AndreaBozzo/ceres-open-data-index huggingface dataset:
Data and code from: Comparison of in-field and laboratory-based phenotyping methods for evaluation of aflatoxin accumulation in maize inbred lines

<p dir="ltr">This dataset contains all data and R code, in RMarkdown notebook format, needed to reproduce all statistical analysis, figures, and tables in the manuscript:</p><p dir="ltr">Jeffers, D., J. S. Smith, E. D. Womack, Q. D. Read, and G. L. Windham. 2024. Comparison of in-field and laboratory-based phenotyping methods for evaluation of aflatoxin accumulation in maize inbred lines. <i>Plant Disease</i>. (citation to be updated upon final acceptance of MS)</p><p dir="ltr">There is a critical need to quickly and reliably identify corn genotypes that are resistant to accumulating aflatoxin in their kernels. We compared three methods of determining how resistant different corn genotypes are to aflatoxin accumulation: a field-based assay (side-needle inoculation) and two different lab-based assays (wounding and non-wounding kernel screening assays; KSA). In this data object, we present the data from the lab and field assays, statistical models that are fit to the data, procedures for comparing model fit of different variants of the model, and model predictions. This includes how reliably each assay identifies resistant and susceptible check varieties, and how well correlated the assay methods are with one another. Statistical analyses are done using R software, including Bayesian models fit with Stan software.</p><p dir="ltr">The following files are included:</p><ul><li><b>ksa_analysis_revised.Rmd</b>: RMarkdown notebook with all code needed to reproduce analyses and create figures and tables in manuscript</li><li><b>ksa_analysis_revised.html</b>: HTML rendered output of notebook</li><li><b>step1_ksa.tsv</b>: tab-separated data file with data from the lab assay. Columns include sample ID, genotype ID and entry code, year, treatment (wound or no-wound), subsample ID, replicate ID, aflatoxin concentration (in units of ng/g), logarithm of aflatoxin concentration, and a column indicating genotypes that are susceptible or resistant checks</li><li><b>step1_ksa_field.tsv</b>: tab-separated data file with data from the field assay. Columns similar to the lab assay data file with an additional column for row in which the sample was planted.</li><li><b>ksa_cov_mod.tsv</b>: tab-separated data file with secondary infection covariate data from the lab assay. Columns similar to the lab assay data file with columns for secondary Asp, Fus, and NI infections and their logarithms.</li><li><b>brmfits.zip</b>: zip archive with 12 .rds files. These are model output files for the Bayesian mixed effect models presented in the MS that were fitted using the R function brm(). You may download these to reproduce output without having to compile and run the models yourself.</li></ul><p dir="ltr">The three .tsv data files should be placed in a subdirectory called "data" in the same directory where the .Rmd notebook is located.</p>

Tags: aflatoxin, aspergillus-flavus, host-plant-resistance, kernel-screening-assay-ksa, maize-zea-mays, phenotyping
Organization: Department of Agriculture
Data from: Annual Compensation for Floral Herbivory by an Iterocarpic Thistle

<p>We tested the extent to which reproductive effort by an iterocarpic native thistle <em>Cirsium undulatum</em> provided within-season tolerance for insect floral herbivory through plant response to apical damage. We imposed apical damage and used insecticide to reduce herbivory damage to manipulate plant response and potential outcomes in reproductive compensation. Data include: 1) detailed size and fecundity data per plant individual under different treatments; and 2) insect damage score and seeds produced per individual flower head. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Wavyleaf thistle individual plant data.</p> <p>File Name: West_2021 Wavyleaf plant data.csv</p><p>Resource Description: Includes detailed information on whole plant morphology (e.g., number of branches and flowerheads), fecundity, and insect damage estimates.</p></li><br><li><p>Resource Title: Wavyleaf thistle per flowerhead data.</p> <p>File Name: West_2021 Wavyleaf flowerhead data.csv</p><p>Resource Description: Includes visual damage score and seed production estimate from individual flowerhead dissections.</p></li><br><li><p>Resource Title: Wavyleaf thistle Plant and Flowerhead data description.</p> <p>File Name: West_2021 Wavyleaf dataset.txt</p><p>Resource Description: Explanation of variables and information on Wavyleaf thistle data files</p></li></ul><p></p>

Tags: apical-dominance, ars, cirsium-undulatum, data-gov, insect-herbivory, np304, plant-tolerance, polycarp, predispersal-seed-predation
Organization: Department of Agriculture
Halyomorpha halys Official Gene Set v1.2

<p>This dataset presents the <em>Halyomorpha halys</em> Official Gene Set (OGS) v1.2. OGSv1.2 is an update of <em>Halyomorpha halys</em> OGSv1.1 (<a href="https://doi.org/10.15482/USDA.ADC/1504240">https://doi.org/10.15482/USDA.ADC/1504240</a>) to the coordinates of genome assembly GCA_000696795.3 (<a href="https://www.ncbi.nlm.nih.gov/assembly/GCA_000696795.3">https://www.ncbi.nlm.nih.gov/assembly/GCA_000696795.3</a>) using <a href="https://github.com/NAL-i5K/coordinates_conversion/">https://github.com/NAL-i5K/coordinates_conversion/</a>. </p>
<p>The original OGSv1.0 is an integration of automatic gene predictions from NCBI's eukaryotic annotation pipeline, NCBI Halyomorpha halys Annotation Release 100 (<a href="https://www.ncbi.nlm.nih.gov/genome/annotation_euk/Halyomorpha_halys/100/">https://www.ncbi.nlm.nih.gov/genome/annotation_euk/Halyomorpha_halys/100/</a>; ftp://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/000/696/795/GCF_000696795.1_Hhal_1.0), with manual annotations by the research community (performed via the Apollo manual curation software, <a href="http://genomearchitect.org/">http://genomearchitect.org/</a>). Manual annotations performed by the community were downloaded from Apollo, QC'd, and merged with NCBI Halyomorpha halys Annotation Release 100 using the GFF3toolkit software (<a href="https://github.com/NAL-i5K/GFF3toolkit/releases/tag/v1.4.4">https://github.com/NAL-i5K/GFF3toolkit/releases/tag/v1.4.4</a>). The resulting merged dataset was formatted for ingest into the i5k Workspace and GenBank databases, resulting in <em>Halyomorpha halys</em> Official Gene Set (OGS) v1.0. </p>
<p>Halyomorpha Official Gene Set halhal_OGSv1.1 is a minor update of halhal_OGSv1.0: Alias attributes were added to all manually annotated cathepsin models; six models from contaminated scaffolds were removed; and notes were added to 3 models located on possibly contaminated scaffolds. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Halymorpha halys Official Gene Set OGSv1.2.</p> <p>File Name: halhal_OGSv1.2.tar.gz</p><p>Resource Description: The attached tar.gz archive (halhal_OGSv1.2.tar.gz) contains the following files:</p>
<p>halhal_OGSv1.2.gff. Gff3 of all gene predictions of Halymorpha halys genome annotations OGSv1.2
halhal_OGSv1.2_CDS.fa. CDS sequences of Halymorpha halys genome annotations OGSv1.2
halhal_OGSv1.2_pep.fa. Amino acid sequences of Halymorpha halys genome annotations OGSv1.2
halhal_OGSv1.2_trans.fa. Transcript sequences of Halymorpha halys genome annotations OGSv1.2
readme. Readme file describing Halymorpha halys genome annotations OGSv1.2</p>
<p></p></li></ul><p></p>

Tags: ars, data-gov, genome-annotation, genome-assembly, halyomorpha-halys, sequence-analysis
Organization: Department of Agriculture
Effects of increasing supplementation rates of extruded distillers’ grain cubes on stocker steers production grazing native range in Bessie, OK and Fort Supply, OK during the summer months in 2021 and 2022

<p dir="ltr">The objectives of this study were to determine the response curve of increasing supplementation rate with extruded distillers’ grains (DDG) cubes for animal performance and supplemental efficiency by steers grazing midgrass prairie in western Oklahoma. A 2-year trial was conducted at the Oklahoma Agricultural Experiment Station, Marvin Klemme Range Research Station (Klemme), Bessie, Oklahoma and the USDA-ARS, Southern Plains Experimental Range (SPER), Ft. Supply, Oklahoma, both in western Oklahoma during the summers of 2021 and 2022. At Klemme, steers (n = 133 Yr 1, BW = 247 ± 24.5 kg; Yr 2, n = 134, BW = 264 ± 29.1 kg) were allocated to 6 pastures in Yr 1 and 7 pastures in Yr 2 which were assigned to three daily supplementation rates of DDG cubes: 1) Negative Control (NC)- no supplementation; 2) Low Supplement (LS) - 0.91 kg/steer and 3) Medium Supplementation (MS) – 1.82 kg/steer. At Klemme, steers were stocked at 2.0 ha/steer in yr 1 and 2.8 ha/steer in yr 2. At SPER steers (n=119 each year; Yr 1, BW = 295 ± 28.8 kg; Yr 2, BW = 294 ± 25.7 kg) were allocated to 12 pastures stocked at 2.0 ha/steer with pastures assigned to: 1) NC; 2) LS; 3) MS and 4) High Supplement – daily supplementation rate of 2.72 kg/steer.</p>

Tags: native-range, stocker-steers, supplementation
Organization: Department of Agriculture
ACRE Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in West Lafayette, Indiana

<p>ACRE Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in West Lafayette, Indiana
In-field measurements of direct soil greenhouse gas (GHG) emissions provide critical data for quantifying the net energy efficiency and economic feasibility of crop residue based bioenergy production systems. A major challenge to such assessments has been the paucity of field studies addressing the effects of crop residue removal and associated best practices for soil management (i.e., conservation tillage) on soil emissions of carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4). This regional survey summarizes soil GHG emissions from nine maize production systems evaluating different levels of corn stover removal under conventional or conservation tillage management across the US Corn Belt. Cumulative growing season soil emissions of CO2, N2O, and/ or CH4 were measured for 2–5 years (2008–2012) at these various sites using a standardized static vented chamber technique as part of the USDA-ARS’s Resilient Economic Agricultural Practices (REAP) regional partnership. Cumulative soil GHG emissions during the growing season varied widely across sites, by management, and by year. Overall, corn stover removal decreased soil total CO2 and N2O emissions by -4 and -7 %, respectively, relative to no removal. No management treatments affected soil CH4 fluxes.When aggregated to total GHG emissions (Mg CO2eq ha-1) across all sites and years, corn stover removal decreased growing season soil emissions by -5±1 % (mean±se) and ranged from -36 % to 54 % (n=50). Lower GHG emissions in stover removal treatments were attributed to decreased C and N inputs into soils, as well as possible microclimatic differences associated with changes in soil cover. High levels of spatial and temporal variabilities in direct GHG emissions highlighted the importance of site-specific management and environmental conditions on the dynamics of GHG emissions from agricultural soils.</p> <div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: West Lafayette, IN ACRE Study (INWLACRE) CSV data.</p> <p>File Name: INWLACRE_csv_data.zip</p><p>Resource Description: CSV format data on Experimental Units, Field Sites, Greenhouse Gas Flux, Harvest Fraction, Residue Management, Soil Biology, Soil Chemistry, Soil Physics, Amendments, Growth Stages, Planting, Tillage, Persons, Treatments, Weather Daily, Weather Station.</p></li></ul>

Tags: ars, data-gov, environment, farming, iso-metadata, np211, np212
Organization: Department of Agriculture
Shortgrass Steppe for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Nunn, Colorado

<p>Shortgrass Steppe for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Nunn, Colorado
Cattle play a major role in nutrient cycling of grassland ecosystems through biomass removal and excrement deposition (urine and feces).  We studied the effects of cattle excrement patches (urine at 430 and feces at 940 kg N ha-1) on nitrous oxide (N2O) and methane (CH4) fluxes using semi-static chambers on cool-season (C3), Bozoisky-select (*Psathyrostachys juncea*) pasture, and warm-season (C4)-dominated native rangeland of the shortgrass steppe (SGS) in northeastern Colorado.  Nitrous oxide emission factors (EF; i.e., percent of added N emitted as N2O-N) did not differ between urine and feces on the C4-dominated native rangeland (0.11 and 0.10%) and C3 pasture (0.13 and 0.10%).  These EFs are substantially less than the Intergovernmental Panel on Climate Change (IPCC) Tier 1 Default EF (2%) for manure deposited on pasture, indicating that during dry years the IPCC Tier 1 Default EF would result in a significant overestimation of emissions from excrement patches deposited on SGS C4-dominated native rangeland and C3 pasture.  Over the first year of the study (19 June 2012 to 18 June 2013), cumulative CH4 uptake was 38% greater for urine (-1.49 vs. -1.08 kg CH4-C ha-1) and 28% greater for control plots (-2.09 vs. -1.63 kg CH4-C ha-1) on C4-dominated native rangeland compared to C3 pasture.  In contrast, feces patches were net sources of CH4 with emissions from the C3 pasture (0.64 kg CH4-C ha-1) 113% greater than the C4-dominated native rangeland (0.30 kg CH4-C ha-1).  Conversion of C4-dominated native rangeland to C3 pasture can have short and long term effects on CH4 uptake; therefore consideration should be taken before implementing this management practice.</p> <div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Nunn, CO Shortgrass Steppe (CONUNRBS) CSV data.</p> <p>File Name: CONUNRBS_csv_data.zip</p><p>Resource Description: CSV format data on Experimental Units, Field Sites, Greenhouse Gas Flux, Soil Chemistry, Soil Physics, Amendments, Planting, Persons, Treatments, Weather Daily, Weather Station.</p></li></ul>

