AndreaBozzo/ceres-open-data-index huggingface dataset:
Long-Term Agroecosystem Research Network regions, 2018 version

<p>The Long-Term Agroecosystem Research Network, consisting of 18+ research locations, is conducting research on the sustainable intensification of agroecosystems. To enable coordinated network level research, a spatial framework is required to facilitate analysis. However, no suitable spatial framework currently exists to meet the needs for the LTAR Network. To develop a framework for analysis the LTAR Network initiated the Regionalization Project. Goals also included providing a standardized spatial footprint for LTAR cross-site investigations, estimating the confidence with which results from research plots and fields could reasonably be extrapolated to "represented regions", informing decisions about where additional research sites should be prioritized and facilitating public outreach of the LTAR Network. To address these goals a workshop was held in 2018 resulting in the production of three sets of regional boundaries in a geographic information system (GIS). These GIS datasets are intended to be used for mapping the
network and for summarizing spatial data relevant to domains of sustainable intensification corresponding with agricultural production, environmental impact, and rural prosperity. This resulted in a geodatabase of three new maps describing regional boundaries for the LTAR Network titled "Long-Term Agroecosystem Research Network regions, 2018 version", archived in the USDA National Agricultural Library's Ag Data Commons repository. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: LTAR_Regions_v2018.</p> <p>File Name: LTAR_Regions<em>v2018.gdb</em>.zip</p><p>Resource Description: Geodatabase of the regions pertaining to the Long-Term Agroecosystem Research Network. There are three data layers describing regions associated with indicators of sustainable intensification corresponding with agricultural production (LTAR_Production_v2018), environmental impacts (LTAR_Environment_v2018), and rural prosperity (LTAR_RuralProsp_v2018). These date were produced by the LTAR Regionalization Project as an outcome from the 2018 LTAR Regionalization Project workshop held in March 2018, Tifton, GA.</p><p>Resource Software Recommended: ArcGIS Pro,url: www.esri.com </p></li></ul><p></p>

Tags: agroecosystem, ars, continent-north-america-united-states-of-america, data-gov, gis, ltar, np211, np216, regions, sustainable-agriculture
Organization: Department of Agriculture
The Bronson Files, Dataset 3, Field 107, 2013

<p>Dr. Kevin Bronson provides a small area nitrogen and water management in Guayule agricultural research dataset for compute, including notation of field events and operations, an intermediate analysis table of correlated and calculated parameters with laboratory analysis results generated during the experimentation, plus high resolution plot level intermediate data analysis tables of SAS process output, as well as the complete raw sensor recorded logger outputs. </p>
<p>This data was collected during the beginning time period of our USDA Maricopa terrestrial proximal high-throughput plant phenotyping tri-metric method generation, where a 5Hz crop canopy height, temperature and spectral signature are recorded coincident to indicate a plant health status. In this early development period, our Proximal Sensing Cart Mark1 (PSCM1) platform supplants people carrying the CropCircle (CC) sensors, and with an improved view mechanical performance result.</p>
<p>Summary:
Active optical proximal cotton canopy sensing spatial data and including additional related metrics such as thermal are presented.
Agronomic nitrogen and irrigation management related field operations are listed.
Unique research experimentation intermediate analysis table is made available, along with 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 Mark 1, where the first dual sliding arm configuration was deployed and platform clearance raised successfully as design improvements.
SAS and GIS compute processing output tables, including Excel formatted examples are presented, where intermediate 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.  Lint and seed yields, first open boll biomass, and nitrogen uptake were also determined.  Soil profile nitrate to 1.8 m depth was determined in 30-cm increments, before planting and after harvest.  Nitrous oxide emissions were determined 20 or more weeks in the season with 1-L vented chambers (samples taken at 0, 12, and 24 minutes).  Nitrous oxide was determined by gas chromatography (electron detection detector).</p>

Tags: agroecosystems-environment-weather-and-climate, ars, data-gov, earth-science-agriculture-soils-nitrogen, earth-science-biosphere-vegetation-plant-phenology, field-based-high-throughput-phenotyping, np211, plant-phenotyping
Organization: Department of Agriculture
Assessing the rate and reversibility of large herbivore effects on community composition in a semi-arid grassland ecosystem with GZTX data on the Central Plains Experimental Range, Nunn, Colorado, USA 1992-2017

