_org and Late_org). They were selected to represent the different agricultural models (Conventional or Organic) and reproduction seasons (Early - during spring, out of ewes' natural reproduction season - or Late -from early summer to the end of autumn) of the Roquefort Basin's farms in Southern France. Simulation results showed that the HFAI scenario had different consequences depending on the farm's production system type. A negative effect on most key sustainability indicators of the Conv farms was observed, as a significant reduction in the fertility rate, in the proportion of young ewes born from AI (-54% in both farms; P < 0.05) and in the flock's milk production were observed; while the workload and greenhouse gas (GHG) emissions were increased compared to the initial scenario. In the Org farms, HFAI had neutral to positive effects on most indicators as the fertility, milk production of the flock, workload during milking and GHG emissions were barely affected by this scenario, while an increase in the proportion of young ewes born from AI was observed (+39% and + 43% in each farm, respectively; P < 0.05), allowing a better farm gross margin. Still, the workload during lambing was increased in Early_org (+18%; P < 0.05), as Early farms, tended to be more negatively impacted by HFAI than Late ones. Overall, our simulation approach provides interesting elements to exchange with stakeholders on how to progress towards a socially acceptable reproduction management system, for the dairy sheep sector.

Exploring Endogenous and Exogenous Factors for Successful Artificial Insemination in Sheep: A Global Overview

Artificial insemination (AI) plays a vital role in animal breeding programs. AI is applied to enhance animal genetics and facilitate the widespread integration of desirable characteristics with a high potential for productivity. However, in sheep, this biotechnology is not commonly practicable due to multi-factorial challenges, resulting in inconsistent outcomes and unpredictable results. Thoughtful selection of semen donors and recipients based on genetic merit deeply impacts ovine AI outcomes. Additionally, endogenous factors such as breed, age, fertility traits, genetic disorders, and cervical anatomy in ewes contribute to ovine AI success. Extensive research has studied exogenous influences on sexual behavior, reproductive health, and hormonal regulation, all impacting ovine AI success. These exogenous factors include techniques like estrus induction, synchronization, semen handling methods (fresh/chilled/frozen), and insemination methods (cervical/laparoscopic), as well as nutritional factors and climatic conditions. This overview of the literature highlights the endogenous and exogenous challenges facing successful ovine AI and proposes strategies and best practices for improvement. This paper will serve as a guide for understanding and optimizing the success of ovine AI.

The Role of Housing Conditions on the Success of Artificial Insemination in Intensively Reared Dairy Ewes in Greece

The objective was to assess the effect of housing conditions during the summer months on the success rates of cervical artificial insemination (AI) with cooled semen, in intensively reared dairy ewes in Greece. The study involved 2083 Lacaune ewes from 23 flocks that were serviced during May to September. An estrous synchronization protocol with the insertion of progestogen sponges for 14 days and eCG administration at sponge removal, was used. All ewes were inseminated 54−57 h after sponge removal with cooled semen (15 °C) from 10 Lacaune rams. Pregnancy diagnosis was performed via trans-dermal ultrasonography at 35−40 days after AI. Data recording started the day after sponge placement (15 days prior to AI), and lasted up to 14 days after AI. Daily records included temperature, relative humidity, and Temperature-Humidity Index (THI) inside the shed. Available space and volume per animal, frequency of bedding renewal, access to a yard, and indoor light were also recorded in each farm. Binary logistic regression of data records showed that temperature and THI increases at days −15 to +4 around AI (day 0) had a negative effect on pregnancy rates (reducing the likelihood of pregnancy by 3−6% and 7%, respectively). The latter also decreased significantly (p < 0.05) in farms with high stocking density, non-frequent bedding renewal, and outdoor access by ewes (by 30%, 34%, and 44%, respectively). Overall, the results indicate that appropriate housing conditions are warranted to increase the success of AI in dairy ewes during the summer months.

Efficiency Analysis as a Tool for Revealing Best Practices and Innovations: The Case of the Sheep Meat Sector in Europe

Simple Summary

The European sheep meat sector faces technical, market and financial challenges that threaten its economic performance and overall sustainability. At the same time, the sector is characterized by poor and slow adoption of innovations that could help towards facing these challenges. In this study, the technical efficiency of extensive, semi-intensive and intensive sheep meat farms in France, Spain and the UK was explored to reveal the profile of the most efficient ones and identify the best practices and innovations that these farms apply. The most efficient sheep meat farms reared large flocks, used available infrastructure at full capacity and managed human labor in a rational way. These best farms emphasized feeding and grazing innovations, marketing strategies, breeding programs and use of digital technologies. The uptake of such practices and innovations by farms of similar production systems could help to increase the productivity and economic performance of the sheep meat sector.

Abstract

The slow adoption of innovations is a key challenge that the European sheep sector faces for its sustainability. The future of the sector lies on the adoption of best practices, modern technologies and innovations that can improve its resilience and mitigate its dependence on public support. In this study, the concept of technical efficiency was used to reveal the most efficient sheep meat farms and to identify the best practices and farm innovations that could potentially be adopted by other farms of similar production systems. Data Envelopment Analysis was applied to farm accounting data from 458 sheep meat farms of intensive, semi-intensive and extensive systems from France, Spain and the UK, and the structural and economic characteristics of the most efficient farms were analyzed. These best farmers were indicated through a survey, which was conducted within the Innovation for Sustainable Sheep and Goat Production in the Europe (iSAGE) Horizon 2020 project, the management and production practices and innovations that improve their economic performance and make them better than their peers.