AndreaBozzo/ceres-open-data-index huggingface dataset:
CottonGen: Cotton Database Resources

<p>CottonGen (<a href="https://www.cottongen.org">https://www.cottongen.org</a>) is a curated and integrated web-based relational database providing access to publicly available genomic, genetic and breeding data to enable basic, translational and applied research in cotton. Built using the open-source Tripal database infrastructure, CottonGen supersedes CottonDB and the Cotton Marker Database, which includes sequences, genetic and physical maps, genotypic and phenotypic markers and polymorphisms, quantitative trait loci (QTLs), pathogens, germplasm collections and trait evaluations, pedigrees, and relevant bibliographic citations, with enhanced tools for easier data sharing, mining, visualization, and data retrieval of cotton research data. CottonGen contains annotated whole genome sequences, unigenes from expressed sequence tags (ESTs), markers, trait loci, genetic maps, genes, taxonomy, germplasm, publications and communication resources for the cotton community. Annotated whole genome sequences of <em>Gossypium raimondii</em> are available with aligned genetic markers and transcripts. These whole genome data can be accessed through genome pages, search tools and GBrowse, a popular genome browser. Most of the published cotton genetic maps can be viewed and compared using CMap, a comparative map viewer, and are searchable via map search tools. Search tools also exist for markers, quantitative trait loci (QTLs), germplasm, publications and trait evaluation data. CottonGen also provides online analysis tools such as NCBI BLAST and Batch BLAST.</p>
<p>This project is funded/supported by Cotton Incorporated, the USDA-ARS Crop Germplasm Research Unit at College Station, TX, the Southern Association of Agricultural Experiment Station Directors, Bayer CropScience, Corteva/Agriscience, Dow/Phytogen, Monsanto, Washington State University, and NRSP10. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Website Pointer for CottonGen.</p> <p>File Name: Web Page, url: <a href="https://www.cottongen.org/">https://www.cottongen.org/</a> </p><p>Genomic, Genetic and Breeding Resources for Cotton Research Discovery and Crop Improvement organized by :</p>
<ul>
<li>Species (Gossypium arboreum, barbadense, herbaceum, hirsutum, raimondii, others), </li>
<li>Data (Contributors, Download, Submission, Community Projects, Archives, Cotton Trait Ontology, Nomenclatures, and links to Variety Testing Data and NCBISRA Datasets), </li>
<li>Search options (Colleague, Genes and Transcripts, Genotype, Germplasm, Map, Markers, Publications, QTLs, Sequences, Trait Evaluation, MegaSearch), </li>
<li>Tools (BIMS, BLAST+, CottonCyc, JBrowse, Map Viewer, Primer3, Sequence Retrieval, Synteny Viewer), </li>
<li>International Cotton Genome Initiative (ICGI), and </li>
<li>Help sources (User manual, FAQs).</li>
</ul>
<p>Also provides Quick Start links for Major Species and Tools.</p></li></ul><p></p>

Tags: ars, cmap, cotton-marker-database, cottondb, cottongen, data-gov, gbrowse, ncbi-blast, np301, online-database, tripal-database
Organization: Department of Agriculture
Data from:  Crop Sequence and Nitrogen Fertilization Effects on Soil Properties in the Western Corn Belt

<p dir="ltr">Understanding long-term management effects on soil properties is necessary to determine the sustainability of cropping systems. Documentation of soil property responses to corn-based cropping systems in the Western Corn Belt, however, is limited. A study was conducted near Mead, Nebraska to document the effects of four crop sequences (continuous corn, corn-soybean, corn-oat+clover-grain sorghum-soybean, corn-soybean-grain sorghum-oat+clover) and three nitrogen (N) rates (zero, low, high) on a suite of soil properties. At the time of sampling (spring 1999), treatments had been in place for 16 years. Soil samples were collected from two depths using a 1.8 cm step-down probe: 0-7.6 cm and 0-30.5 cm. Soil pH and electrical conductivity was estimated from a 1:1 soil-water mixture. Soil nitrate-N was measured using 1:10 soil-KCl extracts and the cadmium reduction method. Extractable P was determined by the Bray P-1 method. Particulate organic matter was determined by weight loss-on-ignition. Total carbon and N were determined by dry combustion. Potentially mineralizable N was determined by anerobic incubation, while microbial biomass was estimated by microwave irradiation. Soils data were used to identify associations with 16-year averages of grain and stover yield, grain and stover N uptake, and post-harvest soil nitrate-N. Data may be used to understand soil responses to corn-based cropping systems under rainfed conditions in a humid continental climate. Applicable USDA soil types include Yutan, Tomek, and Fillmore.</p>

Tags: corn-production, crop-rotation, fertilization-rate, long-term-research
Organization: Department of Agriculture
Water chemistry data for three agricultural ponds in the southern Coastal Plain of Georgia, USA

<p dir="ltr">Ponds used to capture and store water for irrigation are a common feature in agricultural landscapes of the southern Coastal Plain of Georgia, USA. However, not much is known about the biogeochemistry of these ponds. As part of a project describing water quality in irrigation ponds of agricultural landscapes, pond water samples were collected from October 2021 to October 2023 at three ponds in Georgia, USA. Two ponds were located on a farm near Ty Ty, GA (Ty Ty Cooperator Farm, TCF) and one pond was located on a farm near Sumner, GA (Sumner Cooperator Farm, SCF; 31.614247, -83.710532). The two ponds on the TCF are identified as TCF-North (TCF-N; 31.5139853, -83.6177578) and TCF-South (TCF-S; 31.5086980, -83.6167862). The TCF is a rotational cropland while the SCF is an integrated crop-livestock farm. At each pond, water samples were collected at various locations along the edges (littoral sites) and in the center (limnetic sites). At the limnetic sites, samples were collected at the water surface and at 1 m depth. Water samples were collected in 500 mL pre-washed plastic bottles using a peristaltic pump and kept on ice until returned to the laboratory. The samples were filtered (934-AH, Whatman) and the filtrate was split for various chemical analyses including dissolved nutrients (ammonia-N, nitrate-N, nitrite-N, orthophosphate-P, and chloride) using flow injection analysis with colorimetric detection, dissolved micro- and macronutrients (aluminum, arsenic, boron, calcium, iron, potassium, magnesium, manganese, molybdenum, sodium, phosphorus, sulfur, silica, and vanadium) using Inductively Coupled Plasma with Optical Emission Spectroscopy (ICP-OES), and optical characteristics of the dissolved organic matter using UV-Visible and Fluorescence spectroscopy.</p>

Tags: dissolved-nutrients, dissolved-organic-matter, irrigation-ponds, water-chemistry
Organization: Department of Agriculture
Data from: The efficacy of inactivated vaccine against H5 clade 2.3.4.4b highly pathogenic avian influenza virus in turkeys

<p dir="ltr">The global outbreak of clade 2.3.4.4b H5N1 highly pathogenic avian influenza (HPAI) virus has caused tremendous losses in poultry. Although turkeys are a smaller sector in poultry production compared to chickens, they tend to be affected more severely by HPAI virus because they can usually be infected with a lower dose of influenza A virus than chickens (i.e., they are more susceptible). Exposure to non-replicating proteins may help control HPAI, however data with turkeys are somewhat limited regarding how well they work and approaches to modifying surveillance have not been developed. Here, an H5N9 non-replicating protein comprised of a clade 2.3.4.4b H5 hemagglutinin from A/turkey/Indiana/22-003707-003/2022 (TK/IN/22) and a North American wild bird lineage N9 was evaluated in commercial broad breasted white turkeys by challenge to live virus. Turkeys were divided into three groups, where each group was exposed to the non-replicating protein once at 3 (3wk), 7 (7wk), or 9 (9wk) weeks of age. All birds were challenged at 10 weeks of age with TK/IN/22 HPAIV. There was 100% survival in all groups except the sham exposure group which had 100% mortality. A significant decrease in viral shedding was observed in all exposed groups compared to the shams, although the 9wk group shed significantly higher quantities by the cloacal route at seven days post challenge (DPC) compared to the 3wk group. The neuraminidase inhibition-enzyme linked lectin assay (NI-ELLA) was used as a serological test that was able to detect antibody in birds that had been infected after exposure and challenge based on antibodies to the NA protein of the challenge virus (N1 NA) in serum collected 7, 10 and 14DPC. Between 50 and 90% of turkeys, depending on age at exposure, were positive by NI-ELLA at 7DPC and 100% were positive at 14DPC regardless of age at exposure.</p>

