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

Springer Science and Business Media LLC - Tập 22 - Trang 306-315 - 2020
Emma L. White1, J. Alex Thomasson1, Brent Auvermann2, Newell R. Kitchen3, Leland Sandy Pierson1, Dana Porter2, Craig Baillie4, Hendrik Hamann5, Gerrit Hoogenboom6, Todd Janzen7, Rajiv Khosla8, James Lowenberg-DeBoer9, Matt McIntosh10, Seth Murray1, Dave Osborn11, Ashoo Shetty12, Craig Stevenson13, Joe Tevis14, Fletcher Werner15
1Texas A&M University, College Station, USA
2Texas A&M AgriLife Research and Extension Center at Amarillo, Amarillo, USA
3USDA-ARS Cropping Systems and Water Quality Research, Columbia, USA
4University of Southern Queensland, Toowoomba, Australia
5IBM T.J. Watson Research Center, Yorktown Heights, USA
6University of Florida, Gainesville, USA
7Janzen Agricultural Law LLC, Indianapolis, USA
8Colorado State University, Fort Collins, USA
9Harper Adams University, Land, Farm and Agribusiness Management, Newport, UK
10Journalist and Communications Professional, Mc Communications, Wheatley, Canada
11VTX1 Companies, Raymondville, USA
12Amazon Web Services, Dallas, USA
13BASF Canada Agricultural Solutions, Calgary, Canada
14Vis Consulting Inc, Minnetonka, USA
15The Climate Corporation, St. Louis, USA

Tóm tắt

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.

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