AndreaBozzo/ceres-open-data-index huggingface dataset:
CCE Nitrogen Index Tool

<p>The effectiveness of nitrogen fertilizer in maximizing agricultural production and increasing economic returns for farmers has led to its widespread use. However, when this element is applied to a farming system, it can enter the surrounding environment via atmospheric, surface and leaching pathways. Consultants, extension agents, farmers, and other stakeholders need tools than can be used to quickly calculate the risk of nitrogen movement into the environment. The Nitrogen Index can assist users in making these assessments by integrating data on a series of management practices, weather conditions, soil characteristics and off-site factors. This tool has been tested using data from different agroecosystems across the United States, China, Mexico, Argentina, a Mediterranean region in Spain, and the Caribbean. It has performed well in comparing the effects of different management practices on nitrogen losses by distinguishing practices with high and very high risk levels from practices with medium, low and very low risk levels. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Nitrogen Index Tool - N Index 4.5.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=275&modecode=30-12-30-15">https://www.ars.usda.gov/research/software/download/?softwareid=275&modecode=30-12-30-15</a> </p><p>download page</p></li></ul><p></p>

Tags: ars, data-gov, fertilizer, nitrogen
Organization: Department of Agriculture
Gramene

<p>Gramene is a curated, open-source, integrated data resource for comparative functional genomics in crops and model plant species.</p>
<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: The Gramene Database website.</p> <p>File Name: Web Page, url: <a href="http://www.gramene.org/" target="_blank">http://www.gramene.org/</a> </p><p>Gramene is a curated, open-source, integrated data resource for comparative functional genomics in crops and model plant species.  The Gramene database is freely available for download and use as long as Gramene is cited as the source (see <a href="http://www.gramene.org/cite)." target="_blank">http://www.gramene.org/cite).</a> This includes the tools available at Gramene including but not limited to RiceCyc, CMap Viewer, Gramene Mart and the Genome Browser. When using Gramene or the information derived from Gramene databases, kindly acknowledge the Gramene project by citing the web address (<a href="http://www.gramene.org)" target="_blank">http://www.gramene.org)</a> and identifying the version of Gramene being used (identified on the Home page) and the date accessed.</p></li></ul>

Tags: ars, crops, data-gov, genome, genomics, np301, online-database, plants
Organization: Department of Agriculture
Data from: The effect of a bimodal gravel size distribution on clean-out depth of sand

<p dir="ltr">This dataset includes the data in the figures for the article entitled  "The effect of a bimodal gravel size distribution on clean-out depth of sand", which is to be published in the Journal of Hydraulic Engineering. The authors are: Kuhnle, R. A., Smith, J. E., Wren, D. G., and Langendoen, E. L.</p><p dir="ltr">The clogging of the gravel surface layer in gravel-bedded channels with finer sediment (< 2 mm) is a common problem that negatively impacts stream bed habitat quality. Most existing measurements of surface layer sediment clean-out depth are from experiments with narrow gravel size distributions; therefore, a new set of experiments was conducted to explore the effect of widely distributed bimodal gravel fractions on the clean-out depth of interstitial sand. Experiments were used to measure the terminal clean-out depth of 0.136 mm sand from bed material substrates composed of unimodal median diameter gravel of 7.16 mm and bimodal bed material with modes of 7.31 and 34.66 mm and a median diameter of 33.46 mm. It was found that the clean-out depth of sand from immobile gravel beds could be predicted by scaling the bed shear stress using the cumulative probability distribution of the elevations of the surface of the gravel bed.</p>

Tags: gravel-cleanout, gravel-roughness, sediment-transport, shear-stress-modulation
Organization: Department of Agriculture
WinSRFR

<p>WinSRFR is a hydraulic analysis tool for surface irrigation systems. The software combines simulation, evaluation, operational analysis, and design functionalities. Intended users are irrigation specialists, extension agents, researchers, consultants, students, and farmers with moderate to advanced knowledge of surface irrigation hydraulics. WinSRFR 5.1 is the fifth major release of the software. The new version offers a reprogrammed simulation engine, an application programming interface, batch simulation capabilities, and enhancements to the user interface. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: WinSRFR 5.1 Software and User Manual.</p> <p>File Name: WinSRFR5.pdf</p><p>Resource Description: Download WinSRFR Version 5.1.1 (2019) from the ARS software page at <a href="https://www.ars.usda.gov/research/software/download/?softwareid=502&mode">https://www.ars.usda.gov/research/software/download/?softwareid=502&mode</a> / <a href="https://www.ars.usda.gov/research/software/?modeCode=20-20-05-15">https://www.ars.usda.gov/research/software/?modeCode=20-20-05-15</a></p>
<p>Choose file link below to download the user manual.</p></li></ul><p></p>

