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The Ag Data Commons is migrating

The Ag Data Commons is migrating to a new institutional portal on Figshare. The current system is available for search and download only. The new platform is open for submission with assistance from Ag Data Commons curators. Please contact NAL-ADC-Curator@usda.gov, if you need to publish or update your datasets.

Floridan Aquifer Collaborative Engagement for Sustainability (FACETS) - Field trial data from University of Georgia Stripling Irrigation Research Park (SIRP): ARDN Products

    ARDN (Agricultural Research Data Network) annotations for "Floridan Aquifer Collaborative Engagement for Sustainability (FACETS) - Field trial data from University of Georgia Stripling Irrigation Research Park (SIRP)". The ARDN project (https://data.nal.usda.gov/ardn) is a network of datasets harmonized and aggregated using the ICASA vocabulary, as recommended by USDA NAL (https://data.nal.usda.gov/data-dictionary-examples) and described in detail here: www.tinyurl.com/icasa-mvl”. The original dataset presents evaluations of different irrigation and fertilization treatments (corn and cotton have three nitrogen fertilization and three irrigation treatments, peanut has nine irrigation treatments and no N fertilizer treatment) at the University of Georgia’s Stripling Irrigation Research Park (SIRP) located near Camilla, Georgia in a 4 ha research field.

    Floridan Aquifer Collaborative Engagement for Sustainability (FACETS) - Field trial data from University of Georgia Stripling Irrigation Research Park (SIRP)

      Data are presented to evaluate different irrigation and fertilization treatments (corn and cotton have three nitrogen fertilization and three irrigation treatments, peanut has nine irrigation treatments and no N fertilizer treatment) at the University of Georgia’s Stripling Irrigation Research Park (SIRP) located near Camilla, Georgia in a 4 ha research field.

      On-Farm Residue Removal Study for Resilient Economic Agricultural Practices in Morris, Minnesota

        Interest in harvesting crop residues for energy has waxed and waned since the oil embargo of 1973. Since the at least the late 1990’s interest has been renewed due to concern of peak oil, highly volatile natural gas prices, replacing fossil fuel with renewable sources and a push for energy independence. The studies conducted on harvesting crop residues during the 1970’s and1980’s focused primarily on erosion risk and nutrient removal as a result early estimates of residue availability focused on erosion control.

        Transforming Drainage Research Data (USDA-NIFA Award No. 2015-68007-23193)

          This dataset contains research data compiled by the “Managing Water for Increased Resiliency of Drained Agricultural Landscapes” project a.k.a. Transforming Drainage (https://transformingdrainage.org). These data began in 1996 and include plot- and field-level measurements for 39 experiments across the Midwest and North Carolina. Practices studied include controlled drainage, drainage water recycling, and saturated buffers. In total, 219 variables are reported and span 207 site-years for tile drainage, 154 for nitrate-N load, 181 for water quality, 92 for water table, and 201 for crop yield.

          Sustainable Corn CAP Research Data (USDA-NIFA Award No. 2011-68002-30190): ARDN Products

            ARDN (Agricultural Research Data Network) annotations for Sustainable Corn CAP Research Data (USDA-NIFA Award No. 2011-68002-30190). These data are a subset of the Sustainable Corn CAP (Cropping Systems Coordinated Agricultural Project: Climate Change, Mitigation, and Adaptation in Corn-based Cropping Systems) data specifically developed for Agricultural Research Data Network with csv and json files for easy ingestion into crop models.

            CPM - Cotton Production Model

              A new process-based cotton model, CPM, has been developed to simulate the growth and development of upland cotton (Gossypium hirsutum L.) throughout the growing season with minimal data input. CPM predicts final cotton yield for any combination of soil, weather, cultivar and sequence of management actions.