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Ag Data Commons migration begins October 18, 2023

The Ag Data Commons is migrating to a new platform – an institutional portal on Figshare. Starting October 18 the current system will be available for search and download only. Submissions will resume after the launch of our portal on Figshare in November. Stay tuned for details!

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.

      Irrigation Residue Removal Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network and Resilient Economic Agricultural Practices in Lincoln, Nebraska

        USDA-ARS REAP Study (Ithaca, NE) - NEMEIRR Sustainable intensification of high-yielding production systems may help meet increasing demands for food, fuel, and fiber worldwide. Specifically, corn stover is being removed by producers for livestock purposes, and stover is also targeted as a primary 2nd generation biofuel feedstock. The NEMEIRR experimental objectives are to quantify how stover removal (no removal, moderate removal, high removal) and tillage management (no-till, disk) affect crop yields, soil organic carbon, soil greenhouse gas emissions, and other soil responses (microbial community structure, function; soil health). This experiment is conducted in a fully irrigated continuous corn system in the western Corn Belt, and soil and plant measurements have been taken since study establishment in 2001.

        Data from: Agro-environmental consequences of shifting from nitrogen- to phosphorus-based manure management of corn.

          This experiment was designed to measure greenhouse gas (GHG) fluxes and related agronomic characteristics of a long-term corn-alfalfa rotational cropping system fertilized with manure (liquid versus semi-composted separated solids) from dairy animals. Different manure-application treatments were sized to fulfill two conditions: (1) an application rate to meet the agronomic soil nitrogen requirement of corn (“N-based” without manure incorporation, more manure), and (2) an application rate to match or to replace the phosphorus removal by silage corn from soils (“P-based” with incorporation, less manure). In addition, treatments tested the effects of liquid vs. composted-solid manure, and the effects of chemical nitrogen fertilizer. The controls consisted of non-manured inorganic N treatments (sidedress applications). These activities were performed during the 2014 and 2015 growing seasons as part of the Dairy Coordinated Agricultural Project, or Dairy CAP, as described below. The data from this experiment give insight into the factors controlling GHG emissions from similar cropping systems, and may be used for model calibration and validation after careful evaluation of the flagged data.