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.

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.

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.

The Group on Earth Observations, a partnership of governments and international organizations, developed the Global Agricultural Monitoring (GEOGLAM) initiative in response to the growing calls for improved agricultural information. The goal of GEOGLAM is to strengthen the international community’s capacity to produce and disseminate relevant, timely and accurate forecasts of agricultural production at national, regional and global scales through the use of Earth Observations (EO), which include satellite and ground-based observations. This initiative is designed to build on existing agricultural monitoring programs and initiatives at national, regional and global levels and to enhance and strengthen them through international networking, operationally focused research, and data/method sharing.