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Data from: Interseeded cover crop mixtures influence soil water storage during the corn phase of corn-soybean-wheat no-till cropping systems

    This study was initiated to evaluate, during the following corn (*Zea mays* L.) phase, the effects of interseeded cover crops on soil temperature, soil water balances, evapotranspiration, infiltration, and yield and water use efficiency of corn. The study was conducted at the USDA Beltsville Agricultural Research Center, Beltsville, MD from 2017 through 2020. The cropping systems under study were primarily sequences of corn-soybean (*Glycine max* L.)-wheat (*Triticum aestivum* L.)-double crop soybean all planted with no-tillage management.

    Data from: Distance-based decision-making in oviposition by Tribolium castaneum Herbst (Coleoptera: Tenebrionidae) on low- and no-gluten flours

      Red flour beetles have been known to readily infest wheat flour but their likelihood to choose other types of flours is unknown. Red flour beetles will lay eggs in many types of flours but their choice to infest low- and no-gluten flours remains to be tested. Here we test a panel of 14 different commercially available flours in three different choice assays. We find that the beetles lay similar amounts of eggs in buckwheat, teff, millet, rice, and rye flours but that they show significant declines in preference for sorghum, potato, quinoa, cassava, oat, amaranth, garbanzo, spelt, and corn flours.

      Data from: Grain inoculated with different growth stages of the fungus, Aspergillus flavus, affect the close-range foraging behavior by a primary stored product pest, Sitophilus oryzae (Coleoptera: Curculionidae)

        Our goals with this dataset were to 1) isolate, culture, and identify two fungal life stages of Aspergillus flavus, 2) characterize the volatile emissions from grain inoculated by each fungal morphotype, and 3) understand how microbially-produced volatile organic compounds (MVOCs) from each fungal morphotype affect foraging, attraction, and preference by S. oryzae. This dataset includes that derived from headspace collection coupled with GC-MS, where we found the sexual life stage of A. flavus had the most unique emissions of MVOCs compared to the other semiochemical treatments.

        Data from: Vegetation index-based partitioning of evapotranspiration is deficient in grazed systems

          The dataset includes 30 minutes values of partitioned evaporation (E) and transpiration (T), T:ET ratios, and other ancillary datasets for three ET partitioning methods viz. Flux Variance Similarity (FVS) method, Transpiration Estimation Algorithm (TEA), and Underlying Water Use Efficiency (uWUE) method for the three wheat sites. The dataset also contains remote sensing-derived Enhanced Vegetation Index (EVI) data for each site.

          Data from: Vegetation index-based partitioning of evapotranspiration is deficient in grazed systems

            The dataset includes 30 minutes values of partitioned evaporation (E) and transpiration (T), T:ET ratios, and other ancillary datasets for three ET partitioning methods viz. Flux Variance Similarity (FVS) method, Transpiration Estimation Algorithm (TEA), and Underlying Water Use Efficiency (uWUE) method for the three wheat sites. The dataset also contains remote sensing-derived Enhanced Vegetation Index (EVI) data for each site.

            SGA (farm)

              Stored Grain Advisor (SGA) is a decision support system for managing insect pests of farm-stored wheat. The program predicts the likelihood of insect infestation, and recommends appropriate preventative actions . It also provides advice on how to sample and identify insect pests of stored wheat. SGA Pro was designed for use in commercial elevators as part of the Areawide IPM Project for stored grain. Grain samples are taken with a vacuum probe and processed over an inclined sieve. SGA Pro analyzes the insect data, grain temperatures and moistures, and determines which bins need to be fumigated.

              Data from: Attraction, mobility, and preference by Lasioderma serricorne (F.) (Coleoptera: Ptinidae) to microbially-mediated volatile emissions by two species of fungi in stored grain

                Our goals were to 1) isolate, and culture two fungal morphotypes, 2) characterize the volatile emissions from grain inoculated by each fungal morphotype (Aspergillus flavus or Fusarium spp.) compared to uninoculated and sanitized grain, and 3) understand how MVOCs from each morphotype affects mobility, attraction, and preference by L. serricorne.

                Legacy Phosphorus and Potassium Correlation Experiments: Qulin, Missouri

                  Correlation experiments for P and K were conducted from 1968-1973 at a research farm in Qulin, Missouri to better define the relationships between soil tests, crop yields, and fertilizer treatments. Three crop rotations each were conducted for P and K trials (ranges C, D, E, F, G, and H), and included corn, soybean, wheat, cotton, and sorghum.

                  The Bronson Files, Dataset 4, Field 105, 2013

                    Active optical proximal wheat canopy sensing spatial data and including additional related metrics such as canopy thermal and height are presented. Agronomic nitrogen and irrigation management related field operations are listed. Unique research experimentation intermediate analysis table is made available, along with the raw data. The raw data recordings, and annotated table outputs with calculated VIs are made available. Plot polygon coordinate designations allow a re-intersection spatial analysis. Data was collected in the 2013 season at Maricopa Agricultural Center, Arizona, USA. High throughput proximal plant phenotyping via electronic sampling and data processing method approach is exampled. Acquired data using USDA Maricopa first mobile platforms, such as the Proximal Sensing Cart Mark1, SAS and GIS compute processing output tables, including Excel formatted examples are presented, where data tabulation and analysis is available. The weekly proximal sensing data collected include canopy reflectance at six wavelengths, ultrasonic distance sensing of canopy height, and infrared thermometry. Ten levels gradient irrigation application from linear move sprinkler system were applied. Soil physical texture and fertility chemistry results are available. Yield and seed information is presented.