Skip to main content

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, “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.

This is a preview of subscription content, access via your institution.


Download references


This work was supported by a United States Department of Agriculture—National Institute of Food and Agriculture, Food and Agriculture Cyberinformatics and Tools (USDA NIFA FACT) initiative conference Grant Number 2018-67021-28692.

Author information

Authors and Affiliations



Conceptualized and developed conference: ELW, JAT; Wrote manuscript: ELW, JAT; Contributed technical material: CB, HH, GH, TJ, RK, JL-DB, MM, SM, DO, AS, CS, JT, JAT, FW; Organized scenarios: BA, NRK, LSP, DP; Revised: BA, LSP, DP, HH, GH, JL-DB, SM, JT, JAT.

Corresponding author

Correspondence to Emma L. White.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

White, E.L., Thomasson, J.A., Auvermann, B. et al. Report from the conference, ‘identifying obstacles to applying big data in agriculture’. Precision Agric 22, 306–315 (2021).

Download citation

  • Published:

  • Issue Date:

  • DOI: