203 Development and evaluation of a dynamic simulation model of farm management strategies affecting the reproductive performance of a suckled beef cow herd. (5th December 2019) - Lynch, Richard
Abstract: Reproductive output in suckled beef cow systems is underpinned by a combination of genetics and the impact of efficient animal management strategies which given their cumulative nature, are difficult to evaluate. A dynamic simulation model (Grange Reproductive Management Model; GReMM) was developed replicating the reproductive performance of a suckled beef cow herd over multiple production cycles using the Stella Architect dynamic modelling platform (isee systems, Ventana, Lebanon, USA). Model inputs for farm parameters include dates and duration of breeding seasons in addition to nutrition and management of the periparturient beef cow. Specific management parameters pertaining to the duration of the postpartum anoestrus interval (PPAI), such as the body condition score of the cow at calving (BCSc), level of postpartum nutrition (PPN), management of the suckling calf and bio-stimulation of the dam pre-breeding are modelled. Outputs are displayed in the form of shifts in calving distribution, calving rates and calves per cow per year. Scenario analysis consisted of the implementation of a BASE scenario representative of current industry best practice (Normal reproductive management; NRM: BCSc, 2.75; PPN, 100 MJ ME/d; ad libitum suckling). Two further scenarios were developed representing a more intensively managed herd, with high levels of nutrition pre and post calving in addition to alternative reproductive management strategies (Intensive reproductive management; IRM), and a herd with a low level of nutritional management pre and postpartum (Poor reproductive management; PRM). Outputs generated in terms of calving distribution over six production cycles, indicated that a shift in the calving spread towards later in the calving season occurred in the PRM scenario, and a small improvement in reproductive efficiency evident in the IRM scenario over NRM. The model developed offers a decision support tool with the capability of evaluating practical on-farm management decisions on herd reproductive performance.