IDEAS home Printed from https://ideas.repec.org/a/ags/afbmau/333927.html
   My bibliography  Save this article

Estimated Annual Value of a Forage Cultivar Selection Decision Tool for New Zealand Sheep and Beef Farmers

Author

Listed:
  • Ludemann, Cameron

Abstract

In 2011, the New Zealand dairy industry developed a forage cultivar selection decision support tool called the DairyNZ Forage Value Index (FVI). Since then, there has been considerable interest shown in development of a FVI-type cultivar evaluation system for the New Zealand sheep and beef industry. The New Zealand Pastoral Industry Forage Strategy for example recommended actions to develop a FVI for the sheep and beef industry and to have closer collaboration between the sheep and beef industry, the dairy industry and the New Zealand Plant Breeding and Research Association. This is unsurprising since the dairy industry estimated the value of the benefits of the DairyNZ FVI as approximately $NZ160 million each year. The present study provides a cost benefit analysis of a forage cultivar selection decision support tool (DST) across the New Zealand sheep and beef industry. The analysis was performed using a nitrogen fertiliser/barley replacement cost method to estimate the value of forage dry matter. The value of sheep and beef farmers choosing 5 star rated cultivars of perennial ryegrass compared to 3 or 1 star rated cultivars was extrapolated to the eight Beef + Lamb NZ Farm Classes and to the whole sheep and beef industry. Multiple scenarios were examined to assess the net present value and modified internal rate of return of investment in the DST. These scenarios reflected differences in assumed rates of adoption over a 10-year period and differences in implementation costs. The modified internal rate of return over a 10-year period was estimated to range between 27 and 62 per cent depending on whether an annual cost of the DST was assumed to be $NZ0.5 million or $NZ1 million under the adoption scenarios considered. The NPV ranged between $NZ6 million and $NZ45 million. This highlights the potential value of improved farmer selection of ryegrass cultivars through a cultivar selection DST in a sheep and beef context in New Zealand.

