IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v168y2019icp36-47.html
   My bibliography  Save this article

Nitrogen and phosphorus excretion on mountain farms of different dairy systems

Author

Listed:
  • Schiavon, Stefano
  • Sturaro, Enrico
  • Tagliapietra, Franco
  • Ramanzin, Maurizio
  • Bittante, Giovanni

Abstract

We developed a procedure to estimate the release of nutrients into the environment on Alpine dairy farms and applied it to a sample of 564 farms in the Province of Trento (north-eastern Italy) as a case study. Farm data (geographical location, herd size, milk production and quality, reproductive events, land use) were gathered from institutional databases and merged. Information on the formulation of the ration was obtained from farm visits. The farms fell into 4 groups: traditional with summer transhumance to highland pastures (T-ALP, 51%), traditional without transhumance (T-noALP, 24%), traditional using silage (T-S, 5%), and modern (MOD, 20%). The model predicted N and P excretion from cows and heifers on a farm basis. The N in manure was computed from total N excreted, assuming a 28% of N loss due to volatilisation. A cow unit was defined as the cow and its share of replacement heifer. The average dietary N content of the lactating cows ranged from 20 to 30 g/kg DM, while on-farm N excretion ranged from 90 to 190 kg/year per cow unit; the modern farms had the highest average value (137 kg), the T-ALP farms the lowest (106 kg). Average P excretion ranged from 10 to 40 kg/year/cow unit. The on-farm N and P in manure per unit of milk decreased asymptotically with increasing cow productivity, from 25 to 19 and from 4.1 to 2.8 g/kg milk, respectively. The modern farms had the greatest amounts of N and P in manure per unit of agricultural land (260 and 51 kg/ha, respectively), the T-ALP farms the lowest (161 and 37 kg/ha, respectively). Within system, there was a huge variation among farms in the N and P load per unit of agricultural land, which was largely explained by the number of cow units per ha and by nutrient excretion per cow unit, but not by herd size or cow productivity. Within dairy system, the N and P contents of the rations for lactating cows were weakly related to the daily milk yield, but strongly related to the annual excretion of the nutrient per cow unit. The farm N loads were below the legal thresholds (340 kg N/ha per year), but the geographical distribution of the loads indicated two critical areas due to farm density.

Suggested Citation

  • Schiavon, Stefano & Sturaro, Enrico & Tagliapietra, Franco & Ramanzin, Maurizio & Bittante, Giovanni, 2019. "Nitrogen and phosphorus excretion on mountain farms of different dairy systems," Agricultural Systems, Elsevier, vol. 168(C), pages 36-47.
    • Handle: RePEc:eee:agisys:v:168:y:2019:i:c:p:36-47
    DOI: 10.1016/j.agsy.2018.10.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308521X18301604
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agsy.2018.10.006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Carof, Matthieu & Godinot, Olivier, 2018. "A free online tool to calculate three nitrogen-related indicators for farming systems," Agricultural Systems, Elsevier, vol. 162(C), pages 28-33.
    2. Mack, Gabriele & Huber, Robert, 2017. "On-farm compliance costs and N surplus reduction of mixed dairy farms under grassland-based feeding systems," Agricultural Systems, Elsevier, vol. 154(C), pages 34-44.
    3. Mu, W. & Groen, E.A. & van Middelaar, C.E. & Bokkers, E.A.M. & Hennart, S. & Stilmant, D. & de Boer, I.J.M., 2017. "Benchmarking nutrient use efficiency of dairy farms: The effect of epistemic uncertainty," Agricultural Systems, Elsevier, vol. 156(C), pages 25-33.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Berton, M. & Bittante, G. & Zendri, F. & Ramanzin, M. & Schiavon, S. & Sturaro, E., 2020. "Environmental impact and efficiency of use of resources of different mountain dairy farming systems," Agricultural Systems, Elsevier, vol. 181(C).

    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. Pirjo Peltonen-Sainio & Lauri Jauhiainen, 2019. "Risk of Low Productivity is Dependent on Farm Characteristics: How to Turn Poor Performance into an Advantage," Sustainability, MDPI, vol. 11(19), pages 1-17, October.
    2. Miller, Christine M.F. & Waterhouse, Hannah & Harter, Thomas & Fadel, James G. & Meyer, Deanne, 2020. "Quantifying the uncertainty in nitrogen application and groundwater nitrate leaching in manure based cropping systems," Agricultural Systems, Elsevier, vol. 184(C).
    3. Mack, Gabriele & Ritzel, Christian & Jan, Pierrick, 2020. "Determinants for the Implementation of Action-, Result- and Multi-Actor-Oriented Agri-Environment Schemes in Switzerland," Ecological Economics, Elsevier, vol. 176(C).
    4. Tang, Kai, 2024. "Agricultural adaptation to the environmental and social consequences of climate change in mixed farming systems: Evidence from North Xinjiang, China," Agricultural Systems, Elsevier, vol. 217(C).
    5. Mack, G. & Finger, R. & Ammann, J. & El Benni, N., 2023. "Modelling policies towards pesticide-free agricultural production systems," Agricultural Systems, Elsevier, vol. 207(C).
    6. Kuhn, Till & Schäfer, David & Holm-Müller, Karin & Britz, Wolfgang, 2019. "On-farm compliance costs with the EU-Nitrates Directive: A modelling approach for specialized livestock production in northwest Germany," Agricultural Systems, Elsevier, vol. 173(C), pages 233-243.
    7. Till Kuhn, David Schäfer, 2018. "A farm typology for North Rhine-Westphalia to assess agri-environmental policies," Discussion Papers 279702, University of Bonn, Institute for Food and Resource Economics.
    8. Robert Huber & Robert Finger, 2020. "A Meta‐analysis of the Willingness to Pay for Cultural Services from Grasslands in Europe," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(2), pages 357-383, June.
    9. Adenuga, Adewale Henry & Davis, John & Hutchinson, George & Patton, Myles & Donnellan, Trevor, 2020. "Analysis of the effect of alternative agri-environmental policy instruments on production performance and nitrogen surplus of representative dairy farms," Agricultural Systems, Elsevier, vol. 184(C).
    10. Kuhn, T. & Enders, A. & Gaiser, T. & Schäfer, D. & Srivastava, A.K. & Britz, W., 2020. "Coupling crop and bio-economic farm modelling to evaluate the revised fertilization regulations in Germany," Agricultural Systems, Elsevier, vol. 177(C).
    11. Schaefer, David & Britz, Wolfgang & Kuhn, Till, 2020. "Modelling policy induced manure transports at large scale using an agent-based simulation model," Discussion Papers 305270, University of Bonn, Institute for Food and Resource Economics.
    12. Devotha G. Nyambo & Thomas Clemen, 2023. "Differential Assessment of Strategies to Increase Milk Yield in Small-Scale Dairy Farming Systems Using Multi-Agent Modelling and Simulation," Agriculture, MDPI, vol. 13(3), pages 1-13, February.
    13. Galloway, Craig & Conradie, Beatrice & Prozesky, Heidi & Esler, Karen, 2018. "Opportunities to improve sustainability on commercial pasture-based dairy farms by assessing environmental impact," Agricultural Systems, Elsevier, vol. 166(C), pages 1-9.

    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:eee:agisys:v:168:y:2019:i:c:p:36-47. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agsy .

    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.