Tags: clade-2-3-4-4b-h5-influenza, differentiating-infected-from-vaccinated-animals-diva, disease-control-poultry, highly-pathogenic-avian-influenza, inactivated-influenza-vaccine, poultry-vaccination-program, poultry-vaccine, turkeys
Organization: Department of Agriculture
Data from: Vegetation index-based partitioning of evapotranspiration is deficient in grazed systems

<p>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 three wheat sites. Three wheat sites had different grazing treatments. For example, Site 1 was Grain-only and Graze-grain wheat for the 2016-17 and 2017-18 growing seasons, respectively. Site 2 was Grain-only wheat for the 2017-18 growing season. Site 3 was Graze-grain and Graze-out wheat for the 2016-17 and 2017-18 growing seasons, respectively. </p>
<p>The grain-only wheat system is a single purpose to produce wheat grains only. Graze-grain wheat system has a dual purpose as it serves as a pasture for grazing cattle from November to February and is used to produce wheat grains later. Graze-out wheat system is also a single purpose crop that is grazed by the cattle for the entire season to solely serve as a pasture.  </p>
<p>FVS method performed ET partitioning using the high frequency (10 Hz) data collected from Eddy Covariance Flux stations, located near the middle of each field. The high-frequency data were also processed using the EddyPro software to get good quality estimates of different fluxes at 30-minute intervals. The processed 30-min data were used by TEA and uWUE methods for ET partitioning. Ancillary hydro-meteorological variables including net radiation, air temperature, soil water content, relative humidity, and others, also have been included in this dataset.
The study sites were located at the United States Department of Agriculture, Agricultural Research Service (USDA-ARS), Grazinglands Research Laboratory, El Reno, Oklahoma. All sites were rainfed. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: FVS output and other met data and site info.</p> <p>File Name: FVS_output_and_other_met_data_and_site_info.xlsx</p><p>Resource Description: Output of FVS model along with corresponding meteorological data and site metadata.</p></li><br><li><p>Resource Title: TEA output.</p> <p>File Name: TEA_output.xlsx</p><p>Resource Description: Out from TEA model along with site metadata.</p></li><br><li><p>Resource Title: WUE output.</p> <p>File Name: uWUE_output.xlsx</p><p>Resource Description: Output of WUE model run along with site metadata.</p></li></ul><p></p>

Tags: agroecosystems-environment-water-evapotranspiration, ars, data-gov, eddy-covariance-flux, evapotranspiration, evapotranspiration-partitioning, np215, wue-algorithms
Organization: Department of Agriculture
Global Warming Potential Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Mandan, North Dakota

<p>Global Warming Potential Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Mandan, North Dakota
No long-term evaluation of net global warming potential (GWP) for grassland ecosystems in the northern Great Plains (NGP) of North America has been reported. Given this need, we sought to determine net GWP for three grazing management systems located within the NGP. Grazing management systems included two native vegetation pastures (moderately grazed pasture [MGP], heavily grazed pasture [HGP]) and a heavily grazed crested wheatgrass [Agropyron desertorum (Fisch. ex. Link) Schult.] pasture (CWP) near Mandan, ND. Factors evaluated for their contribution to GWP included (i) CO2 emissions associated with N fertilizer production and application, (ii) literature-derived estimates of CH4 production for enteric fermentation, (iii) change in soil organic carbon (SOC) over 44 yr using archived soil samples, and (iv) soil–atmosphere N2O and CH4 fl uxes over 3 yr using static chamber methodology.  Analysis of SOC indicated all pastures to be significant sinks for SOC, with sequestration rates ranging from 0.39 to 0.46 Mg C ha−1 yr−1. All pastures were minor sinks for CH4 (<2.0 kg CH4–C ha−1 yr−1). Greater N inputs within CWP contributed to annual N2O emission nearly threefold greater than HGP and MGP. Due to diff erences in stocking rate, CH4 production from enteric fermentation was nearly threefold less in MGP than CWP and HGP. When factors contributing to net GWP were summed, HGP and MGP were found to serve as net CO2equiv. sinks, while CWP was a net CO2equiv. source. Values for GWP and GHG intensity, however, indicated net reductions in GHG emissions can be most eff ectively achieved through moderate stocking rates on native vegetation in the NGP.</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/0bc3b108-4663-47da-b9d8-918554c27b31" target="_blank">https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/0bc3b108-4663-47da-b9d8-918554c27b31</a> </p></li></ul>