<p>This data package was produced initially by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Then, was continued by the Rangeland Resources and Systems Research Unit of the USDA Agricultural Research Service. Data collection was conducted on the Central Plains Experimental Range in Nunn, Colorado.</p>
<p>When the CPER was established in 1939, researchers constructed a .5-1 ha grazing exclosure in each of the pastures. These areas have remained protected from grazing for the past 70 years. The remaining areas have been grazed for the past 20+ years. This collection of pastures and exclosures provided an extraordinary opportunity to reinitiate grazing and protection, and evaluate the balance between degradation and aggradation. We proposed to rearrange fences and expose areas to grazing that have been protected for 50 years, and protect areas from grazing that had been grazed for 50 years. The combinations of grazing conditions were: 1. Long-term protection 2. Long-term grazing (moderate) 3. 50 years of protection followed by grazing 4. 50 years of grazing followed by protection Net primary production, nitrogen dynamics, cattle utilization, and community dynamics of vegetation were measured. Additional information and referenced materials about many of the long-term studies initiated on the CPER can be found: <a href="http://hdl.handle.net/10217/85596">http://hdl.handle.net/10217/85596</a>. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Monthly Precipitation Data (1991-2017)  from the Central Plains Experimental Range, Nunn, CO.</p> <p>File Name: precipitationData.xlsx</p><p>Resource Description: These data were collected from a catch can located at the CPER headquarters</p></li><br><li><p>Resource Title: Species level percent basal cover data associated with the GZTX study on the Central Plains Experimental Range..</p> <p>File Name: baseline3_GZTX.xlsx</p><p>Resource Description: Species level percent basal cover data associated with the GZTX study on the Central Plains Experimental Range.</p></li><br><li><p>Resource Title: baseline3 GZTX Data Dictionary.</p> <p>File Name: baseline3_GZTX_dataDictionary.csv</p></li></ul><p></p>

Tags: ars, data-gov, np215, precipitation
Organization: Department of Agriculture
CottonGen JBrowse

<p>CottonGen has an instance of the JBrowse genome browser for viewing genome data. A list of the genomes available in CottonGen can be accessed by clicking the <a href="https://www.cottongen.org/tools/jbrowse">JBrowse link in the Tools menu</a>.</p>
<p>Whole Genomes</p>
<ul>
<li>2019-03: Gossypium barbadense AD2 Hai-7124 genome ZJU v1.1_a1</li>
<li>2018-12: Gossypium barbadense AD2 3-79 genome HAU v2_a1</li>
<li>2015-12: Gossypium barbadense AD2 3-79 genome HAU v1_a1</li>
<li>2019-03: Gossypium hirsutum AD1 genome ZJU-Improved v2.1_a1</li>
<li>2018-12: Gossypium hirsutum AD1 genome HAU v1_a1</li>
<li>2017-09: Gossypium hirsutum AD1 genome TX-JGI v1.1_a1</li>
<li>2015-04: Gossypium hirsutum AD1 genome NAU-NBI v1.1_a1.1</li>
<li>2015-04: Gossypium hirsutum AD1 genome CGP-BGI v1_a1</li>
<li>2018-05: Gossypium arboreum A2 genome CRI-Updated v1_a1</li>
<li>2014-05: Gossypium arboreum A2 genome CGP-BGI v2_a1</li>
<li>2012-12: Gossypium raimondii D5 genome JGI v2_a2.1</li>
<li>2012-08: Gossypium raimondii D5 genome CGP-BGI v1_a1</li>
</ul>
<p>Chloroplast Genomes</p>
<ul>
<li>Gossypium arboreum chloroplast</li>
<li>Gossypium barbadense chloroplast</li>
<li>Gossypium hirsutum chloroplast</li>
<li>Gossypium raimondii chloroplast</li>
</ul>
<p>Please watch the JBrowse tutorial for more details about how to navigate and use JBrowse.</p>
<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: CottonGen JBrowse and User Manual.</p> <p>File Name: Web Page, url: <a href="https://www.cottongen.org/node/8287911" target="_blank">https://www.cottongen.org/node/8287911</a> </p><p>CottonGen has an instance of the JBrowse genome browser for viewing genome data.  A list of the genomes available in CottonGen can be accessed by clicking the <a href="https://www.cottongen.org/tools/jbrowse" target="_blank">JBrowse link in the Tools menu</a>.  

