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Communication Dans Un Congrès Année : 2021

Exploring the impact of within flock variability on hormone-free dairy sheep farm performances

Résumé

Hormone-free artificial insemination (AI) in dairy sheep breeding has been made possible through the development of automated heat detection. However, in order to facilitate its implementation and success, it is necessary to control the synchronisation of heat entry into the flock. It is therefore necessary to understand how to manage the individual variability in heat entry within the flock, inherent in management without synchronising hormones. This variability is related to individual responses to heat induction and synchronisation, which result from the diversity of individual characteristics. To understand how individual characteristics such as age, body condition score (BCS) or milk yield impact the individual responses, as well as the overall flock productive and reproductive performance, we built a dynamic agent-based model. The model integrates ewe’s individual reproduction and lactation processes. We simulated the weekly number of lambings and milk yield. We tested different flock scenarios in which we have increased or decreased the age, BCS and milk yield values, alone or simultaneously, compared to a reference scenario from a hormone-free organic sheep flock (μAge=2.5, μBCS=2.5, μTMY=195 L). The results showed that improving simultaneously age, BCS and milk-yield in the flock (μAge=+0.5, μBCS=+0.5 and μTMY=+50 L) seems to significantly increase flock’s number of lambing (+3%), concentration of lambing over the first lambing period (i.e. the success of synchronisation method) and total milk yield (+4%), whereas decreasing simultaneously the values of those factors (μAge=-0.5, μBCS=-0.5 and μTMY=-50 L) seems to provide the opposite effect (P<0.05). Preliminary simulation results suggest that the model seems adequate to predict how the structure of the ewe population influences the performances of the flock in a hormone-free context. It thus gives us the opportunity to link flock structure with its management strategies in order to design management strategies that would facilitate the implementation and the success of hormone-free AI in dairy sheep farm.
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Dates et versions

hal-03376302 , version 1 (13-10-2021)

Identifiants

  • HAL Id : hal-03376302 , version 1

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Ellen Laclef, Nathalie Debus, Patrick Taillandier, Eliel González García, Amandine Lurette. Exploring the impact of within flock variability on hormone-free dairy sheep farm performances. 72nd Annual Meeting of the European Federation of Animal Science, Aug 2021, Davos, Switzerland. ⟨hal-03376302⟩
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