IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i12p7260-d838170.html
   My bibliography  Save this article

The Impact of Using Novel Equations to Predict Nitrogen Excretion and Associated Emissions from Pasture-Based Beef Production Systems

Author

Listed:
  • Angelos E. Angelidis

    (Department of Animal Sciences, School of Agriculture, Policy and Development, University of Reading, P.O. Box 237, Earley Gate, Reading, Berkshire RG6 6EU, UK)

  • Graham A. McAuliffe

    (Sustainable Agriculture Sciences, Rothamsted Research, North Wyke, Okehampton, Devon EX20 2SB, UK)

  • Taro Takahashi

    (Sustainable Agriculture Sciences, Rothamsted Research, North Wyke, Okehampton, Devon EX20 2SB, UK
    Bristol Veterinary School, University of Bristol, Langford, Somerset BS40 5DU, UK)

  • Les Crompton

    (Department of Animal Sciences, School of Agriculture, Policy and Development, University of Reading, P.O. Box 237, Earley Gate, Reading, Berkshire RG6 6EU, UK)

  • Tianhai Yan

    (Sustainable Agri-Food Sciences Division, Agriculture Branch, Agri-Food and Biosciences Institute, Large Park, Hillsborough, County Down BT26 6DR, UK)

  • Christopher K. Reynolds

    (Department of Animal Sciences, School of Agriculture, Policy and Development, University of Reading, P.O. Box 237, Earley Gate, Reading, Berkshire RG6 6EU, UK)

  • Sokratis Stergiadis

    (Department of Animal Sciences, School of Agriculture, Policy and Development, University of Reading, P.O. Box 237, Earley Gate, Reading, Berkshire RG6 6EU, UK)

  • Tom Misselbrook

    (Sustainable Agriculture Sciences, Rothamsted Research, North Wyke, Okehampton, Devon EX20 2SB, UK)

Abstract

The excretion of nitrogen (N) in faeces and urine from beef cattle contributes to atmospheric pollution through greenhouse gas and ammonia emissions and eutrophication of land and aquatic habitats through excessive N deposition and nitrate leaching to groundwater. As N excretion by beef cattle is rarely measured directly, it is important to accurately predict losses by utilising a combined knowledge of diet and production parameters so that the effect of dietary changes on the potential environmental impact of beef production systems can be estimated. This study aimed to identify differences between IPCC and more detailed country-specific models in the prediction of N excretion and N losses at a system level and determine how the choice of model influences the interpretation of differences in diet at the system scale. The data used in this study were derived from a farm-scale experimental system consisting of three individual grazing farms, each with a different sward type: a permanent pasture, a high sugar ryegrass monoculture, and a high sugar ryegrass with white clover (~30% groundcover). Data were analysed using a mixed linear model (residual maximum likelihood analysis). The IPCC methods demonstrated significantly lower estimates of N excretion than country-specific models for the first housing period and significantly greater losses for the grazing and second housing periods. The country-specific models enabled prediction of N partitioning to urine and faeces, which is important for estimation of subsequent N losses through the production system, although the models differed in their estimates. Overall, predicted N losses were greater using the IPCC approaches compared to using more detailed country-specific approaches. The outcomes of the present study have highlighted that different models can have a substantial impact on the predicted N outputs and subsequent losses to the environment for pasture-based beef finishing systems, and the importance, therefore, of using appropriate models and parameters.