Tags: api, ars, data-gov, hydraulic-analysis, irrigation, model, software
Organization: Department of Agriculture
CSR2 Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Watkinsville, Georgia

<p>CSR2 Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Watkinsville, Georgia
</p> <div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Watkinsville, GA CSR2 Study (GAJPCSR2) CSV data.</p> <p>File Name: GAJPCSR2_csv_data.zip</p><p>Resource Description: CSV format data on Experimental Units, Field Sites, Grazing Plants, Soil Biology, Soil Chemistry, Soil Physics, Amendments, Grazing, Persons, Treatments, Weather Daily, Weather Station.</p></li></ul>

Tags: ars, data-gov, environment, farming, iso-metadata, np211, np212
Organization: Department of Agriculture
Data from: Evaluating a Novel Core-and-Perimeter Delimiting Trapping Survey Design for Insects: I. Field Experiment

<p dir="ltr">We compared the "core and perimeter" (C&P) and "fully trapped" (FT) designs in a mark-release-recapture experiment with <i>Ceratitis capitata</i> (Weidemann; Diptera: Tephritidae) in Hawaii in 2022. Each design had four repetitions with four separate releases of flies, and six collection days from 1 to 14 days after release. The square FT grid had 99 traps over 0.92-km<sup>2</sup>, plus 24 “sentinel” traps just outside. The circular C&P grid had 20 core traps, and 108 traps in a 220 m-wide perimeter, set 500 m from the release point (smaller than the recommended radius).</p>

Tags: chemical-ecology-study, hawaii, invasive-pest, mark-release-recapture, tephritidae, tropical
Organization: Department of Agriculture
Data from: Genetic diversity, population structure, and selection of core germplasm sets from the USDA sweetpotato (Ipomoea batatas) collection

<p>R scripts and associated data used to select the sweetpotato core sets described in:
Slonecki, T. J., Rutter, W. B., Olukolu, B. A., Yencho, G. C., Jackson, D. M., & Wadl, P. A. (2023). Genetic diversity, population structure, and selection of breeder germplasm subsets from the USDA sweetpotato (Ipomoea batatas) collection. Frontiers in Plant Science, 13. <a href="https://doi.org/10.3389/fpls.2022.1022555">https://doi.org/10.3389/fpls.2022.1022555</a></p>
<p>Resources in this dataset:</p>
<p>Title: Sweetpotato_phenotype_classification_scripts
File name: SP_phenotype_classification_scripts_7-29-21.R
Description: R Scripts used to format, classify, and retain individuals with 'rare' phenotypes into the core collections, generating the reduced 508 accession dataset from which the core sets were selected</p>
<p>Title: Sweetpotato_core_set_selection_scripts
File name: Core_set_selection_permutations_8-24-20.R
Description: Core set sampling scripts derived from previous R scripts and data generated in "SP_phenotype_classification_scripts"</p>
<p>Title: Original Phenotype data
File name: Core_Sets_VanRaden_Complete_Passport_Phenotype_July_2021.xlsx
Description: Phenotype data downloaded from GRIN sweetpotato collection and used for core set selection</p>
<p>Title: SP_core_selection_Rdata
File name: SP_core_selection_data_7-30-21.zip
Description: Data sets used in conjunction with Rscripts from Slonecki et. al. 2022</p>

Tags: ars, core-germplasm-set, data-gov, genotype, np301, np303, phenotype, sweet-potatoes
Organization: Department of Agriculture
Data from: Tephritid fruit fly gut bacterial population and community dynamics following adult emergence

