IDEAS home Printed from https://ideas.repec.org/a/ags/agreko/9492.html
   My bibliography  Save this article

Estimates of the increase in milk production due to the introduction of maize silage to a dairy farm in KwaZulu-Natal: A time series approach

Author

Listed:
  • Mkhabela, Thulasizwe S.

Abstract

A method involving time series modelling is provided for evaluating the effects of an abrupt intervention, such as the adoption of a new technology, when no control is available for comparative evaluation. The new technology was the introduction of maize silage into the feeding programme of a dairy farm in the midlands of KwaZulu-Natal. A model was developed using historical milk data from a nine-year period. The model was used to forecast subsequent milk production on the dairy farm had maize silage not been introduced, and these forecasts were compared with actual production after the introduction of maize silage. Milk production was more than 320,000 litres greater than forecast in ten seasons over a four-year period after the introduction of silage. During the same period, production was more than 14,000 litres less than forecast in one season, with the remaining six seasons estimated to be within 5% of observed values. This resulted in an estimated net gain of 305,668 litres of milk above the amount expected had silage not been introduced, representing an average increase in production of 18% per annum.

Suggested Citation

  • Mkhabela, Thulasizwe S., 2004. "Estimates of the increase in milk production due to the introduction of maize silage to a dairy farm in KwaZulu-Natal: A time series approach," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 43(4), pages 1-8, December.
    • Handle: RePEc:ags:agreko:9492
    DOI: 10.22004/ag.econ.9492
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/9492/files/43040484.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.9492?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. Matis, J. H. & Saito, T. & Grant, W. E. & Iwig, W. C. & Ritchie, J. T., 1985. "A Markov chain approach to crop yield forecasting," Agricultural Systems, Elsevier, vol. 18(3), pages 171-187.
    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. Camilo Olaya, 2015. "Cows, agency, and the significance of operational thinking," System Dynamics Review, System Dynamics Society, vol. 31(4), pages 183-219, October.

    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. Mikkel Bojesen & Hans Skov-Petersen & Morten Gylling, 2013. "Forecasting the potential of Danish biogas production: spatial representation of Markov chains," IFRO Working Paper 2013/16, University of Copenhagen, Department of Food and Resource Economics.
    2. Peace Bamurigire & Anthony Vodacek & Andras Valko & Said Rutabayiro Ngoga, 2020. "Simulation of Internet of Things Water Management for Efficient Rice Irrigation in Rwanda," Agriculture, MDPI, vol. 10(10), pages 1-12, September.
    3. AL-Hiyali, A.D.K & Blaw, Hayder Hameed & Madlul, Najlaa Salah, 2024. "Predicting the Value of Agricultural GDP in Iraq for the Period 2019—2030 by Applying the Markov Transition Matrix," Research on World Agricultural Economy, Nan Yang Academy of Sciences Pte Ltd (NASS), vol. 5(1), March.
    4. J. R. Stokes, 2024. "A Markov chain model of crop conditions and intrayear crop yield forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 583-592, April.
    5. GwanSeon Kim & Mehdi Nemati & Steven Buck & Nicholas Pates & Tyler Mark, 2020. "Recovering Forecast Distributions of Crop Composition: Method and Application to Kentucky Agriculture," Sustainability, MDPI, vol. 12(7), 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:agreko:9492. 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/aeasaea.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.