IDEAS home Printed from https://ideas.repec.org/a/ags/jlaare/8641.html
   My bibliography  Save this article

Economic Value of Selecting and Marketing Cattle by Leptin Genotype

Author

Listed:
  • Lusk, Jayson L.

Abstract

Recent research has identified genetic diversity in the ability of animals to manufacture and recognize leptin, a protein that regulated appetite and weight. This paper determines the economic value of using information on leptin genotype to select and manage beef cattle. Results reveal that the economic value of using genotypic information to sort cattle by optimal endpoint is only about $2/head for steers and $1/head for heifers; however, the value of using genotypic information to optimally select and feed only certain genotypes is $23/head for steers and $28/head for heifers. The difference in per head profit between the best and worst performing genotype is over $28 on the date the cattle were actually marketed and increases to $60 if each genotype is optimally marketed.

Suggested Citation

  • Lusk, Jayson L., 2007. "Economic Value of Selecting and Marketing Cattle by Leptin Genotype," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 32(2), pages 1-24, August.
    • Handle: RePEc:ags:jlaare:8641
    DOI: 10.22004/ag.econ.8641
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/8641/files/32020306.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.8641?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
    ---><---

    Citations

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


    Cited by:

    1. Scott W. Fausti & Zhiguang Wang & Bashir A. Qasmi & Matthew A. Diersen, 2014. "Risk and marketing behavior: pricing fed cattle on a grid," Agricultural Economics, International Association of Agricultural Economists, vol. 45(5), pages 601-612, September.
    2. Fausti, Scott W. & Diersen, Matthew A. & Qasmi, Bashir A. & Li, Jing, 2010. "Value-Based Marketing: A Dsicussion of Issues and Trends in the Slaughter Cattle Market," Journal of Agribusiness, Agricultural Economics Association of Georgia, vol. 27(1-2), pages 1-22.
    3. Thompson, Nathanael M. & DeVuyst, Eric A. & Brorsen, B. Wade & Lusk, Jayson L., 2016. "Using Genetic Testing to Improve Fed Cattle Marketing Decisions," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 41(2), May.
    4. Thompson, Nathanael M. & Brorsen, B. Wade & DeVuyst, Eric A. & Lusk, Jayson L., 2016. "Random Sampling of Beef Cattle for Genetic Testing: Optimal Sample Size Determination," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 229195, Southern Agricultural Economics Association.
    5. Lambert, David K., 2008. "The expected utility of genetic information in beef cattle production," Agricultural Systems, Elsevier, vol. 99(1), pages 44-52, December.
    6. Maples, Joshua G. & Lusk, Jayson L. & Peel, Derrell S., 2019. "Technology and evolving supply chains in the beef and pork industries," Food Policy, Elsevier, vol. 83(C), pages 346-354.
    7. Parcell, Joseph L. & Franken, Jason R.V. & Schafer, Daniel & Patterson, David J. & John, Mike & Kerley, Monty S. & Haden, Kent, 2011. "Coordinating Sire Genetics in a Synchronized AI Program," Journal of the ASFMRA, American Society of Farm Managers and Rural Appraisers, vol. 2011, pages 1-12, June.
    8. Belasco, Eric J., 2008. "The Role of Price Risk Management in Mitigating Fed Cattle Profit Exposure," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 33(3), pages 1-17.
    9. Jay Mitchell & Eric A. DeVuyst & Marc L. Bauer & Daniel L. Larson, 2009. "Cow‐calf profitability and leptin genotyping," Agricultural Economics, International Association of Agricultural Economists, vol. 40(1), pages 113-118, January.
    10. Parcell, Joseph L. & Schaefer, Daniel & Patterson, David J. & John, Mike & Kerley, Monty S. & Haden, Kent, 2008. "Assessing the Value of Coordinated Sire Genetics in a Synchronized AI Program," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37618, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    11. Thompson, Nathanael M. & DeVuyst, Eric A. & Brorsen, B. Wade & Lusk, Jayson L., 2014. "Value of Genetic Information for Management and Selection of Feedlot Cattle," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 39(1), pages 1-17, April.

    More about this item

    Keywords

    Livestock Production/Industries;

    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:jlaare:8641. 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.

    We have no bibliographic references for this item. You can help adding them by using 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/waeaaea.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.