<p>Data include microbial count data (CFUs), 16S-rRNA copy number data (qPCR), and microbial community (microbiome) data from the guts of the invasive tephritid fruit flies, melon fly (Zeugodacus cucurbitae) and medfly (Ceratitis capitata).</p>
<p>Resources in this dataset:</p>
<ul>
<li>
<p>Resource Title: R code for dada2 processing and stacked bar charts of control microbiomes
File Name: Control_Processing.zip
Resource Description: Data showing performance of known controls (purchased from Zymo Research) using in-house DNA extraction and PCR methods for 16S-rRNA gene amplification and sequencing.</p>
</li>
<li>
<p>Resource Title: Data processing of 16S amplicon data
File Name: 16S SSU rRNA Microbiome Data Processing and Analysis.zip
Resource Description: Raw data and accompanying R scripts for analysis of figure and generation of figures and tables. Data files include both amplicon sequence variant (ASV) count data matrix and accompanying ASV sequence files and taxonomies. Analysis and figure generation are made through independent R files.</p>
</li>
<li>
<p>Resource Title: Data and analysis of fly culturable titers
File Name: CFU titers.zip
Resource Description: Colony forming units (CFUs) of fruit flies at different ages and the R code for figure generation and analysis.</p>
</li>
<li>
<p>Resource Title: qPCR of 16S rRNA of Tephritid fruit flies at different ages
File Name: 16S qPCR Titers.zip
Resource Description: Raw data and R code of 16S rRNA copy numbers associated with medfly and melon fly gut tissues.</p>
</li>
</ul>

Tags: 16s-rrna-gene, ars, data-gov, diptera, insect-gut-metagenome, insects, invasive-species, microbiome, np304, tephritidae
Organization: Department of Agriculture
Data from: A genome-wide association study of Nigerien and Senegalese sorghum germplasm of Exserohilum turcicum, the causal agent of leaf blight

<p dir="ltr">Sorghum supplies the daily calorie needs of millions of inhabitants in Senegal, West Africa. However, <i>Exserohilum </i><i>turcicum</i>, causal agent of leaf blight significantly reduces the crop's productivity and profitability. Data based on a total of 120 sorghum lines (60 lines each from Niger and Senegal) planted in replicated plots in three locations in Senegal, West Africa. The leaf blight incidence and severity were collected by Louis K Prom, Mame Penda Sarr, Cyril Diatta, Coumba Fall, and Clint Magill. Disease incidence was based on the number of plants infected with leaf blight in a row divided by the total number of plants in the same row multiplied by 100. The severity scale 0 to 11 with mid-points, where 1=5.5, 2=15.5, 3=25.5, 4=35.5, 5=45.5, 6=55.5, 7=65.5, 8=75.5, 9=85.5, 10=95.5, and 11=100 previously described by Prom et al. 2023 was used. the dataset was used to perform genome-wide association studies to identify single-nucleotide polymorphisms associated with leaf blight incidence.</p>

Tags: disease-incidence, disease-severity, exserohilum-turcicum, fungi, gwas, leaf-blight, sorghum
Organization: Department of Agriculture
LTAR Upper Mississippi River Basin - St. Paul - Restored Prairie Phenocam

<p>A stationary camera used to track vegetation phenology overlooking a restored native prairie.  This site is located at the Rosemount Research and Outreach Center in Rosemount, Minnesota.  Images are taken every 30 minutes.

A link to the Phenocam's network FAQ: https://phenocam.sr.unh.edu/webcam/faq</p> <div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: GeoData catalog record.</p> <p>File Name: Web Page, url: <a href="https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/7fe0227e-5eeb-43bb-b2e3-1949c0d59f50" target="_blank">https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/7fe0227e-5eeb-43bb-b2e3-1949c0d59f50</a> </p></li></ul>

Tags: ars, biological-resources, corn, cover-crops, data-gov, earth-science-agriculture-agricultural-plant-science, earth-science-biosphere-vegetation, earth-science-biosphere-vegetation-chlorophyll, earth-science-biosphere-vegetation-leaf-characteristics, earth-science-biosphere-vegetation-plant-phenology, np211, prairie, soybeans, vegetation
Organization: Department of Agriculture
The Ogallala Agro-Climate Tool

<p>The Ogallala Agro-Climate Tool is a Visual Basic application that estimates irrigation demand and crop water use over the Ogallala Aquifer region. The application's meteorological database consists of daily precipitation and temperature data from 141 U.S. Historical Climatology Network stations during 1976-2005. From that daily data the program calculates climate and crop evapotranspiration (ETc) statistics over arbitrarily defined periods within summer or winter growing seasons at user-selected latitude-longitude coordinates. The statistics reported include: ETc estimates derived from the FAO-56 single crop coefficient algorithm, probabilities of exceedance of cumulative rainfall, irrigation demand and growing degree days, the probability that minimum and maximum daily temperatures will exceed user-defined temperature thresholds, and the probability of heat stress, cold stress and dry periods of varying duration. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Ogallala Agro-Climate Tool.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=485&modecode=30-96-05-00">https://www.ars.usda.gov/research/software/download/?softwareid=485&modecode=30-96-05-00</a> </p><p>download page</p></li></ul><p></p>

