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Cassavabase

    The Next Generation Cassava Breeding (NEXTGEN Cassava) project aims to significantly increase the rate of genetic improvement in cassava breeding and unlock the full potential of cassava, a staple crop central to food security and livelihoods across Africa. The project will implement and empirically test a new breeding method known as Genomic Selection that relies on statistical modeling to predict cassava performance before field-testing, and dramatically accelerates the breeding cycle.

    Data from: Gas emissions from dairy barnyards

      To assess the magnitude of greenhouse gas (GHG) fluxes, nutrient runoff and leaching from dairy barnyards and to characterize factors controlling these fluxes, nine barnyards were built at the U.S. Dairy Forage Research Center Farm in Prairie du Sac, WI (latitude 43.33N, longitude 89.71W). The barnyards were designed to simulate outdoor cattle-holding areas on commercial dairy farms in Wisconsin. Each barnyard was approximately 7m x 7m; areas of barnyards 1-9 were 51.91, 47.29, 50.97, 46.32, 45.64, 46.30, 48.93, 48.78, 46.73 square meters, respectively. Factors investigated included three different surface materials (bark, sand, soil) and timing of cattle corralling. Each barnyard included a gravity drainage system that allowed leachate to be pumped out and analyzed. Each soil-covered barnyard also included a system to intercept runoff at the perimeter and drain to a pumping port, similar to the leachate systems.

      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.

        Feedstock Readiness Level Evaluations Summary Table v3.0

          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.

          Feedstock Readiness Level (FSRL) evaluation: Saccharum spp. (energy cane), Alcohol-to-Jet, Southeast, Jun. 2017

            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. The data from this evaluation, compiled in June 2017, assesses the maturity of *Saccharum spp.* (energy cane), as a feedstock for the Alcohol-to-Jet conversion process in the United States South region.

            Feedstock Readiness Level (FSRL) evaluation: Triticum aestivum (wheat straw), Alcohol-to-Jet, Northwest, May 2017

              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. The data from this evaluation, compiled in May 2017, assesses the maturity of *Triticum aestivum* (wheat straw), as a feedstock for the Alcohol-to-Jet conversion process in the United States Northwest region.

              Feedstock Readiness Level (FSRL) evaluation: Triticum aestivum (wheat straw), Alcohol-to-Jet, Central East, May 2017

                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. The data from this evaluation, compiled in May 2017, assesses the maturity of *Triticum aestivum* (wheat straw), as a feedstock for the Alcohol-to-Jet conversion process in the United States Central East region.

                Feedstock Readiness Level (FSRL) evaluation: Populus (poplar), Alcohol-to-Jet, Northwest, May 2017

                  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. The data from this evaluation, compiled in September 2016, assesses the maturity of *Populus* spp. (poplar), as a feedstock for the Alcohol-to-Jet conversion process in the United States Northwest region.

                  Feedstock Readiness Level (FSRL) evaluation: Millettia pinnata (pongamia), hydroprocessing (HEFA), Southeast, May 2017

                    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. The data from this evaluation, compiled in May 2017, assesses the maturity of *Millettia pinnata* (pongamia), as a feedstock for the hydroprocessed esters and fatty acids (HEFA) conversion process in the United States Southeast region.

                    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.