Whole Genomes

*   2019-03: Gossypium barbadense AD2 Hai-7124 genome ZJU v1.1_a1
*   2018-12: Gossypium barbadense AD2 3-79 genome HAU v2_a1
*   2015-12: Gossypium barbadense AD2 3-79 genome HAU v1_a1
*   2019-03: Gossypium hirsutum AD1 genome ZJU-Improved v2.1_a1
*   2018-12: Gossypium hirsutum AD1 genome HAU v1_a1
*   2017-09: Gossypium hirsutum AD1 genome TX-JGI v1.1_a1
*   2015-04: Gossypium hirsutum AD1 genome NAU-NBI v1.1_a1.1
*   2015-04: Gossypium hirsutum AD1 genome CGP-BGI v1_a1
*   2018-05: Gossypium arboreum A2 genome CRI-Updated v1_a1
*   2014-05: Gossypium arboreum A2 genome CGP-BGI v2_a1
*   2012-12: Gossypium raimondii D5 genome JGI v2_a2.1
*   2012-08: Gossypium raimondii D5 genome CGP-BGI v1_a1

Chloroplast Genomes

*   Gossypium arboreum chloroplast
*   Gossypium barbadense chloroplast
*   Gossypium hirsutum chloroplast
*   Gossypium raimondii chloroplast

Please watch the JBrowse tutorial for more details about how to navigate and use JBrowse.</p></li></ul>

Tags: ars, chloroplast, cotton, cottongen, data-gov, genomics, np301, online-database
Organization: Department of Agriculture
Data from: Development of PLEAD: a database containing event-based runoff P loadings from agricultural fields

<p>The P Loss in runoff Events from Agricultural fields Database (PLEAD) is a compilation of event-based, field-scale dissolved and/or total P loss runoff loadings from agricultural fields collected at various research sites located in the US Heartland and Southern US. The database also includes runoff and erosion rates; soil test P; tillage practices; planting and harvesting rates and practices; fertilizer application rate, method, and timing; manure application rate, method, and timing; and livestock grazing density and timing. In total, over 1800 individual runoff events – ranging in duration from 0.4 to 97 hr – have been included in the database. Event runoff P losses ranged from less than 0.05 to 1.3 and 3.0 kg P/ha for dissolved and total P, respectively. The data contained in this database have been used in multiple research studies to address important modeling questions relevant to P management planning. We provide these data to encourage additional studies by other researchers. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: PLEAD Database - Excel.</p> <p>File Name: PLEAD_2018-11-16.xlsx</p><p>Resource Description: Includes data spreadsheets for: Land Use, Soil Data, Soil Chem Data, Inorganic P Application, Grazing Data, Organic P Application, Tillage, Irrigation, Planting, Harvesting, Runoff Data, Sampling Info, Runoff Collection Notes, Daily Weather Data, Weather Stations, Other Notes, Contact Info.</p></li><br><li><p>Resource Title: PLEAD Database Data Dictionary.</p> <p>File Name: PLEAD_data_dictionary.csv</p><p>Resource Description: Defines the column headers/variables, units, and data type represented in each spreadsheet.</p></li></ul><p></p>

Tags: ars, data-gov, np212, p-loss-in-runoff-events-from-agricultural-fields-database, phosphorus-loss, phosphorus-modeling, plead
Organization: Department of Agriculture
NYC Business Solutions for NYCHA Residents by NYCHA Development - Local Law 163

This datasets contains information about NYC <a href="https://maps.nyc.gov/sbs/">Business Solutions</a> service, a service offered by the Department of Small Business Services (SBS) aimed at giving New Yorkers free services to start, operate and grow their businesses. Each row in the dataset represents the number of public housing residents on a NYCHA Development-level who receive or utilize this service.

For datasets related to other services provided to NYCHA residents, view the data collection “Services available to NYCHA Residents - Local Law 163”.

Tags: businessolutions, development, ll163, locallaw163, nycha, public-housing, sbs, smallbusinesses
Organization: City of New York
Data from: Construction of a High-Density American Cranberry (Vaccinium macrocarpon Ait.) Composite Map Using Genotyping-by-Sequencing for Multi-pedigree Linkage Mapping