Tags: ars, climatology, data-gov, irrigation-and-water-use, ogallala-aquifer
Organization: Department of Agriculture
Alternative Rotation Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Brookings, South Dakota

<p>Alternative Rotation Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Brookings, South Dakota
Greenhouse gas fluxes and ancillary data are being measured in a 2-yr corn-soybean rotation (business as usual) and a 4- yr corn-pea-winter wheat-soybean rotation (more sustainable).</p> <div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: GeoData catalog record.</p> <p>File Name: Web Page, url: <a href="https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/829740f4-6f6d-4dfc-9e51-b894497aff6b" target="_blank">https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/829740f4-6f6d-4dfc-9e51-b894497aff6b</a> </p></li></ul>

Tags: ars, corn-pea-winter-wheat-soybean-rotation, corn-soybean-rotation, crop-rotation, data-gov, environment, farming, greenhouse-gas-fluxes, np211, np212
Organization: Department of Agriculture
LTAR - Meteorological Stations - R.J. Cook Agronomy Farm - Cook East

<p>USDA-ARS Northwest Sustainable Agroecosystems Research (NSAR) and Washington State University (WSU) established a long-term meteorological and eddy covariance tower in 2017.  </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: GeoData catalog record.</p> <p>File Name: Web Page, url: <a href="https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/ba0fb201-dd3f-439b-be57-25b090730dc7">https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/ba0fb201-dd3f-439b-be57-25b090730dc7</a> </p><p>
</p></li></ul><p></p>

Tags: air-pressure, air-temperature, ars, atmosphere, climate, data-gov, meteorological-data, vegetation, weather, wind-speed
Organization: Department of Agriculture
Nashua Data Access: An agricultural water quality study in Nashua, Iowa

<p>The measured and simulated data for corn and soybean yields, tileflow, N concentration, and N loading by plot, year, treatment, rotation, tillage and N application from 36 1-acre plots located on the Northeast Research and Demonstration Farm near Nashua, Iowa are presented. The measured data were analyzed with the Root Zone Water Quality Model (RZWQM) Version 1.0.2000.830 and summarized in 8 papers in a special issue of <em>Geoderma</em> (Volume 140, No. 3, pages 217-322). The economic returns associated with each plot year were budgeted using the EconDocs software, since improved and released as DevTreks. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Nashua Data Access .</p> <p>File Name: Web Page, url: <a href="https://apps.tucson.ars.ag.gov/nashua/">https://apps.tucson.ars.ag.gov/nashua/</a> </p><p>Web site for the Nashua Project, including links to :</p>
<ul>
<li>graphical presentation of the measured data</li>
<li>climate data</li>
<li>official soil series information about the Clyde, Floyd, Kenyon, and Readlyn soils</li>
<li>interactive Access database of the measured and simulated results</li>
<li>spreadsheet detailing all of the operations used on the research plots</li>
<li>graphical summary of the simulated vs measured results for corn and soybean yields, tileflow, N concentration, and N loading by plot, year, treatment, rotation, tillage and N application method</li>
<li>listing of the RZWQM input files for each plot in each year</li>
<li>information on the RZWQM model and its applications</li>
<li>spreadsheet detailing all of the costs and returns</li>
<li>DevTreks software</li>
<li>bibliography of water quality papers based on the Nashua site</li>
</ul>
<p></p></li></ul><p></p>

Tags: ars, data-gov, economic-returns, northeast-research-and-demonstration-farm
Organization: Department of Agriculture
Data from: Flight burst duration as an indicator of flight ability and physical fitness in two species of Tephritid fruit flies

