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Feedstock Readiness Level (FSRL) evaluation: Panicum virgatum (switchgrass), Alcohol-to-Jet, Southeast, Sept. 2016

    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 *Panicum virgatum* (switchgrass) as a feedstock for the Alcohol-to-Jet conversion process in the United States Southeast region.

    Feedstock Readiness Level (FSRL) evaluation: Miscanthus x giganteus (giant miscanthus), Alcohol-to-Jet, Southeast, Sept. 2016

      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 *Miscanthus x giganteus* (giant miscanthus) as a feedstock for the Alcohol-to-Jet conversion process in the United States Southeast region.

      Feedstock Readiness Level (FSRL) evaluation: Brassica napus (Canola), hydroprocessed esters & fatty acids (HEFA), Southeast, Sept. 2016

        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 *Brassica napus* (Canola) as a feedstock for the Hydroprocessed Esters and Fatty Acids (HEFA) conversion process in the United States Southeast region.

        Data from: Soil Water Holding Capacity Mitigates Downside Risk and Volatility in US Rainfed Maize: Time to Invest in Soil Organic Matter?

          This dataset includes county-level annual data on maize (Zea mays L.) yield, soil physical and chemical characteristics, and mean weather data for 2000 through 2014 for IL, MI, MN and PA. The data were aggregated from public databases, including NASS Quick Stats, NOAA Climate Data Online, and the USDA-NRCS Web Soil Survey. U.S. counties were the experimental unit for this study, and all data are county-level averages. Covariances among county-level maize yield stability and environmental variability were analyzed using structural equation models (SEM) and linear mixed effects (LME) models.

          Unit process data for field operations: work processes and farm implements version 1

            This document describes the preparation of datasets for the LCA Commons that represent unit process/ gate-to-gate operations for field operations (a.k.a. work processes e.g., soil preparation and planting for conventional tillage, applying fertilizer with incorporation) and farm implements (e.g., operation of moldboard plows, broadcast sprayers) used in the production of field crops. The data cover 49 types of field operations and 104 types of farm implements for 9 crops in 36 U.S. states, resulting in the development of almost 19,000 unit process datasets. The field operation and farm implement datasets described herein fall between the field crop production and the aggregated fleet equipment datasets already in the Commons.

            Unit process data for agricultural self-propelled equipment version 1

              This document describes the preparation of datasets for the LCA Digital Commons that represent unit process/ gate-to-gate operations for the production of work (in MJ) by agricultural self-propelled equipment and fleets of agricultural self-propelled equipment. The data cover 19 types of fleets and over 200 types of self-propelled equipment datasets, representing the potential to prepare thousands of unit-process datasets by varying the operating and model years, applicable power ranges, and operating temperatures.

              USDA LCA Commons Data Submission Guidelines

                This document provides instructions for editing and submitting unit process or product system models to the USDA LCA Commons life cycle inventory (LCI) database. The LCA Commons LCI database uses the openLCA life cycle modeling tool's database schema. Therefore, this document describes how to import and edit data in openLCA and name and classify flows such that they properly import into and operate in the database. This document also describes metadata or documentation requirements for posting models to the LCA Commons. This document is an evolving standard for LCA Commons data. As USDA-NAL continues to gain experience in managing a general purpose LCI database and global conventions continue to evolve, so too will the LCA Commons Submission Guidelines.

                GrainGenes, the genome database for small-grain crops

                  GrainGenes is a popular repository for information about genetic maps, mapping probes and primers, genes, alleles and QTLs for the following crops: wheat, barley, rye and oat. Documentation includes such data as primer sequences, polymorphism descriptions, genotype and trait scoring data, experimental protocols used, and photographs of marker polymorphisms, disease symptoms and mutant phenotypes. These data, curated with the help of many members of the research community, are integrated with sequence and bibliographic records selected from external databases and results of BLAST searches of the ESTs.

                  Unit process data for Rapeseed production in the U.S. wheat belt

                    Unit processes represent wheat-wheat-fallow and wheat-wheat-rapeseed crop production simulations that illustrate using the IPCC (Tier 1) method for calculating changes in soil C and the roundtable on sustainable biomaterials (RSB) method for estimating N2O emissions in different locations for the use in modeling the crop production portion of the HRJ lifecycle. Data are archived in a SimaPro .csv file, which can be imported into various life cycle assessment modeling tools.