IDEAS home Printed from https://ideas.repec.org/p/ags/aaea16/236018.html
   My bibliography  Save this paper

Evaluating economic threshold for dynamically optimal disease management

Author

Listed:
  • Liu, Yangxuan
  • Small, Ian
  • Langemeier, Michael
  • Gramig, Benjamin
  • Preckel, Paul
  • Joseph, Laura
  • Wu, Yuanhan
  • Fry, William

Abstract

Precision agriculture has emerged as a revolutionary technology in helping make farm decisions. It transforms farm related data into information, and then coverts information into useful knowledge for decision-making. This study evaluates economic thresholds for a new web-based decision support system developed for precision fungicide management for potato production. Using 10 years of computer simulation experiments from 152 locations in the United States, we compared different thresholds in terms of disease severity, fungicide usage efficiency, and net income over fungicide cost to manage potato late blight disease. The empirical results show that the economic thresholds improved disease suppression and farming profit relative to the previous critical thresholds while maintaining fungicide use efficiency.

Suggested Citation

  • Liu, Yangxuan & Small, Ian & Langemeier, Michael & Gramig, Benjamin & Preckel, Paul & Joseph, Laura & Wu, Yuanhan & Fry, William, 2016. "Evaluating economic threshold for dynamically optimal disease management," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236018, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea16:236018
    DOI: 10.22004/ag.econ.236018
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/236018/files/AAEA%20paper-%20Liu%20et%20al2.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.236018?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. Schimmelpfennig, David & Ebel, Robert, 2011. "On the Doorstep of the Information Age: Recent Adoption of Precision Agriculture," Economic Information Bulletin 291945, United States Department of Agriculture, Economic Research Service.
    2. Zhang, Wei & Swinton, Scott M., 2009. "Incorporating natural enemies in an economic threshold for dynamically optimal pest management," Ecological Modelling, Elsevier, vol. 220(9), pages 1315-1324.
    3. Liu, Yangxuan & Langemeier, Michael & Small, Ian & Joseph, Laura & Fry, William, 2015. "Risk management strategies using potato precision farming technology," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205417, Agricultural and Applied Economics Association.
    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. Liu, Yangxuan & Langemeier, Michael & Gramig, Benjamin & Preckel, Paul & Small, Ian & Joseph, Laura & Fry, William, 2016. "Economic Threshold for Dynamically Optimal Late Blight Management," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230080, Southern Agricultural Economics Association.
    2. de Oliveira, A.C.S. & Martins, S.G.F. & Zacarias, M.S., 2013. "An individual-based model for the interaction of the mite Tetranychus urticae (Koch, 1836) with its predator Neoseiulus californicus (McGregor, 1954) (Acari: Tetranychidae, Phytoseiidae)," Ecological Modelling, Elsevier, vol. 255(C), pages 11-20.
    3. Gonzalez, Darinka & Cabral, João Alexandre & Torres, Laura & Santos, Mário, 2015. "A cohort-based modelling approach for managing olive moth Prays oleae (Bernard, 1788) populations in olive orchards," Ecological Modelling, Elsevier, vol. 296(C), pages 46-56.
    4. J Blasch & B van der Kroon & P van Beukering & R Munster & S Fabiani & P Nino & S Vanino, 2022. "Farmer preferences for adopting precision farming technologies: a case study from Italy," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 49(1), pages 33-81.
    5. Yun, Seong Do & Gramig, Benjamin M., 2014. "Dynamic Optimization of Ecosystem Services: A Comparative Analysis of Non-Spatial and Spatially-Explicit Models," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170450, Agricultural and Applied Economics Association.
    6. Xiaoxue Du & Levan Elbakidze & Liang Lu & R. Garth Taylor, 2022. "Climate Smart Pest Management," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    7. Lu, Liang & Elbakidze, Levan, 2012. "Application of Comparative Dynamics in Stochastic Invasive Species Management in Agricultural Production," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 125226, Agricultural and Applied Economics Association.
