IDEAS home Printed from https://ideas.repec.org/p/ags/eaae11/114444.html
   My bibliography  Save this paper

Farm Level Economic Implications of Genetic Selection for Improving Milk Fat Composition

Author

Listed:
  • Demeter, Robert Milan
  • Bovenhuis, Henk
  • Kristensen, Anders Ringgaard
  • Oude Lansink, Alfons G.J.M.
  • Meuwissen, Miranda P.M.
  • van Arendonk, Johan A.M.

Abstract

The objective of the study was to assess the farm level economic implications of value-adding genetic selection strategies to improve milk fat composition. Selection based on a quantitative trait (ratio of total saturated to total unsaturated fatty acids in milk) or a known genotype (for the DGAT1 gene) was considered. Technical and economic performance of hypothetical herds were computed by a herd optimization and simulation model. It was assumed that the herds are already bred for the specific milk composition, and the transition period was not considered. Correlated effects of the selection scenarios on milk production, female fertility, and functional longevity traits were accounted for. Results showed that increasing the total unsaturated fatty acids in milk by traditional selection leads to lower net revenue, whereas selection based on DGAT1 genotype results in slightly higher net revenue. Our results, therefore, suggest that genetic selection based on DGAT1 genotype is a more profitable strategy for dairy farmers than selection based on phenotypes for SFA/UFA ratio.

Suggested Citation

  • Demeter, Robert Milan & Bovenhuis, Henk & Kristensen, Anders Ringgaard & Oude Lansink, Alfons G.J.M. & Meuwissen, Miranda P.M. & van Arendonk, Johan A.M., 2011. "Farm Level Economic Implications of Genetic Selection for Improving Milk Fat Composition," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114444, European Association of Agricultural Economists.
  • Handle: RePEc:ags:eaae11:114444
    DOI: 10.22004/ag.econ.114444
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/114444/files/Demeter_Robert_530.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.114444?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
    ---><---

    References listed on IDEAS

    as
    1. Anders Kristensen & Erik Jørgensen, 2000. "Multi‐level hierarchic Markov processes as a framework for herd management support," Annals of Operations Research, Springer, vol. 94(1), pages 69-89, January.
    2. Dooley, A.E. & Parker, W.J. & Blair, H.T. & Hurley, E.M., 2005. "Implications of on-farm segregation for valuable milk characteristics," Agricultural Systems, Elsevier, vol. 85(1), pages 82-97, July.
    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. Lars Relund Nielsen & Erik Jørgensen & Søren Højsgaard, 2011. "Embedding a state space model into a Markov decision process," Annals of Operations Research, Springer, vol. 190(1), pages 289-309, October.
    2. Lan Ge & Anders Kristensen & Monique Mourits & Ruud Huirne, 2014. "A new decision support framework for managing foot-and-mouth disease epidemics," Annals of Operations Research, Springer, vol. 219(1), pages 49-62, August.
    3. Nielsen, Lars Relund & Kristensen, Anders Ringgaard, 2006. "Finding the K best policies in a finite-horizon Markov decision process," European Journal of Operational Research, Elsevier, vol. 175(2), pages 1164-1179, December.
    4. Reza Pourmoayed & Lars Relund Nielsen, 2022. "Optimizing pig marketing decisions under price fluctuations," Annals of Operations Research, Springer, vol. 314(2), pages 617-644, July.
    5. Erik Jørgensen & Anders Kristensen & Dennis Nilsson, 2014. "Markov Limid processes for representing and solving renewal problems," Annals of Operations Research, Springer, vol. 219(1), pages 63-84, August.
    6. Hegrenes, Agnar & Kristensen, Anders Ringgaard & Lien, Gudbrand D., 2003. "Optimal Economic Length Of Leys: A Dynamic Programming Approach," 2003 Annual Meeting, August 16-22, 2003, Durban, South Africa 25848, International Association of Agricultural Economists.
    7. Toft, Nils & Kristensen, Anders R. & Jorgensen, Erik, 2005. "A framework for decision support related to infectious diseases in slaughter pig fattening units," Agricultural Systems, Elsevier, vol. 85(2), pages 120-137, August.
    8. Pourmoayed, Reza & Nielsen, Lars Relund & Kristensen, Anders Ringgaard, 2016. "A hierarchical Markov decision process modeling feeding and marketing decisions of growing pigs," European Journal of Operational Research, Elsevier, vol. 250(3), pages 925-938.
    9. Kazim Topuz & Hasmet Uner & Asil Oztekin & Mehmet Bayram Yildirim, 2018. "Predicting pediatric clinic no-shows: a decision analytic framework using elastic net and Bayesian belief network," Annals of Operations Research, Springer, vol. 263(1), pages 479-499, April.

    More about this item

    Keywords

    Livestock Production/Industries;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:ags:eaae11:114444. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/eaaeeea.html .

    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.