<p>The American cranberry (<em>Vaccinium macrocarpon</em> Ait.) is a recently domesticated, economically important, fruit crop with limited molecular resources. New genetic resources could accelerate genetic gain in cranberry through characterization of its genomic structure and by enabling molecular-assisted breeding strategies. To increase the availability of cranberry genomic resources, genotyping-by-sequencing (GBS) was used to discover and genotype thousands of single nucleotide polymorphisms (SNPs) within three interrelated cranberry full-sib populations. Additional simple sequence repeat (SSR) loci were added to the SNP datasets and used to construct bin maps for the parents of the populations, which were then merged to create the first high-density cranberry composite map containing 6073 markers (5437 SNPs and 636 SSRs) on 12 linkage groups (LGs) spanning 1124 cM. Interestingly, higher rates of recombination were observed in maternal than paternal gametes. The large number of markers in common (mean of 57.3) and the high degree of observed collinearity (mean Pair-wise Spearman rank correlations >0.99) between the LGs of the parental maps demonstrates the utility of GBS in cranberry for identifying polymorphic SNP loci that are transferable between pedigrees and populations in future trait-association studies. Furthermore, the high-density of markers anchored within the component maps allowed identification of segregation distortion regions, placement of centromeres on each of the 12 LGs, and anchoring of genomic scaffolds. Collectively, the results represent an important contribution to the current understanding of cranberry genomic structure and to the availability of molecular tools for future genetic research and breeding efforts in cranberry. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Journal article with supplementary data files.</p> <p>File Name: Web Page, url: <a href="https://academic.oup.com/g3journal/article/7/4/1177/6031795#supplementary-data">https://academic.oup.com/g3journal/article/7/4/1177/6031795#supplementary-data</a> </p></li></ul><p></p>

Tags: ars, breeding, cranberry, cranberry-full-sib-populations, crop, data-gov, fruit, genomics
Organization: Department of Agriculture
STEWARDS - A data delivery application for the USDA/ARS Conservation Effects Assessment Project

<p>A data delivery application that provides web-based access to of soil, water, climate, land management, and geospatial data produced by Conservation Effects Assessment Project (CEAP) watershed research sites across the United States.</p>
<ul><li>Data access via ArcGIS Server and MS SQL Server</li>
<li>Enhanced data searches and summary options in Tools</li>
<li>Access to high-resolution imagery in the Map>Table of Contents</li>
<li>Enhanced graphing options on the Get Data page</li>
<li>Transparency sliders for individual map components in the Map>Table of Contents</li>
</ul> <div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: STEWARDS - A data delivery application for the USDA/ARS Conservation Effects Assessment Project.</p> <p>File Name: Web Page, url: <a href="https://www.nrrig.mwa.ars.usda.gov/stewards/stewards.html" target="_blank">https://www.nrrig.mwa.ars.usda.gov/stewards/stewards.html</a> </p></li></ul><p></p>

Tags: ars, barometric-pressure, beasley-lake, choptank-river, coliforms, data-gov, deethylatrazine, deisoatrazine, discharge, dissolved-solids, enterococci, filterable-suspended-solids, fort-cobb-reservoir, georgia, geospatial-data, gis, goodwater-creek, goodwin-creek, gust-speed, hydroxyatrazine, idaho, indiana, iowa, iron, leon-river, little-river, little-washita-river, mahantango-creek, map, maryland, mississippi, missouri, north-walnut-creek, np211, ohio, oklahoma, online-database, pennsylvania, rainfall, relative-humidity, riesel-watershed, salinity, salt-river, sample-flow, secchi-depth, sediment, silt, simazine, sodium, soil-conductivity, soil-moisture, soil-temperature, soil-texture, soil-water-content, solar-irradiance, solar-radiation, south-fork-iowa-river, specific-conductivity, st-joseph-river, stream-stage, sulfate, sulfur, surface-runoff, suspended-solids, texas, topashaw-canal, upper-big-walnut-creek, upper-snake-rock-creek, vapor-pressure, water-temperature, water-turbidity, wind-direction, wind-run, wind-speed, zinc
Organization: Department of Agriculture
Data from: Chromosome-scale Genome Assembly of Lewis Flax (Linum lewisii Pursh.)

