Report from the conference, ‘identifying obstacles to applying big data in agriculture’

Article

White, Emma L., Thomasson, J. Alex, Auvermann, Brent, Kitchen, Newell R., Pierson, Leland Sandy, Porter, Dana, Baillie, Craig, Hamann, Hendrik, Hoogenboom, Gerrit, Janzen, Todd, Khosla, Rajiv, Lowenberg‑DeBoer, James, McIntosh, Matt, Murray, Seth, Osborn, Dave, Shetty, Ashoo, Stevenson, Craig, Tevis, Joe and Werner, Fletcher. 2021. "Report from the conference, ‘identifying obstacles to applying big data in agriculture’." Precision Agriculture. 22 (1), pp. 306-315. https://doi.org/10.1007/s11119-020-09738-y
Article Title

Report from the conference, ‘identifying obstacles to applying big data in agriculture’

ERA Journal ID5325
Article CategoryArticle
AuthorsWhite, Emma L., Thomasson, J. Alex, Auvermann, Brent, Kitchen, Newell R., Pierson, Leland Sandy, Porter, Dana, Baillie, Craig, Hamann, Hendrik, Hoogenboom, Gerrit, Janzen, Todd, Khosla, Rajiv, Lowenberg‑DeBoer, James, McIntosh, Matt, Murray, Seth, Osborn, Dave, Shetty, Ashoo, Stevenson, Craig, Tevis, Joe and Werner, Fletcher
Journal TitlePrecision Agriculture
Journal Citation22 (1), pp. 306-315
Number of Pages10
Year2021
PublisherSpringer
Place of PublicationUnited States
ISSN1385-2256
1573-1618
Digital Object Identifier (DOI)https://doi.org/10.1007/s11119-020-09738-y
Web Address (URL)https://link.springer.com/article/10.1007/s11119-020-09738-y
Abstract

Data-centric technology has not undergone widespread adoption in production agriculture but could address global needs for food security and farm profitability. Participants in the U.S. Department of Agriculture (USDA) National Institute for Food and Agriculture (NIFA) funded conference, “Identifying Obstacles to Applying Big Data in Agriculture,” held in Houston, TX, in August 2018, defined detailed scenarios in which on-farm decisions could benefit from the application of Big Data. The participants came from multiple academic fields, agricultural industries and government organizations and, in addition to defining the scenarios, they identified obstacles to implementing Big Data in these scenarios as well as potential solutions. This communication is a report on the conference and its outcomes. Two scenarios are included to represent the overall key findings in commonly identified obstacles and solutions: “In-season yield prediction for real-time decision-making”, and “Sow lameness.” Common obstacles identified at the conference included error in the data, inaccessibility of the data, unusability of the data, incompatibility of data generation and processing systems, the inconvenience of handling the data, the lack of a clear return on investment (ROI) and unclear ownership. Less common but valuable solutions to common obstacles are also noted.

KeywordsAutomation; Big data; Farm proftability; Food security
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020300802. Horticultural crop growth and development
460304. Computer vision
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Byline AffiliationsTexas A&M University, United States
U.S. Department of Agriculture-Agricultural Research Service, United States
University of Southern Queensland
IBM, United States
University of Florida, United States
Janzen Agricultural Law LLC, United States
Colorado State University, United States
Harper Adams University, United Kingdom
MC Communications, Canada
VTX1 Companies, United States
Amazon Web Services, United States
BASF Canada Agricultural Solutions, Canada
Vis Consulting, United States
The Climate Corporation, United States
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