Location: Forage and Livestock Production ResearchTitle: Model predicted DMI, nitrogen (N) excretion and N use efficiency utilizing plasma urea nitrogen (PUN) versus values estimated in conjunction with viable dry matter intake estimates in lambs grazing pasture Author
|Neel, James - Jim|
|Brown, Michael - Retired ARS Employee|
|Belesky, D - West Virginia University|
Submitted to: Journal of Animal Science and Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/18/2019
Publication Date: 2/22/2019
Citation: Neel, J.P., Moriasi, D.N., Brown, M.A., Belesky, D.P. 2019. Model predicted DMI, nitrogen (N) excretion and N use efficiency utilizing plasma urea nitrogen (PUN) versus values estimated in conjunction with viable dry matter intake estimates in lambs grazing pasture. Journal of Animal Science and Research. 3(1). https://doi.org/10.16966/2576-6457.123.
DOI: https://doi.org/10.16966/2576-6457.123 Interpretive Summary: Increasingly, models are being developed and utilized for research, and to predict farm nutrient flow and use efficiency. Although models can be very useful tools, it is extremely vital that they are capable of providing accurate information when research conclusions, and management and political decisions are based on their outputs. Nevertheless, validation of these models is only possible if credible measured data is available from various regions of the world. In 2005 a model was developed that utilized animal blood urea nitrogen (BUN) to predict nitrogen excretion and the efficiency of its utilization (NUE) in sheep and other ruminants. Since the use of N fertilizer improves plant and system productivity, an accurate and affordable way to estimate grazer N excretion avenues and use efficiency would be highly beneficial for improving pasture systems. Based on current literature, this model has not been evaluated, perhaps due to limited availability of appropriate credible measured data. Availability of quality data, obtained from a research study located within a small hill-farm in southern West Virginia, USA, made it possible to evaluate the model developed to predict nitrogen excretion and the efficiency of its utilization in sheep. We evaluated the model’s efficacy utilizing experimentally derived lamb BUN, herbage nitrogen, pasture dry matter intake estimates, and lamb productivity data. Based on the model’s pasture dry matter intake estimates, the model greatly underestimates intake nitrogen. It appears that the model needs to be combined with actual animal body weights and herbage N content, and viable DMI estimates for it to produce realistic outputs. With modification, the model could be a valuable tool in evaluating nitrogen excretion and its use efficiency within a pastoral system.
Technical Abstract: In 2005, a Blood Urea Nitrogen (BUN) model was developed that utilizes animal BUN to predict nitrogen excretion and the efficiency of its utilization in sheep. However, this model has not been evaluated, perhaps due to limited availability of measured data. Our goal was to evaluate the BUN model efficacy using experimentally derived BUN, herbage N, pasture dry matter intake (DMI) estimates, and lamb productivity data from experiments carried out in the Appalachian mountain region of the eastern USA. Based on the model’s estimated lamb N intake, model DMI values were calculated utilizing known herbage N contents obtained from paddock samples clipped prior to grazing events where lamb BUN was determined. The model’s DMI estimates were lower (P<0.01) than experimentally derived estimates, and were unrealistic when related to actual animal performance. The model predicted lower (P<0.0001) intake N and fecal N, and predicted greater (P<0.0001) N use efficiency than experimentally derived estimates. It appears that the model needs to be combined with actual BWs and herbage N content estimates, and viable DMI estimates to generate realistic outputs. Within these criterion, the model could be a valuable tool to help evaluate N excretion and N use efficiency within a pastoral system.