<p>Within this dataset:</p>
<ol>
<li>Genome assembly of Linum lewisii (NDSU_LiLewi_1.0.fasta)
<ul>
<li>First 9 scaffolds represent all 9 chromosomes (e.g. Scaffold_1 is Chromosome 1, Scaffold_9 is Chromosome 9)</li>
<li>Remaining scaffolds are unplaced contigs</li>
<li>4 scaffolds shorter than 200bp were removed (Scaffold_[1710-1713])</li>
<li>Scaffold_919 was also removed due to identified contamination (a-proteobacteria)</li>
</ul></li>
<li>Genome annotation file in GFF3 format </li>
<li>RNA-Seq data for tissue grown in dark conditions</li>
<li>RNA-Seq data for tissue grown in light conditions</li>
<li>RNA-Seq data of meristem tissue grown in cold conditions</li>
<li>RNA-Seq data of pre-flower (developing bud) tissue</li>
<li>RNA-Seq data of flowering tissue</li>
<li>RNA-Seq data of post-flower (developing seed capsules) tissue</li>
<li>Raw Omni-C reads</li>
</ol>
<p>Linum lewisii, a perennial blue flax native to North America, holds potential as a sustainable perennial crop for oilseed production due to its ecological adaptability, upright harvestable structure, nutritious seeds, and low insect and disease issues. Its native distribution spans a large geographic range, from the Pacific Coast to the Mississippi River, and from Alaska to Baja California. Tolerant to cold and drought conditions, this species is also important for native ecosystem rehabilitation. Its enhancement of soil health, support for pollinators, and carbon sequestration underscore its agricultural relevance. </p>
<p>This study presents a high-quality, chromosome-scale assembly of the L. lewisii (2n = 2x = 18) genome, derived from PacBio HiFi and Dovetail Omni-C sequencing of the “Maple Grove” variety. The initial assembly contained 642,903,787 base pairs across 2,924 scaffolds. Following HiRise scaffolding, the final assembly contained 643,041,835 base pairs, across 1,713 scaffolds, yielding an N50 contig length of 66,209,717 base pairs. Annotation of the assembly revealed 38,808 genes, including 37,599 protein-coding genes and 7,108 putative transposable elements. Analysis of synteny with other flax species revealed a striking number of chromosomal rearrangements. We also found an intriguing absence of the single-copy TSS1 gene in the L. lewisii genome, potentially linked to its transition from heterostyly to homostyly. </p>
<p>Taken together, these findings represent a significant advancement in our understanding of the Linum genus and provide a resource for future domestication efforts and basic research on Lewis flax.</p>

Tags: ars, crop-domestication, data-gov, gene-annotation, genome-assembly, heterostyly, hirise-scaffolding, homostyly, linum, mating-system-evolution, np301, oilseed-crop, perennials, s-locus, sustainable-agriculture, transposable-elements
Organization: Department of Agriculture
Amino acid and phenolic compound levels in grapevine leaves infected with Grapevine leafroll-associated virus 3 and Grapevine red blotch-associated virus

<p>Dataset consists of monitoring the levels of 15 amino acid and 21 phenolic compounds in Cabernet franc grapevine leaves infected with Grapevine red blotch-associated virus or Cabernet sauvignon grapevine leaves infected with Grapevine leafroll-associated virus 3 during May, July, and September of 2018 and 2019 in Davis, California. Unless indicated, amino acid data is in microg/g fresh weight and phenolic data is in mg/g fresh weight. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Amino acid and phenolic compound amounts in healthy and virus-infected grapevines..</p> <p>File Name: GrapevineVirusChemistryProject.xlsx</p><p>Resource Description: Data from leaves collected in May, July, or September in 2018 or 2019. Unless indicated, amino acid levels in ppm (microg/g fresh weight) and phenolic levels in mg/g fresh weight.</p></li></ul><p></p>

Tags: amino-acids, ars, data-gov, grapevine, grapevine-leafroll-associated-virus-3-glrav-3, grapevine-red-blotch-assoicated-virus-grbav, host-plant-interactions, np303, phenolics
Organization: Department of Agriculture
Data from: Topographic position index predicts within-field yield variation in a dryland cereal production system

<p dir="ltr">We investigated drivers of sub-field spatial variability in yield for 3 crops (hard red winter wheat, <i>Triticum aestivum</i> L. variety Langin; corn, <i>Zea mays</i> L.; and proso millet, <i>Panicum milaceum</i> L.) usings this multi-year dataset from a dryland research farm in northeastern Colorado, USA. The dataset spanned 18 2.6-4.3 ha management units collected over 4 years (2019-2022). The data includes high resolution topographic data collected via real-time kinematic GPS, densely sampled soil texture and chemical properties, and meteorological data from an on-site weather station.</p>

Tags: dryland, machine-learning, precision-agriculture, rainfed, random-forest, spatial-variability, topographic-position-index, yield
Organization: Department of Agriculture