U.S. flag

An official website of the United States government

Comparison of methods to detect low levels of Salmonella enterica in surface waters to support antimicrobial resistance surveillance efforts performed in multiple laboratories

    Identifying and developing effective and sensitive detection methods for antimicrobial resistant Salmonella enterica from surface water is a goal of the U.S. National Antimicrobial Resistance Monitoring System (NARMS). No specific microbiological methods used in surveillance efforts for Salmonella enterica or antimicrobial resistant S. enterica in water have been standardized or reported in the U.S. Here we describe a multi-laboratory evaluation of four methods, bulk water enrichment (BW), vertical Modified Moore Swab (VMMS), modified Standard Method 9260.B3 (SM), and dead-end ultrafiltration (DEUF), to recover S. enterica from surface water.

    Data from: Plant Tissue Characteristics of Miscanthus x giganteus v2

      As part of a study identifying relationships between environmental variables and insect distributions within a bioenergy crop, giant miscanthus (Miscanthus x giganteus) samples were collected in October 2016 at 33 locations within a field in southeast Georgia, USA. This dataset describes the chemical composition of giant miscanthus leaves and stems including the total carbon (TC) and nitrogen (TN) content, total macro- and micronutrients.

      Data from: Plant Tissue Characteristics of Miscanthus x giganteus

        As part of a study identifying relationships between environmental variables and insect distributions within a bioenergy crop, giant miscanthus (Miscanthus x giganteus) samples were collected in October 2016 at 33 locations within a field in southeast Georgia, USA. This dataset describes the chemical composition of giant miscanthus leaves and stems including the total carbon (TC) and nitrogen (TN) content, total macro- and micronutrients.

        BAR- The Bio-Analytic Resource for Plant Biology

          BAR is a collection of web-based, user-friendly tools for exploring, visualizing, and analyzing large datasets from plants. Supported are expression data, Next-Gen sequence data, protein-protein interactions, polymorphisms / conservation, and protein 3-D structures.