TY - JOUR
T1 - Report from the conference, ‘identifying obstacles to applying big data in agriculture’
AU - White, Emma L.
AU - Thomasson, J. Alex
AU - Auvermann, Brent
AU - Kitchen, Newell R.
AU - Pierson, Leland Sandy
AU - Porter, Dana
AU - Baillie, Craig
AU - Hamann, Hendrik
AU - Hoogenboom, Gerrit
AU - Janzen, Todd
AU - Khosla, Rajiv
AU - Lowenberg-DeBoer, James
AU - McIntosh, Matt
AU - Murray, Seth
AU - Osborn, Dave
AU - Shetty, Ashoo
AU - Stevenson, Craig
AU - Tevis, Joe
AU - Werner, Fletcher
N1 - Publisher Copyright:
© 2020, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2021/2
Y1 - 2021/2
N2 - 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.
AB - 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.
KW - Automation
KW - Big data
KW - Farm profitability
KW - Food security
UR - https://www.scopus.com/pages/publications/85087981658
U2 - 10.1007/s11119-020-09738-y
DO - 10.1007/s11119-020-09738-y
M3 - Article
AN - SCOPUS:85087981658
SN - 1385-2256
VL - 22
SP - 306
EP - 315
JO - Precision Agriculture
JF - Precision Agriculture
IS - 1
ER -