JDS Journal of Data Science 1683-86021680-743X1680-743X School of Statistics, Renmin University of China JDS1235 10.6339/26-JDS1235 Data Science in Action Use of Farm Equipment Machine-Logged Data to Inform Crop Production Statistics✩ RhodesSeansean.rhodes@usda.gov1∗ JohnsonDavid M.1 https://orcid.org/0000-0002-0446-1328 SartoreLuca21 GarberSamuel C.1 MillerDarcy1 AbreuDenise A.1 United States Department of Agriculture, National Agriculture Statistics Service, Washington DC, 20250, USA National Institute of Statistical Sciences, Washington DC,  20033, USA

The findings and conclusions in this presentation are those of the authors and should not be construed to represent any official USDA or US Government determination or policy.

Corresponding author. Email: sean.rhodes@usda.gov. 202686202600116 Supplementary Material

The supplementary material contains an R program that is made available in a zip file attached to this article.

29920252952026 2026 The Author(s). Published by the School of Statistics and the Center for Applied Statistics, Renmin University of China.2026 Open access article under the CC BY license.

The United States Department of Agriculture’s (USDA’s) National Agricultural Statistics Service (NASS) conducted a pilot study in 2024 to obtain data collected onboard farm machinery and explore their uses for statistical purposes. NASS has recognized high value in these machine-logged data (MLD) systems as they can potentially augment, or even replace, traditional survey efforts while providing additional benefits of reducing respondent burden and improving crop-related estimates. This pilot study ultimately addressed four topics: 1) understanding the obstacles in obtaining MLD from farmers; 2) creating geographic workflows to manage inherent geospatial MLD; 3) developing the linkages to NASS’s tabular list frame information; and 4) assessing the use of MLD to replace survey data for time-sensitive estimates. To study each topic, field-level information was gathered from the MLD systems of dozens of producers over hundreds of fields across the central United States (US) for the 2023 growing season. Results showed that 90% of the fields could be linked to a producer on the NASS list frame. Of those producers, the consistency of MLD versus traditional survey reporting was highly variable for those who were selected for a survey in 2023. Comparisons showed median MLD values were larger than historical NASS survey values. Approximately 48% of survey comparisons showed a difference of 25% or less between MLD and historical NASS survey values. MLD shows promise for use in official statistics; however, further analyses with additional producers’ data and enhancements to MLD collection processes are needed before supplementing traditional survey methods.

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