A general planner to explore drenching strategies in natural and organic lamb production systems

Abstract

The need for anthelmintic drenching varies from animal to animal. To avoid unnecessary use of drenches it is therefore desirable to formulate drenching rules that apply to the individual, rather than the mob. We used a computer decision support tool called the general planner for agro-ecosystem models (GPAM) to investigate drenching rules for lamb production on a dual organic-conventional farm. The GPAM was combined with a dynamic model of nematode infection in lambs to help understand how varying premiums for organically produced lamb affected optimal drenching decisions. Simulations showed that there was no incentive to produce lambs organically if the premium for organic meat was less than 20%. Even when the premium was increased to 80%, half the lambs slaughtered had conventional status. As the premium increased, more lambs were produced organically and there was greater variation in liveweight between animals, whether drenched or undrenched. This modelling exercise demonstrated that there is potential to devise individualised drenching strategies that return the greatest carcass value for the entire mob. However, it is also clear that without alternative non-anthelmintic strategies to control infection, a significant proportion of the flock will have to be finished using drenches even with high premiums for organic lamb. Keywords: organic lamb production, nematode infection, decision making, artificial intelligence