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

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

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, “Identifyin...

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Published in:Precision agriculture Vol. 22; no. 1; pp. 306 - 315
Main Authors: 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, Werner, Fletcher
Format: Journal Article
Language:English
Published: New York Springer US 01-02-2021
Springer Nature B.V
Subjects:
Agricultural industry
Agriculture
Atmospheric Sciences
Barriers
Big Data
Biomedical and Life Sciences
Brief Communication
Chemistry and Earth Sciences
Computer Science
Decision making
Economics
Farms
Food security
Incompatibility
Life Sciences
Physics
Profitability
Remote Sensing/Photogrammetry
Return on investment
Soil Science & Conservation
Statistics for Engineering
Automation
Big data
Farm profitability
Food security
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Summary: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.
ISSN:1385-2256
1573-1618
DOI:10.1007/s11119-020-09738-y