Tags: ars, data-gov, environment, farming, iso-metadata, np211, np212
Organization: Department of Agriculture
Gulf Atlantic Coastal Plain LTAR Dataset: NFARM, Inorganic N, & C Production, 2016-2018

<p>In situ denitrification rates in intact soil cores from the Gulf Atlantic Coastal Plain (GACP) LTAR site in GA quantified by directly measuring dinitrogen (N2) and nitrous oxide (N2O) production via the Nitrogen-Free Air Recirculation Method (N-FARM) from 2016-2018. 10-day laboratory incubations provided estimates of ancillary soil data, including microbial respiration and potential net N mineralization and nitrification. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Gulf Atlantic Coastal Plain Data Dictionary.</p> <p>File Name: Gulf Atlantic Coastal Plain Data Dictionary.csv</p><p>Resource Description: Data Dictionary for GACP dataset.</p></li><br><li><p>Resource Title: Gulf Atlantic Coastal Plain Metadata.</p> <p>File Name: Gulf Atlantic Coastal Plain Metadata.csv</p><p>Resource Description: Metadata for GACP dataset.</p></li><br><li><p>Resource Title: Gulf Atlantic Coastal Plain Dataset.</p> <p>File Name: Gulf Atlantic Coastal Plain Dataset.csv</p><p>Resource Description: GACP Dataset.</p></li></ul><p></p>

Tags: ammonium, ars, carbon-dioxide, data-gov, deep-soil, denitrification, dinitrogen, ecosystems, gulf-atlantic-coastal-plain-ltar, hot-moment, hot-spot, laboratory-incubation, ltar, mineralization, nitrate, nitrification, nitrogen, nitrous-oxide-flux, respiration, soil, soil-depths, surface-soil, usda-long-term-agricultural-research-ltar-network
Organization: Department of Agriculture
Data from: A global assembly of landrace oat (<i>Avena sativa</i> L.) accessions is a discovery resource for adaptive variation, association mapping, and trait deployment

<p>Oat Landrace Diversity (OLD) Panel phenotypes, genotypes, and metadata from: Rahman et al. (2024) "A global assembly of landrace oat (<em>Avena sativa</em> L.) accessions is a discovery resource for adaptive variation, association mapping, and trait deployment".</p>
<p><strong>"File S1"</strong> and <strong>"File S2"</strong> include population metadata and phenotypic (environmental) data used in association mapping, of which mapping results are listed in <strong>"File S3"</strong>.</p>
<p><strong>"Rahman_et_al_2024_Metadata.geojson"</strong> is geographical information of OLD Panel accessions surveyed in this study.</p>
<p><strong>"SBATCH_RUN_nsgc_deepvariant_glsnexus.sh"</strong> and <strong>"RUN_nsgc_deepvariant_glsnexus.sh"</strong> are scripts for variant calling and filtering in SciNet clusters from GBS alignments. IMPORTANT: Do not pull containers in $HOME directory - put them in the main path (for use in SciNet clusters). Google DeepVariant - generates "deepvariant_1.6.0.sif" (RUN: singularity pull docker://google/deepvariant:1.6.0); GLNexus - generates "glnexus_v1.4.1.sif" (RUN: singularity pull docker://google/glnexus:1.4.1). <strong>"DeepVariantWGS.yml"</strong> is the config file for running GLNexus.</p>
<p><strong>"nsgc.gdv.gln.cohort.clean.maf01maxmiss75diploid.beagle_sorted_filt.gt.vcf"</strong> is the final genotype file described in the study.</p>

Tags: adaptation, climate-change, founder-population, functional-traits, gwas, landrace, oats, qtl
Organization: Department of Agriculture
PhenoCam images from ARSOPE3LTAR site, Beltsville Agricultural Research Center, Maryland, USA since 2017

