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Data from: Field Trapping and Flight Capacity of Eucosma giganteana (Riley) (Lepidoptera: Tortricidae) in Response to Behaviorally Active Congeneric Semiochemicals in Novel Silflower Agroecosystems

    We evaluated the flight behavior of E. giganteana in response to semiochemicals identified from other closely related Eucosma species, including: (Z)- and (E)-8-dodecenyl acetate, (E)-9-dodecenyl acetate, (Z)-8-dodecenol, (E,E)-8,10-dodecadienyl acetate, and (Z,E)-9,12-tetradecadienyl acetate. The goals were to evaluate whether any of these compounds could improve capture of E. giganteana on clear sticky cards in the field, and whether the most attractive volatiles might affect flight behavior on a computer-automated flight mill assay.

    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.

        Irrigation Residue Removal Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network and Resilient Economic Agricultural Practices in Lincoln, Nebraska

          USDA-ARS REAP Study (Ithaca, NE) - NEMEIRR Sustainable intensification of high-yielding production systems may help meet increasing demands for food, fuel, and fiber worldwide. Specifically, corn stover is being removed by producers for livestock purposes, and stover is also targeted as a primary 2nd generation biofuel feedstock. The NEMEIRR experimental objectives are to quantify how stover removal (no removal, moderate removal, high removal) and tillage management (no-till, disk) affect crop yields, soil organic carbon, soil greenhouse gas emissions, and other soil responses (microbial community structure, function; soil health). This experiment is conducted in a fully irrigated continuous corn system in the western Corn Belt, and soil and plant measurements have been taken since study establishment in 2001.

          Data from: Chromosome-level genome assembly and transcriptome of the green alga Chromochloris zofingiensis illuminates astaxanthin production

            For genome assembly of *C. zofingiensis* strain SAG 211–14, we used a hybrid approach blending short reads (Illumina), long reads (Pacific Biosciences of California), and whole-genome optical mapping (OpGen) (SI Appendix, SI Text and Datasets S1–S19, and refer to SI Appendix, Datasets Key). The combined power of these approaches yielded a high-quality haploid nuclear genome of *C. zofingiensis* of ∼58 Mbp distributed over 19 chromosomes (Fig. 2) in the tradition of model organism projects, as opposed to the fragmentary “gene-space” assemblies typical of modern projects using high-throughput methods and associated software. Approximately 99% of reads from the Illumina genomic libraries were accounted for, and nonplaceholder chromosomal sequence covers ∼94% of the optical map. Because no automated pipeline was found able to achieve the desired quality, methods are described in SI Appendix, SI Text.

            Agricultural Land Management Alternative with Numerical Assessment Criteria (ALMANAC) Simulation Model

              The Agricultural Land Management Alternative with Numerical Assessment Criteria (ALMANAC) model simulates crop growth, competition, light interception by leaves, biomass accumulation, partitioning of biomass into grain, water use, nutrient uptake, and growth constraints such as water, temperature, and nutrient stress. Plant development is temperature driven, with duration of growth stages dependent on degree days. Each plant species has a defined base temperature and optimum temperature.