Suggested Citation

  • Angelos E. Angelidis & Graham A. McAuliffe & Taro Takahashi & Les Crompton & Tianhai Yan & Christopher K. Reynolds & Sokratis Stergiadis & Tom Misselbrook, 2022. "The Impact of Using Novel Equations to Predict Nitrogen Excretion and Associated Emissions from Pasture-Based Beef Production Systems," Sustainability, MDPI, vol. 14(12), pages 1-12, June.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:12:p:7260-:d:838170
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/12/7260/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/12/7260/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mark C. Eisler & Michael R. F. Lee & John F. Tarlton & Graeme B. Martin & John Beddington & Jennifer A. J. Dungait & Henry Greathead & Jianxin Liu & Stephen Mathew & Helen Miller & Tom Misselbrook & P, 2014. "Agriculture: Steps to sustainable livestock," Nature, Nature, vol. 507(7490), pages 32-34, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Miriam Baumgartner & Sandra Kuhnke & Kurt-Jürgen Hülsbergen & Michael H. Erhard & Margit H. Zeitler-Feicht, 2021. "Improving Horse Welfare and Environmental Sustainability in Horse Husbandry: Linkage between Turnout and Nitrogen Surplus," Sustainability, MDPI, vol. 13(16), pages 1-16, August.
    2. Tichenor, Nicole E. & van Zanten, Hannah H.E. & de Boer, Imke J.M. & Peters, Christian J. & McCarthy, Ashley C. & Griffin, Timothy S., 2017. "Land use efficiency of beef systems in the Northeastern USA from a food supply perspective," Agricultural Systems, Elsevier, vol. 156(C), pages 34-42.
    3. Wu, L. & Harris, P. & Misselbrook, T.H. & Lee, M.R.F., 2022. "Simulating grazing beef and sheep systems," Agricultural Systems, Elsevier, vol. 195(C).
    4. Stutz, Adrian & Schell, Sabrina & Hack, Andreas, 2022. "In family firms we trust – Experimental evidence on the credibility of sustainability reporting: A replication study with extension," Journal of Family Business Strategy, Elsevier, vol. 13(4).
    5. Chengji Han & Guogang Wang & Hongbo Yang, 2022. "Study on the Coupling System of Grain-Grass-Livestock of Herbivorous Animal Husbandry in Agricultural Areas: A Case Study of Najitun Farm of Hulunbuir Agricultural Reclamation in China," Land, MDPI, vol. 11(5), pages 1-26, May.
    6. Mollie Chapman & Susanna Klassen & Maayan Kreitzman & Adrian Semmelink & Kelly Sharp & Gerald Singh & Kai M. A. Chan, 2017. "5 Key Challenges and Solutions for Governing Complex Adaptive (Food) Systems," Sustainability, MDPI, vol. 9(9), pages 1-30, September.
    7. Germer, Leah A. & van Middelaar, Corina E. & Oosting, Simon J. & Gerber, Pierre J., 2023. "When and where are livestock climate-smart? A spatial-temporal framework for comparing the climate change and food security synergies and tradeoffs of Sub-Saharan African livestock systems," Agricultural Systems, Elsevier, vol. 210(C).
    8. Massimo Canali & Pegah Amani & Lusine Aramyan & Manuela Gheoldus & Graham Moates & Karin Östergren & Kirsi Silvennoinen & Keith Waldron & Matteo Vittuari, 2016. "Food Waste Drivers in Europe, from Identification to Possible Interventions," Sustainability, MDPI, vol. 9(1), pages 1-33, December.
    9. Richard Twine, 2021. "Emissions from Animal Agriculture—16.5% Is the New Minimum Figure," Sustainability, MDPI, vol. 13(11), pages 1-8, June.
    10. Martin C. Parlasca & Matin Qaim, 2022. "Meat Consumption and Sustainability," Annual Review of Resource Economics, Annual Reviews, vol. 14(1), pages 17-41, October.
    11. zu Ermgassen, Erasmus K.H.J. & Phalan, Ben & Green, Rhys E. & Balmford, Andrew, 2016. "Reducing the land use of EU pork production: where there’s swill, there’s a way," Food Policy, Elsevier, vol. 58(C), pages 35-48.
    12. Mishra, Pulak & Das, Pinaki & Ghosh, Soumya Kanti & Dandapat, Akash & Dasgupta, Soumita, 2024. "Agriculture-livestock-forestry nexus and household income diversification: Experiences from selected villages of West Bengal, India," Agricultural Systems, Elsevier, vol. 217(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:12:p:7260-:d:838170. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.