Suggested Citation

  • Ludemann, Cameron, 2022. "Estimated Annual Value of a Forage Cultivar Selection Decision Tool for New Zealand Sheep and Beef Farmers," AFBM Journal, Australasian Farm Business Management Network, vol. 19(1), April.
    • Handle: RePEc:ags:afbmau:333927
    DOI: 10.22004/ag.econ.333927
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/333927/files/AFBMJ-Vol-19-Paper-1-Ludemann.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.333927?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. Lowell S. Hardin & Glenn L. Johnson, 1955. "Economics of Forage Evaluation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 37(5), pages 1457-1459.
    2. Montes de Oca Munguia, Oscar & Pannell, David J. & Llewellyn, Rick & Stahlmann-Brown, Philip, 2021. "Adoption pathway analysis: Representing the dynamics and diversity of adoption for agricultural practices," Agricultural Systems, Elsevier, vol. 191(C).
    3. Ludemann, C.I. & Cullen, B.R. & Malcolm, Bill & Smith, K.F., 2013. "Economic values of changes in energy concentration of pasture in contrasting temperate dairy regions in Australia," AFBM Journal, Australasian Farm Business Management Network, vol. 10, pages 1-15.
    4. Terrance M. Hurley & Xudong Rao & Philip G. Pardey, 2014. "Re-examining the Reported Rates of Return to Food and Agricultural Research and Development," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(5), pages 1492-1504.
    5. Kuehne, Geoff & Llewellyn, Rick & Pannell, David J. & Wilkinson, Roger & Dolling, Perry & Ouzman, Jackie & Ewing, Mike, 2017. "Predicting farmer uptake of new agricultural practices: A tool for research, extension and policy," Agricultural Systems, Elsevier, vol. 156(C), pages 115-125.
    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. Lewis, Claire D. & Smith, Kevin F. & Jacobs, Joe L. & Ho, Christie K.M. & Leddin, Clare M. & Malcolm, Bill, 2020. "Using a two-price market value method to value extra pasture DM in different seasons," Agricultural Systems, Elsevier, vol. 178(C).
    2. Brown, Brendan & Paudel, Gokul P. & Krupnik, Timothy J., 2021. "Visualising adoption processes through a stepwise framework: A case study of mechanisation on the Nepal Terai," Agricultural Systems, Elsevier, vol. 192(C).
    3. Ursula Ploll & Miguel Arato & Jan Börner & Monika Hartmann, 2022. "Sustainable Innovations: A Qualitative Study on Farmers’ Perceptions Driving the Diffusion of Beneficial Soil Microbes in Germany and the UK," Sustainability, MDPI, vol. 14(10), pages 1-23, May.
    4. Ludemann, C.I. & Cullen, B.R. & Malcolm, Bill & Smith, K.F., 2013. "Economic values of changes in energy concentration of pasture in contrasting temperate dairy regions in Australia," AFBM Journal, Australasian Farm Business Management Network, vol. 10, pages 1-15.
    5. Maleki, Tahereh & Koohestani, Hossein & Keshavarz, Marzieh, 2022. "Can climate-smart agriculture mitigate the Urmia Lake tragedy in its eastern basin?," Agricultural Water Management, Elsevier, vol. 260(C).
    6. Thompson, Wyatt & Dewbre, Joe & Pieralli, Simone & Schroeder, Kateryna & Pérez Domínguez, Ignacio & Westhoff, Patrick, 2019. "Long-term crop productivity response and its interaction with cereal markets and energy prices," Food Policy, Elsevier, vol. 84(C), pages 1-9.
    7. Lachaud, Michée A. & Bravo-Ureta, Boris E., 2022. "A Bayesian statistical analysis of return to agricultural R&D investment in Latin America: Implications for food security," Technology in Society, Elsevier, vol. 70(C).
    8. Rick S. Llewellyn & Brendan Brown, 2020. "Predicting Adoption of Innovations by Farmers: What is Different in Smallholder Agriculture?," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 42(1), pages 100-112, March.
    9. Hurley, Terrance M. & Pardey, Philip G. & Rao, Xudong, 2013. "Returns to Food and Agricultural R&D Investments Worldwide, 1958-2011," Briefs 159649, University of Minnesota, International Science and Technology Practice and Policy.
    10. Martha Swamila & Damas Philip & Adam Meshack Akyoo & Stefan Sieber & Mateete Bekunda & Anthony Anderson Kimaro, 2020. "Gliricidia Agroforestry Technology Adoption Potential in Selected Dryland Areas of Dodoma Region, Tanzania," Agriculture, MDPI, vol. 10(7), pages 1-17, July.
    11. Mullen, John & de Myer, Julien & Griffith, Garry & Lemerle, Caroline & Malcolm, Bill, 2023. "On Reconciling the Multiple Objectives of Agricultural RD&E," Australasian Agribusiness Review, University of Melbourne, Department of Agriculture and Food Systems, vol. 31(3), May.
    12. Terrance M. Hurley & Xudong Rao & Philip G. Pardey, 2017. "Re-Examining the Reported Rates of Return to Food and Agricultural Research and Development: Reply," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(3), pages 827-836.
    13. Toritseju Begho, 2021. "Using Farmers’ Risk Tolerance to Explain Variations in Adoption of Improved Rice Varieties in Nepal," Journal of South Asian Development, , vol. 16(2), pages 171-193, August.
    14. Nicholas Rada & David Schimmelpfennig, 2018. "Evaluating research and education performance in Indian agricultural development," Agricultural Economics, International Association of Agricultural Economists, vol. 49(3), pages 395-406, May.
    15. Joel Buyinza & Ian K. Nuberg & Catherine W. Muthuri & Matthew D. Denton, 2022. "Why Farmers Are Hesitant to Adopt What Appears Good on the Basis of Science: Understanding Farmers’ Perceptions of Biophysical Research," Journal of Sustainable Development, Canadian Center of Science and Education, vol. 15(3), pages 1-68, May.
    16. Elizabeth Ahikiriza & Joshua Wesana & Xavier Gellynck & Guido Van Huylenbroeck & Ludwig Lauwers, 2021. "Context Specificity and Time Dependency in Classifying Sub-Saharan Africa Dairy Cattle Farmers for Targeted Extension Farm Advice: The Case of Uganda," Agriculture, MDPI, vol. 11(9), pages 1-19, August.
    17. Stéphane Lemarié & Valérie Orozco & Jean-Pierre Butault & Antonio Musolesi & Michel Simioni & Bertrand Schmitt, 2020. "Assessing the long-term impact of agricultural research on productivity: evidence from France," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 47(4), pages 1559-1586.
    18. Richard Pomfret & Kym Anderson, 2014. "Globalisation and Agricultural Trade," Australian Economic History Review, Economic History Society of Australia and New Zealand, vol. 54(3), pages 285-306, November.
    19. Abubakar Shehu Umar, Norsida Man & Jasmin Arif Shah, Nitty Hirawaty Kamarulzaman, 2024. "Influences of Policies and Language of Communication on Achievement Level of Extension Services among Crop Farmers in North-eastern Nigeria," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(1), pages 1384-1397, January.
    20. Zhihua Xiao & Murray Fulton, 2018. "Underinvestment in Producer†Funded Agricultural R&D: The Role of the Horizon Problem," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 66(1), pages 55-86, March.

    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:afbmau:333927. 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/afbmnea.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.