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Big Data and the Ag Sector: More than Lots of Numbers

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  • Sonka, Steve

Abstract

It seems that one can’t go through a work day without seeing some mention of Big Data, its application and its potential to have unprecedented impact. The potential for Big Data application in the agricultural sector is examined. The role of analytics and the variety and velocity characteristics of Big Data as they can apply to the sector are stressed. Integration of data and analysis across business and government entities will be needed for successful implementation. The eventual impact of Big Data within the agricultural sector likely will require both organizational and technological innovation.

Suggested Citation

  • Sonka, Steve, 2014. "Big Data and the Ag Sector: More than Lots of Numbers," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 17(1), pages 1-20, February.
    • Handle: RePEc:ags:ifaamr:163351
    DOI: 10.22004/ag.econ.163351
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    File URL: https://ageconsearch.umn.edu/record/163351/files/20130114.pdf
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    References listed on IDEAS

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    1. Lu, Jianjun & Bowles, Marcus, 2013. "How Will Nanotechnology Affect Agricultural Supply Chains?," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 16(2), pages 1-21, May.
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    Cited by:

    1. Jozwiak, Akos & Milkovics, Matyas & Lakner, Zoltan, 2016. "A Network-Science Support System for Food Chain Safety: A Case from Hungarian Cattle Production," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 19(A), pages 1-26, June.
    2. Ge, Lan & Bogaardt, Marc-Jeroen, 2015. "Bites into the Bits: Governance of Data Harvesting Initiatives in Agrifood Chains," 148th Seminar, November 30-December 1, 2015, The Hague, The Netherlands 229261, European Association of Agricultural Economists.
    3. 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. 2016.
    4. 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.
    5. Whitaker, Stephan D., 2018. "Big Data versus a survey," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 285-296.
    6. Karali, Berna & Isengildina-Massa, Olga & Irwin, Scott H. & Adjemian, Michael K. & Johansson, Robert, 2019. "Are USDA reports still news to changing crop markets?," Food Policy, Elsevier, vol. 84(C), pages 66-76.
    7. Mark, Tyler B. & Griffin, Terry W. & Whitacre, Brian E., 2016. "The Role of Wireless Broadband Connectivity on ‘Big Data’ and the Agricultural Industry in the United States and Australia," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 19(A), pages 1-14, June.
    8. Arunachalam, Deepak & Kumar, Niraj & Kawalek, John Paul, 2018. "Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 416-436.
    9. Jesse Tack & Keith H. Coble & Robert Johansson & Ardian Harri & Barry J. Barnett, 2019. "The Potential Implications of “Big Ag Data” for USDA Forecasts," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 41(4), pages 668-683, December.
    10. Archana Singh & Apoorva Sharma & Gaurav Dubey, 2020. "Big data analytics predicting real estate prices," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 208-219, July.
    11. Lineth Rodríguez & Mihalis Giannakis & Catherine da Cunha, 2018. "Investigating the Enablers of Big Data Analytics on Sustainable Supply Chain," Post-Print hal-01982533, HAL.
    12. Joshua D. Woodard, 2016. "Data Science and Management for Large Scale Empirical Applications in Agricultural and Applied Economics Research," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 38(3), pages 373-388.
    13. Sykuta, Michael E., 2016. "Big Data in Agriculture: Property Rights, Privacy and Competition in Ag Data Services," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 19(A), pages 1-18, June.
    14. Sebastiano Cupertino & Gianluca Vitale & Angelo Riccaboni, 2018. "L?impatto dei Big Data sulle attivit? di pianificazione & controllo aziendali: In caso di studio di una PMI agricola Italiana," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2018(3), pages 59-86.
    15. Protopop, Iuliia & Shanoyan, Aleksan, 2016. "Big Data and Smallholder Farmers: Big Data Applications in the Agri-Food Supply Chain in Developing Countries," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 19(A), pages 1-18, June.
    16. Castillo, Maria Jose & Boucher, Stephen & Carter, Michael, 2016. "Index Insurance: Using Public Data to Benefit Small-Scale Agriculture," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 19(A), pages 1-22, June.
    17. Wolfert, Sjaak & Ge, Lan & Verdouw, Cor & Bogaardt, Marc-Jeroen, 2017. "Big Data in Smart Farming – A review," Agricultural Systems, Elsevier, vol. 153(C), pages 69-80.
    18. Cara Stitzlein & Simon Fielke & François Waldner & Todd Sanderson, 2021. "Reputational Risk Associated with Big Data Research and Development: An Interdisciplinary Perspective," Sustainability, MDPI, vol. 13(16), pages 1-13, August.

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