Predicting and optimising nitrogen use in beef systemsAngelidis, A. E. (2022) Predicting and optimising nitrogen use in beef systems. PhD thesis, University of Reading
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.48683/1926.00117337 Abstract/SummaryDietary protein fed to beef cattle, which retain less than two-thirds of their nitrogen (N) intake, is beyond requirements, thus posing economic and environmental sustainability burdens to beef farms worldwide. N excretion in urine and faeces contributes to greenhouse gas emissions, through subsequent manure management and soil N losses as nitrous oxide (N2O), to air quality pollution and terrestrial and aquatic acidification and eutrophication through volatilization of ammonia (NH3) as well as aquatic eutrophication through nitrate leaching. Beef producers must comply with guidelines on N fertiliser, manure management and reduction of dietary protein in beef cattle. However, this reduction may risk grassland and animal productivity, and deteriorate economic performance of beef farms. Therefore, (i) investigation of the animal and diet factors that improve N use efficiency (NUE) in beef cattle in a context broader than individual studies, and (ii) the accurate prediction of manure N output, and subsequent N2O and NH3 emissions, by revising current prediction models, are critical. The first chapter of this thesis, reviews important aspects of ruminant nutrition, N environmental impact and models for the prediction of N outputs. The regression models for NUE produced in Chapter 2, using a database from 69 published studies, show that more digestible diets with less N and fibre and adequate metabolisable energy (ME), to ensure optimal productivity and health, may reduce N excretion. By using the data of 570 individual animals split into three sub-sets based on dietary protein, Chapter 3 presents regression models which show that dietary protein is essential for accurate predictions, while dietary starch, fat, and ME can be used to further improve model accuracy. Using a similar database to Chapter 2 and redundancy analysis, Chapter 4 highlights that feedstuffs providing adequate digestible fibre, as well as reduction of protein oversupply, can improve NUE and shift N outputs from urine to faeces. In Chapter 5, where available models for the prediction of N excretion and losses at a system level are compared, the predicted N losses appear greater using the IPCC compared to more detailed approaches with country-specific parameters in pasture-based beef finishing systems. Results presented in this thesis aim to guide the sustainable reduction in dietary N inputs, and provide novel tools for producers, feed industry, researchers, regulating bodies and the public.
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