Tags: ars, climate-change, data-gov, environment, farming, grazing, greenhouse-gas, methane, nitrous-oxide, np211, np212, pastures, soil
Organization: Department of Agriculture
Agricultural Research Service (ARS) Corn, Ames, Iowa

<p>Four-year rainfed corn field experiment in Ames, Iowa. This dataset is part of an Agricultural Model Intercomparison and Improvement Project (AgMIP) data node maintained at National Agricultural Library for USDA-AgMIP data. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Corn Dataset.</p> <p>File Name: agmip_download.zip</p><p>Resource Description: Direct download, zipped aceb data format file at <a href="https://api.agmip.org/cropsitedb/2/dataset/53616eb8-df80-45dd-9c45-d7d81b8e1181">https://api.agmip.org/cropsitedb/2/dataset/53616eb8-df80-45dd-9c45-d7d81b8e1181</a></p></li></ul><p></p>

Tags: agmip, ames, ars, data-gov, np216
Organization: Department of Agriculture
Data from: Dataset of de novo assembly and functional annotation of the transcriptome of blueberry (Vaccinium spp.)

<p>Blueberry is an economically important berry crop. Both production and consumption of blueberries have increased sharply worldwide in recent years at least partly due to their known health benefits. The development of improved genomic resources for blueberry, such as a well-assembled genome and transcriptome, could accelerate breeding through genomic-assisted approaches. To enrich available transcriptome data and identify genes potentially involved in fruit quality, RNA sequencing was performed on fruit tissue from two northern-adapted hybrid blueberry breeding populations. RNA-seq was carried out using the Illumina HiSeqTM 2500 platform. Because of the absence of a reference-grade genome for blueberry, a transcriptome was de novo assembled from this RNA-seq data and other publicly available transcriptome data from blueberry downloaded from the National Center for Biotechnology Information (NCBI) Short Read Archive (SRA) using Trinity. After removing redundancy, this resulted in a dataset of 91,861 blueberry unigenes. This unigene dataset was functionally annotated using the NCBI-Nr protein database. All raw reads from the breeding populations were deposited in the NCBI SRA with accession numbers SRR6281886, SRR6281887, SRR6281888, and SRR6281889. The de novo transcriptome assembly was deposited at NCBI Transcriptome Shotgun Assembly (TSA) database with accession number GGAB00000000. These data will provide real expression evidence for the blueberry genome gene prediction and gene functional annotation and a reference transcriptome for future gene expression studies involving blueberry fruit. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Dataset of de novo assembly and functional annotation of the transcriptome of blueberry (Vaccinium spp.).</p> <p>File Name: Web Page, url: <a href="https://doi.org/10.1016/j.dib.2019.104390">https://doi.org/10.1016/j.dib.2019.104390</a> </p></li></ul><p></p>

Tags: ars, data-gov, northern-adapted-hybrid, np301
Organization: Department of Agriculture
Data and code from: Establishment of southern highbush blueberry cultivars and suppression of Phytophthora root rot using cover crop and soil amendment treatments

