Journal Articles
Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915
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Item Applying equineRSU and seasonal livestock correction to wider equine stud farm types(Taylor and Francis Group, 2024-09-12) Chin YY; Airey H; Horne DJ; Gee EK; Back PJ; Sclater J; Rogers CW; Sneddon NTo adjust for potential overestimations in the nitrogen excretion by horses within Overseer®, a revised stock unit system has been proposed (equineRSU). These equineRSU were generated and validated using a medium-sized equine farm as a model farm. The aim of this study was to test the application of the equineRSU and seasonal stock number adjustment on a more complex farming model. Livestock numbers and management data were captured prospectively for the base property (128.8 ha) of a large multi-property commercial breeding stud (3 support properties, 556 ha total area) between June 2022 and May 2023. The monthly on-farm metabolisable energy (ME) requirement and pasture demand were deterministically modelled with both a customised feed budget using livestock class and weight or using the equineRSU and monthly adjusted stock numbers. There were multiple complex movements of horses on and off the property in the different stock classes across the year, with stock management reflecting seasonal periods of high stocking density. There was good agreement (6% variance) between actual ME demand (complex feed budget) and estimated feed demand (simplistic equineRSU model) of 4,387,187 MJ vs 4,102,770 MJ. This suggests that the equineRSU could be used on complex equine farm systems within Overseer®.Item Quantification of relative stock units for horses to permit correct application within pasture-based production systems(CSIRO Publishing, 2023-05-29) Chin YY; Back PJ; Gee EK; Horne DJ; Rogers CW; Bryden WContext. Overseer® is the primary software tool used to estimate farm-level nutrient cycle and management for regulatory purposes in New Zealand. The model compares feed demand among different livestock by using ‘revised stock units’ (RSUs, the annual energy requirement of a mature ewe to raise a single lamb to weaning; 6000 MJ metabolisable energy). The RSUs for several common equine stock classes are not yet available, while those currently available within the model are based on the linear scaling of feed demand to liveweight, which does not consider allometric scaling of metabolism to liveweight or the differences in digestive physiology and nutrient metabolism between ruminants and monogastric hindgut fermenters (horses). Aim. To compare the current RSU values used in Overseer® for different equine stock classes, with the equineRSU values calculated using equine-specific models. Methods. Weighted average estimates of the bodyweight for the different equine livestock classes were calculated from the published literature. These weighted average estimates of bodyweight were used to estimate the energy requirements on the basis of data published by National Research Council. The resulting dry-matter intake and N intake from the equineRSU values and the current RSU values in use within Overseer® were modelled using published data on diet composition, crude protein content and the digestibility of the different feeds offered. Results. The current RSUs in Overseer were 2.5–6.8 units higher than the equineRSU values obtained from the equine-specific models. This overestimation in feed demand resulted in N-intake estimates at an animal level being 52–108% higher than values derived using the equine-specific estimates. Conclusion. The use of RSUs based on linear scaling of feed demand from ruminants on the basis of liveweight overestimates feed demand and N intake in horses. If horses are to be included within nutrient management models, feed demand must be based on published equine data for energy requirements to avoid over-inflation of N excretion. The equineRSUs calculated in this study reduce the risk of over-inflation of N intake and excretion, and subsequently the N leaching estimations. Implication. Failure to accurately model feed demand of horses within nutrient management software would unfairly compromise stocking density and horse management on large commercial breeding farms. The implication for these errors on economic impact and restricted livestock number is greatest for the Thoroughbred breeding industry due to the scale of the operations.