<p>This data set consists of repeat digital imagery from a tower-mounted digital camera (hereafter, PhenoCam) maintained by the USDA-ARS Hydrology Remote Sensing Laboratory (HRSL) in the Lower Chesapeake Bay (LCB) watershed. HRSL is a member of the PhenoCam network, which has as its mission to serve as a long-term, continental-scale, phenological observatory. Imagery is uploaded to the PhenoCam server every 30 minutes. The archived images provide a permanent record that can be visually-inspected to determine the phenological state of the vegetation at any point in time. Vegetation greenness metrics (e.g., GCC) derived from the ratio of the green color band to sum of red, green, and blue color bands serve as proxies for vegetation greenness. Greenness metrics can be extracted from the images using simple image processing methods in 1-day or 3-day increments.</p>
<p>This dataset is available to the public and may be freely downloaded. Please keep the designated Contact person informed of any plans to use the dataset. Consultation or collaboration with the original investigators is strongly encouraged. Publications and data products that make use of the dataset must include proper acknowledgement.</p>
<p>The development of PhenoCam has been supported by multiple entities. Those include the Northeastern States Research Cooperative, NSF’s Macrosystems Biology program (award EF-1065029), DOE’s Regional and Global Climate Modeling program (award DE-SC0016011), the US National Park Service Inventory and Monitoring Program, the USA National Phenology Network (grant number G10AP00129 from the United States Geological Survey), and is currently supported by the Department of Agriculture (USDA) Agricultural Research Service.</p>
<p>This research was a contribution from the Long-Term Agroecosystem Research (LTAR) network. LTAR is supported by the United States Department of Agriculture (USDA) Agricultural Research Service.</p>

Tags: ars, beltsville, corn, data-gov, digital-image, long-term-monitoring-sites, ltar, np211, np212, ope3, phenocam, phenology, primary-productivity
Organization: Department of Agriculture
Data from: Does Increasing the Diversity of Small Grain Cropping Systems Improve Aggregate Stability and Soil Hydraulic Properties?

<p>This is the Data Set from a paper titled "Does Increasing the Diversity of Small Grain Cropping Systems Improve Aggregate Stability and Soil Hydraulic Properties?" The paper is published in the journal Agronomy. The doi for the paper is <a href="https://doi.org/10.3390/agronomy13061567">https://doi.org/10.3390/agronomy13061567</a>. We measured wet and dry aggregate stability, water retention hydraulic conductivity, bulk density and soil carbon concentration on a dryland small grain cropping system study. This study was a dryland study located in Sidney, Montana, USA with 10 cropping systems. We sampled this study after 2 cycles of the four year cropping systems. The 10 cropping systems were continuous spring wheat, continuous winter wheat, continuous barley, pea-spring wheat, pea-barley, pea-winter wheat, pea-barley-camelina-spring wheat, pea-barley-canola-spring wheat, pea-winter wheat-camelina-spring wheat and pea-winter wheat-canola-spring wheat. We found that increasing the diversity of the cropping system did not improve the soil properties that we measured.</p>

Tags: ars, barley, climate, climate-soils-and-atmosphere, cropping-systems, data-gov, no-till-cropping-system, np216, small-grains, spring-wheat
Organization: Department of Agriculture
Data from: Low-dose foliar and tuber treatments of the auxin analog 2,4-D reduces potato common scab and powdery scab for multiple potato cultivars and can improve potato root development

<p>All of the annotated raw data from the submitted paper "Low-dose foliar and tuber treatments of the auxin analog 2,4-D reduces potato common scab and powdery scab for multiple potato cultivars and can improve potato root development." Datasets included are common scab disease scores from 2017 and 2018 field sites in ME and PA, soil profile data from 2018 PA and ME field sites, bag weight data from 2018 PA and ME field trials, common scab disease scores from seed tuber treatment trial in Tasmania, powdery scab disease score data from 2017 and 2018 Tasmania trials, tuber necrosis data from seed-tuber treatment trials, total tuber yield from the 2017 and 2018 Tasmania field trials, root growth from the 2017 Tasmania trial. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Compressed data from: Low-dose foliar and tuber treatments of the auxin analog 2,4-D reduces potato common scab and powdery scab for multiple potato cultivars and can improve potato root development  .</p> <p>File Name: 2-4DandScabRawDataCombined.zip</p><p>Resource Description: All data from the referenced submitted paper as individual csv files. </p></li></ul><p></p>

Tags: ars, data-gov, np303, potato-common-scab, powdery-scab
Organization: Department of Agriculture