AndreaBozzo/ceres-open-data-index huggingface dataset:
GOSSYM

<p>GOSSYM is a dynamic, process-level simulation model of cotton growth and yield. GOSSYM essentially is a materials balance model which keeps track of carbon and nitrogen in the plant and water and nitrogen in the soil root zone. GOSSYM predicts the response of the field crop to variations in the environment and to cultural inputs. Specifically, the model responds to weather inputs of daily total solar radiation, maximum and minimum air temperatures, daily total wind run, and rainfall and/or irrigation amount. The model also responds to cultural inputs such as preplant and withinseason applications of nitrogen fertilizer, row spacing and within row plant density as they affect total plant population, and cultivation practices. </p>

Tags: air-temperature, carbon, computer-software, cotton, crop-management, crop-models, farms, field-crops, irrigation-rates, models, nitrogen, nitrogen-fertilizers, plant-density, rain, rhizosphere, row-spacing, simulation-models, soil, solar-radiation, weather, wind
Organization: Department of Agriculture
West Texas Mesonet Agro-Climate Monitor

<p>West Texas Mesonet Agro-Climate Monitor shows the precipitation, temperature, weather forecast for mesonet stations in West Texas. Although dependent on rainfall and other climate factors to produce crops, West Texas crop consultants, extension agents, and agricultural producers have few tools that allow them to track the current growing season’s climate conditions and determine how current conditions compare with those of past years. The West Texas Mesonet Agro-Climate Monitor (ACM), a JavaScript web application based on daily data from Texas Tech University’s mesonet weather station network, was designed to meet this need. By displaying continuously updated information on variables such as soil temperature, cumulative growing degree days (GDD), cumulative precipitation, and first freeze dates, the ACM allows producers to monitor planting conditions, track crop development, and compare current conditions with those during the previous 10 yr’s growing seasons. In illustrating how mesonet data might be used as an operational climate data resource, the ACM might also serve as a conceptual model for other high resolution climate tools that estimate measures of current climate using continuously updated daily data sets. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: West Texas Mesonet Agro-Climate Monitor.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=484&modecode=30-96-05-00">https://www.ars.usda.gov/research/software/download/?softwareid=484&modecode=30-96-05-00</a> </p><p>download page</p></li></ul><p></p>

Tags: climatic-factors, computer-software, consultants, crops, data-collection, extension-agents, growing-season, heat-sums, internet, meteorological-data, models, planting, rain, soil-temperature, texas, weather-forecasting
Organization: Department of Agriculture
Terrestrial Condition Assessment (TCA) Wildfire Hazard Potential (Map Service)

The 2018 Wildland Hazard Potential (WHP) represents areas of uncharacteristic fuel buildup. The WFP is a raster geospatial product produced by the USFS Fire Modeling Institute in the Fire, Fuel, and Smoke Program. Higher values have a higher probability of high-intensity fire, with torching, crowning, and other forms of extreme fire behavior. Data used represent areas classified as �high� or �very high� hazard.

Tags: fire, gtac, open-data, risk, tca, usfs
Organization: Department of Agriculture
Data From: The 1014F knockdown resistance mutation is not a strong correlate of phenotypic resistance to pyrethroids in Florida populations of <i>Culex quinquefasciatus</i>

<p dir="ltr"><i>Culex quinquefasciatus</i> is an important target for vector control because of its ability to transmit pathogens that cause disease. Most populations are resistant to pyrethroids and often to organophosphates, the two most common classes of active ingredients used by public health agencies. A knockdown resistance (<i>kdr)</i> mutation, resulting in a change from a leucine to phenylalanine in the voltage gated sodium channel, is one mechanism contributing to the pyrethroid resistant phenotype. Enzymatic resistance has also been shown to play a very important role. Recent studies have shown strong resistance in populations even when <i>kdr</i> is relatively low which indicates factors other than <i>kdr</i> may be larger contributors to resistance. In this study, we examined on a statewide scale (over 70 populations), the strength of the correlation between resistance in the CDC bottle bioassay and the<i> kdr</i> genotypes and allele frequencies. Spearman correlation analysis showed only moderate (-0.51) and weak (-0.29) correlation between the <i>kdr</i> genotype and permethrin and deltamethrin respectively. The frequency of the <i>kdr</i> allele was an even weaker correlate. These results indicate, in contrast to <i>Aedes aegypti</i>, assessing <i>kdr</i> in populations of <i>Culex quinquefasciatus</i> is not a good surrogate for phenotypic resistance testing.</p>