<p>These data are from a study on a new method to quantify flight ability and physical fitness of individual fruit flies which we term ‘Flight Burst Duration’ (FBD). The method consisted of tethering individual insects by the dorsal thorax using a vacuum and measuring the length of time the insect beats its wings while suspended off a surface. Consecutive measurements with <em>Bactrocera dorsalis</em> Hendel (Dipera: Tephritidae) and <em>Zeugodacus cucurbitae</em> Coquillett (Diptera: Tephritidae) in the same day and across days indicated that a single measurement was sufficient, and that FBD was consistent and repeatable. Insects under stress from starvation displayed shorter FBD over time, and we suggest that the measure also relates to the physical condition or survival fitness of the individual. Though somewhat laborious and timeconsuming, we proposed that FBD can be useful for research studies requiring individual-level phenome data and for obtaining estimates quality and dispersive movement for insects.</p>
<p>Resources in this dataset:</p>
<ul>
<li>
<p>Resource title: Consecutive Burst Assay data
File name: 2017-01_consecutive-data-complete-nal.csv</p>
</li>
<li>
<p>Resource title: Longitudinal and Nutritional Deprivation Test Data
File name: 2023-08_longitudional-nutritional-data-complete-nal.csv</p>
</li>
<li>
<p>Resource title: Metadata
File name: README.txt</p>
</li>
</ul>

Tags: ars, data-gov, dispersion, mass-rearing, np304, quality-control, tephritidae
Organization: Department of Agriculture
LTAR Great Basin Wyoming Big Sage Brush Meteorological Station, Reynolds Creek Experimental Watershed

<p>Near-real time weather records collected at the Wyoming Big sagebrush meteorological site of the Great Basin LTAR. The station data is composited from a meteorological station and a nearby Eddy Covariance station. This site is also the primary meteorological station for the Nancy Gulch sub-watershed of the Reynolds Creek Experimental Watershed and the Wyoming Big sagebrush vegetation zone of the Reynolds Creek Critical Zone Observatory. The site includes precipitation, incoming solar radiation, air temperature, relative humidity, wind speed and direction, snow depth, soil moisture, soil temperature. The records have had preliminary quality assurance filters applied and are considered raw field measurements.</p> <div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: GeoData catalog record.</p> <p>File Name: Web Page, url: <a href="https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/044dff2b-7c03-4980-b4fe-7286b3217adb" target="_blank">https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/044dff2b-7c03-4980-b4fe-7286b3217adb</a> </p><p>
</p></li></ul>

Tags: ars, data-gov, meteorological-data, np211, np215
Organization: Department of Agriculture
Data from: Phenological variation associates with the stability of fruit quality traits in cultivated tetraploid blueberry

<p dir="ltr">Data of twelve fruit quality traits and three phenology-related traits collected in 2020, 2021, 2022, and 2023 seasons from 187 genotypes of southern high bush blueberry established in Poplarville, MS, USA (30.8402°N, 89.5342°W) in a sandy loam soil. Fruit quality data include berry weight, berry size, firmness, pH, total polyphenol, citric acid, malic acid, total acids, D-glucose, D-fructose, total Glucose, and total sugar content. The phenology-related traits include flowering and ripening dates, and fruit development period.</p><p dir="ltr"><br></p>

Tags: blueberry, vaccinium
Organization: Department of Agriculture
Immigration and cyclical bottlenecks: High inbreeding despite high genetic diversity in an oscillating population of the biting midge, Culicoides sonorensis (Diptera: Ceratopogonidae)

<p>These data represent the microsatellite peak calls generated after genotyping the specimens, as well as, the outputs from downstream analyses and the metadata used to construct some of the figures and tables. The microsatellite data can be found in "Shults_2023_peak_calls.xlsx" and contains the identity of each peak scored scored using Geneious v.9.1 software. An "x" represents no peak call at that marker for that individual. These data were used as input for all of the subsequent population genetic analyses. All of the data used to create the tables and figures of the manuscript can be found in "Shults_2023_tables_figs.xlsx".</p>
<p>Resources in this dataset:</p>
<ul>
<li>
<p>Resource Title: Microsatellite peak calls
File Name: Shults_2023_peak_calls.xlsx
Resource Description: Contained in this file are all of the individual specimens (rows) genotype during this project. An "x" represents an uncalled peak for that specific marker.</p>
</li>
<li>
<p>Resource Title: Tables and Figures
File Name: Shults_2023_tables_figs.xlsx
Resource Description: Contained in this file are all of the metadata used to create the tales and figures from the manuscript. Each tab is labeled with the corresponding information and IBT stands for isolation by time.</p>
</li>
</ul>

Tags: ars, culicoides, data-gov, microsatellite, np104, population-genetics
Organization: Department of Agriculture