    8. MacDonald, James M. & Korb, Penni & Hoppe, Robert A., 2013. "Farm Size and the Organization of U.S. Crop Farming," Economic Research Report 262221, United States Department of Agriculture, Economic Research Service.
    9. Gu, Xi & Marsh, Thomas L., 2017. "Pesticide Substitution Under Maximum Residue Limits: Application to Hops Production," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258572, Agricultural and Applied Economics Association.
    10. Alina Petronela Alexoaei & Raluca Georgiana Robu & Valentin Cojanu & Dumitru Miron & Ana-Maria Holobiuc, 2022. "Good Practices in Reforming the Common Agricultural Policy to Support the European Green Deal – A Perspective on the Consumption of Pesticides and Fertilizers," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 24(60), pages 525-525, April.
    11. Canales, Elizabeth & Bergtold, Jason S. & Williams, Jeffery & Peterson, Jeffrey, 2015. "Estimating farmers’ risk attitudes and risk premiums for the adoption of conservation practices under different contractual arrangements: A stated choice experiment," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205640, Agricultural and Applied Economics Association.
    12. Schimmelpfennig, David & Lowenberg-DeBoer, James, 2020. "Farm types and precision agriculture adoption: crops, regions, soil variability, and farm size," Agri-Tech Economics Papers 304070, Harper Adams University, Land, Farm & Agribusiness Management Department.
    13. Wang, Sun Ling & Newton, Doris J., 2015. "Productivity and Efficiency of U.S. Field Crop Farms: A Look at Farm Size and Operator’s Gender," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205344, Agricultural and Applied Economics Association.
    14. Luís Loures & Alejandro Chamizo & Paulo Ferreira & Ana Loures & Rui Castanho & Thomas Panagopoulos, 2020. "Assessing the Effectiveness of Precision Agriculture Management Systems in Mediterranean Small Farms," Sustainability, MDPI, vol. 12(9), pages 1-15, May.
    15. Rejesus, Roderick M. & Marra, Michele C. & Roberts, Roland K. & English, Burton C. & Larson, James A. & Paxton, Kenneth W, 2013. "Changes in Producers’ Perceptions of Within-Field Yield Variability after Adoption of Cotton Yield Monitors," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 45(2), pages 1-18, May.
    16. Griffin, Terry W. & Mark, Tyler B. & Ferrell, Shannon & Janzen, Todd & Ibendahl, Gregory & Bennett, Jeff D. & Maurer, Jacob L. & Shanoyan, Aleksan, 2016. "Big Data Considerations for Rural Property Professionals," Journal of the ASFMRA, American Society of Farm Managers and Rural Appraisers, vol. 2015, pages 1-14.
    17. Fausti, Scott W. & Erickson, Bruce & Clay, David E. & Clay, Sharon A., 2021. "The Custom Service Industry’s Role in Precision Agriculture Adoption: A Literature Review," Western Economics Forum, Western Agricultural Economics Association, vol. 19(2), December.
    18. Vasileiadis, V.P. & Sattin, M. & Otto, S. & Veres, A. & Pálinkás, Z. & Ban, R. & Pons, X. & Kudsk, P. & van der Weide, R. & Czembor, E. & Moonen, A.C. & Kiss, J., 2011. "Crop protection in European maize-based cropping systems: Current practices and recommendations for innovative Integrated Pest Management," Agricultural Systems, Elsevier, vol. 104(7), pages 533-540, September.
    19. Liu, Yangxuan & Langemeier, Michael & Small, Ian & Joseph, Laura & Fry, William, 2015. "Risk management strategies using potato precision farming technology," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205417, Agricultural and Applied Economics Association.
    20. James Rudolph Miksanek & George E Heimpel, 2019. "A matrix model describing host–parasitoid population dynamics: The case of Aphelinus certus and soybean aphid," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-20, June.

    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:aaea16:236018. 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/aaeaaea.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.