<p dir="ltr">This dataset contains all data and R statistical software code needed to reproduce the analyses presented in the paper:</p><p dir="ltr">Smith, B.J., Stafne, E.T. & Read, Q.D. (2025). Establishment of Southern Highbush Blueberry Cultivars and Suppression of Phytophthora Root Rot Using Cover Crop and Soil Amendment Treatments. <i>PhytoFrontiers</i>. https://doi.org/10.1094/PHYTOFR-09-24-0096-R</p><h2>Summary</h2><p dir="ltr">Phytophthora root rot is a major disease of blueberry that often relies on cultural practices including the addition of soil amendments for disease management. We evaluated the effect of three cover crops on the establishment and growth of southern highbush blueberry (SHB) plants and their ability to suppress Phytophthora root rot infection of plants. This dataset includes data from soil chemical analyses (Table 1), soil pH and electrical conductivity measurements (Table 2), plant leaf, flower, crop load, and fruit ratings (Table 3), plant vigor rating and survival rate (Table 3), stem count, length, weight, and survival (Table 4), root length, diameter, and weight (Table 5). In addition, seedling weight and count data from a blueberry seedling assay (Table 6) and a lupine seedling assay (Table 7) are included.</p><p dir="ltr">The associated RMarkdown notebook includes statistical models to analyze all datasets presented here. Linear mixed models, generalized linear mixed models, generalized additive models, and cumulative logistic mixed models are fit where appropriate. A combination of Bayesian and frequentist methods are used; some of the frequentist models include Bayesian-style prior distributions on fixed effects. Models are described in more detail in the notebook.</p><h2>Files included</h2><ul><li>Smith BB cover crop 7 data sets 10.9.24.xlsx: Excel spreadsheet with seven tabs containing all raw data and explanation of contents</li><li>blueberry_covercrop_analysis.Rmd: RMarkdown notebook containing all R code for statistical analysis presented in manuscript, with text explanations</li><li>blueberry_covercrop_analysis.html: HTML rendered output of Rmd notebook</li></ul><h2>Version history</h2><p dir="ltr">V2 replaces blueberry_covercrop_analysis.Rmd and blueberry_covercrop_analysis.html with new versions. This corrects an error in the statistical analysis code from the previous version.</p>

Tags: blueberry, cover-crop, electrical-conductivity, highbush-blueberry, ph, phytophthora-cinnamomi, plant-disease, plant-disease-control, root-disease, soil-amendment
Organization: Department of Agriculture
USDA Database for the Isoflavone Content of Selected Foods, Release 2.1 (November 2015)

<p>This database contains data on the isoflavone content of 560 food items.  Isoflavones included in the database are daidzein, genistein, glycitein and total isoflavones.  Other phytoestrogens (coumestrol, biochanin A, and formononetin) are included as a separate table in the PDF report and in the database.</p>
<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: READ ME - USDA Database for the Isoflavone Content of Selected Foods, Release 2.1.</p> <p>File Name: Isoflav_R2-1.pdf</p><p>Resource Description: Information about the release history, documentation, format of the database, sources of data, and references cited in the data.</p><p>Resource Software Recommended: Adobe Acrobat Reader,url: <a href="http://www.adobe.com/prodindex/acrobat/readstep.html" target="_blank">http://www.adobe.com/prodindex/acrobat/readstep.html</a> </p></li><br><li><p>Resource Title: Data Dictionary.</p> <p>File Name: Isoflav_R21_DD.pdf</p></li><br><li><p>Resource Title:  Isoflav_R2-1.accdb .</p> <p>File Name: Isoflav_R2-1.zip</p><p>Resource Description: This file contains the Isoflavone Database imported into a MS Access database, version 2007 or later. The file structure is the same as that of the USDA National Nutrient Database for Standard Reference.
</p></li></ul>

Tags: ars, biochanin-a, coumestrol, daidzein, data-gov, food-components, formononetin, genistein, glcyitein, isoflavone, np107, phytoestrogens
Organization: Department of Agriculture
Data from: Use of long-read sequencing simulators to assess real-world applications for food safety

<p>Shiga toxin-producing <em>Escherichia coli</em> (STEC) and <em>Listeria monocytogenes</em> are responsible for severe foodborne illnesses in the United States. Current identification methods require at least four days to identify STEC and six days for <em>L. monocytogenes</em>. Adoption of long-read, whole genome sequencing for testing could significantly reduce the time needed for identification, but method development costs are high. Therefore, the goal of this project was to use NanoSim-H software to simulate Oxford Nanopore sequencing reads to assess the feasibility of sequencing-based foodborne pathogen detection and guide experimental design. Sequencing reads were simulated for STEC, <em>L. monocytogenes</em>, and a 1:1 combination of STEC and <em>Bos taurus</em> genomes using NanoSim-H. This dataset includes all of the simulated reads generated by the project in fasta format. This dataset can be analyzed bioinformatically or used to test bioinformatic pipelines. </p>

Tags: ars, data-gov, escherichia-coli-o157-h7, listeria-monocytogenes, long-read-sequencing, minion, np108, sequencing-simulation
Organization: Department of Agriculture