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NLET - National Load Estimating Tool

    NLET (National Load Estimating Tool) is a web-based tool for estimating pollutant loads in watersheds across the contiguous United States. This tool helps visualize the effects of land use patterns, cultivated crops, and conservation practices through graphical representation.

    Sodium Monitoring Dataset

      The Agricultural Research Service of the US Department of Agriculture (USDA) in collaboration with other government agencies has a program to track changes in the sodium content of commercially processed and restaurant foods. Results of these monitoring activities are shared once a year in the [Sodium Monitoring Dataset](https://www.ars.usda.gov/ARSUserFiles/80400525/Sodium/Copy%20of%20SodiumMonitoringDatasetUpdatedJuly2616.xlsx) and [USDA National Nutrient Database for Standard Reference](https://www.ars.usda.gov/Services/docs.htm?docid=8964) and once every two years in the [Food and Nutrient Database for Dietary Studies](https://www.ars.usda.gov/Services/docs.htm?docid=12068).

      APEX – Agricultural Policy/Environmental eXtender Model

        Agricultural Policy/Environmental eXtender (APEX) has components for routing water, sediment, nutrients, and pesticides across complex landscapes and channel systems to the watershed outlet as well as groundwater and reservoir components. A watershed can be subdivided as much as necessary to assure that each subarea is relatively homogeneous in terms of soil, land use, management, and weather. APEX was constructed to evaluate various land management strategies considering sustainability, erosion (wind, sheet, and channel), economics, water supply and quality, soil quality, plant competition, weather, and pests. The routing of water, sediment, nutrient, and pesticide capabilities are some of the most comprehensive available in current landscape-scale models and can be simulated between subareas and channel systems within the model. APEX can perform long-term continuous simulations for modeling the impacts of different nutrient management practices, tillage operations, conservation practices, alternative cropping systems, and other management practices on surface runoff and losses of sediment, nutrients, and other pollutant indicators.

        International Soil Carbon Network

          The ISCN is a self-chartered, international, collaborative organization composed of scientists who recognize a need for and value in large-scale synthesis of soil carbon science.

          NUOnet (Nutrient Use and Outcome Network) database

            The Nutrient Uptake and Outcomes (NUOnet) database will be able to help establish baselines on nutrient use efficiencies; processes contributing to nutrient losses; and processes contributing to optimal crop yield, nutritional and organoleptic quality. This national database could be used to calculate many different environmental indicators from a comprehensive understanding of nutrient stocks and flows.

            USDA Branded Food Products Database

              The USDA Branded Food Products Database is the result of a Public-Private Partnership, whose goal is to enhance public health and the sharing of open data by complementing USDA Food Composition Databases with nutrient composition of branded foods and private label data provided by the food industry. [Note: Integrated as part of FoodData Central, April 2019.]

              Low-Disturbance Manure Incorporation

                The LDMI experiment (Low-Disturbance Manure Incorporation) was designed to evaluate nutrient losses with conventional and improved liquid dairy manure management practices in a corn silage (*Zea mays*) / rye cover-crop (*Secale cereale*) system. The improved manure management treatments were designed to incorporate manure while maintaining crop residue for erosion control. Field observations included greenhouse gas (GHG) fluxes from soil, soil nutrient concentrations, crop growth and harvest biomass and nutrient content, as well as monitoring of soil physical and chemical properties. Observations from LDMI have been used for parameterization and validation of computer simulation models of GHG emissions from dairy farms (Gaillard et al., submitted). The LDMI experiment was performed as part of the Dairy CAP.

                Manure application methods for alfalfa-grass

                  The MAMA experiment (Manure Application Methods for Alfalfa-Grass), from the USDA-ARS research station in Marshfield, WI was designed to evaluate nutrient and pathogen losses with conventional and improved liquid dairy manure management practices for alfalfa-grass production. Observations from MAMA have also been used for parameterization and validation of computer simulation models of greenhouse gas (GHG) emissions from dairy farms.