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GOSSYM

    GOSSYM is a dynamic, process-level simulation model of cotton growth and yield. GOSSYM essentially is a materials balance model which keeps track of carbon and nitrogen in the plant and water and nitrogen in the soil root zone. GOSSYM predicts the response of the field crop to variations in the environment and to cultural inputs. Specifically, the model responds to weather inputs of daily total solar radiation, maximum and minimum air temperatures, daily total wind run, and rainfall and/or irrigation amount. The model also responds to cultural inputs such as preplant and withinseason applications of nitrogen fertilizer, row spacing and within row plant density as they affect total plant population, and cultivation practices.

    PAL

      Profit and Loss (PAL) Farm Budgeting Economic Software for Colorado Agriculture is a windows desktop software for analyzing farm operations budgets. The software was developed in cooperation with Colorado State University.

      iFarm Record Keeper

        The easy to use iFARM Field Record Keeper spreadsheet-based tool was designed to help farmers keep track of field operational records. The tool is designed to be farm specific allowing the user inputs to be specific to their operation. Drop down menus are created from user input including field names, crops, tillages, fertilizer, chemicals, landlords, and storage locations. This information needs only to be entered once. After initial setup each field will be saved as a file with the completed information. Up to four spray operations can be entered per field with the spray reports satisfying current Colorado Department of Agriculture and EPA requirements for Restricted Use Pesticide (RUP). The one page field report meets the fundamental requirements for the current Conservation Security Program (CSP) requirements for record keeping.

        GPFARM

          GPFARM (Great Plains Framework for Agricultural Resource Management) is a simulation model computer application. It incorporates state of the art knowledge in agronomy, animal science, economics, weed science and risk management into a user-friendly, decision support tool. Producers, agricultural consultants, action agencies and scientists can utilize GPFARM to test alternative management strategies that may in turn lead to sustainable agriculture, a reduction in pollution, or maximum economic return. GPFARM Express contains default projects to allow users to quickly set up their operations.

          2017 Census of Agriculture - Census Data Query Tool (CDQT)

            The Census Data Query Tool (CDQT) is a web-based tool that is available to access and download table level data from the Census of Agriculture Volume 1 publication. The data found via the CDQT may also be accessed in the NASS Quick Stats database. The CDQT is unique in that it automatically displays data from the past five Census of Agriculture publications.

            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.

              Feedstock Readiness Level Evaluations Summary Table v4.1

                The table in this dataset collates the results of the FSRL evaluations listed under the Farm2Fly Ag Data Commons datasets to enable users to quickly identify, review, and compare available evaluations. Feedstock readiness level evaluations are performed for a specific feedstock-conversion process combination and for a particular region. FSRL evaluations complement evaluations of Fuel Readiness Level (FRL) and environmental progress.

                Feedstock Readiness Level Evaluations Summary Table v4.0

                  The table in this dataset collates the results of the FSRL evaluations listed under the Farm2Fly Ag Data Commons datasets to enable users to quickly identify, review, and compare available evaluations. Feedstock readiness level evaluations are performed for a specific feedstock-conversion process combination and for a particular region. FSRL evaluations complement evaluations of Fuel Readiness Level (FRL) and environmental progress.

                  USDA-ARS Colorado Maize Water Productivity Dataset 2012-2013

                    The USDA-Agricultural Research Service carried out an experiment on water productivity in response to seasonal timing of irrigation of maize (*Zea mays* L.) at the Limited Irrigation Research Farm (LIRF) facility in northeastern Colorado (40°26’ N, 104°38’ W) starting in 2012. Twelve treatments involved different water availability targeted at specific growth-stages. This dataset includes data from the first two years, which were complete years with intact treatments. Data includes canopy growth and development (canopy height, canopy cover and LAI), irrigation, precipitation, and soil water storage measured periodically through the season; daily estimates of crop evapotranspiration; and seasonal measurement of crop water use, harvest index and crop yield. Hourly and daily weather data are also provided from the CoAgMET, Colorado’s network of meteorological information.

                    USDA Plants Database API in R

                      The USDA maintains a database of plant information - [USDA Plants Database](http://plants.usda.gov/java/) - containing trait data, some of its life history. This resource is an independently created RESTful API for that data. The API, and open issues for bugs/feature requests can be found in the GitHub repository. This tool can be used from the command line, R, Ruby, Python, a browser, etc.