Tags: cdc-bottle-bioassay, culex-quinquefasciatus, florida-counties, insecticide-resistance, knockdown-resistance-kdr, l1014f, organophosphate-insecticide-resistance-monitoring, pyrethroid-insecticide-resistance-monitoring, topical-application
Organization: Department of Agriculture
Data from: Discovery of MicroRNAs of the Stable Fly (Diptera: Muscidae) by High-Throughput Sequencing

<p>This dataset reports discovery and initial comparative analysis of 88 presumptive microRNA (miRNA) sequences from the stable fly, obtained using high-throughput sequencing of small RNAs. The majority of stable fly miRNAs were 22-23 nucleotides (nt) in length. Many miRNAs were arthropod specific, and several mature miRNA sequences showed greater sequence identity to miRNAs from other blood-feeding dipterans such as mosquitoes rather than to Drosophilids. This initial step in characterizing the stable fly microRNAome provides a basis for further analyses of life stage-specific and tissue-specific expression to elucidate their functional roles in stable fly biology.</p>
<p>The stable fly, Stomoxys calcitrans (L.), is a serious ectoparasite affecting animal production and health of both animals and humans. Stable fly control relies largely on chemical insecticides; however, the development of insecticide resistance as well as environmental considerations requires continued discovery research to develop novel control technologies. MicroRNAs are a class of short noncoding RNAs that have been shown to be important regulators of gene expression across a wide variety of organisms, and may provide an innovative approach with regard to development of safer more targeted control technologies. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Table 1. miRNAs identified in pooled life stages of the stable fly S. calcitrans and corresponding miRBase 18 entries.</p> <p>File Name: Web Page, url: <a href="https://academic.oup.com/view-large/91020692">https://academic.oup.com/view-large/91020692</a> </p><p>miRNAs identified in pooled life stages of the stable fly S. calcitran. and corresponding miRBase 18 entries (≥10 reads, sorted by abundance).</p></li></ul><p></p>

Tags: ars, cattle, cattle-pest, data-gov, diptera, ectoparasite, insecticide-resistance, livestock-pest, microrna, mirna, muscidae, noncoding-rna, np104, stable-fly, stomoxys-calcitrans
Organization: Department of Agriculture
Data from: Cultivar resistance to common scab disease of potato is dependent on the pathogen species

<p>All data from the paper "Cultivar resistance to common scab disease of potato is dependent on the pathogen species." Three separate datasets are included:</p>
<ol>
<li>
<p>A csv file with the disease severity of three common scab pathogens across 55 different potato cultivars in a greenhouse pot assay (Figures 2-5 in the associated paper). The included R script was used with this data to perform the ANOVA for the data from the greenhouse pot assay (Table 2 in the associated paper). This script can be used in R for any similar dataset to calculate the significance and percent of total variation for any number of user-defined fixed effects.</p>
</li>
<li>
<p>A zipped file with all of the qPCR data for the expression of the txtAB genes (Figure 6 in the associated paper).</p>
</li>
<li>
<p>An Excel file with the HPLC data for making the thaxtomin detection standard curve and quantifying the amount of thaxtomin in the test sample. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Streptomyces pot assay data.</p> <p>File Name: 18.4.2updatedfileAllDataPotAssay.csv</p><p>Resource Description: Combined data from all Streptomyces - potato pot assays from the paper "Cultivar resistance to common scab disease of potato is dependent on the pathogen species." This csv file can be used with the example R script "DiseaseseverityEstimateScript."</p></li><br><li><p>Resource Title: Combined qPCR data..</p> <p>File Name: CombinedtxtABqPCRresults.zip</p><p>Resource Description: Zipped file that contains all qPCR data of txtAB gene expression in all experimental conditions. Combined qPCR data from Figure 6 of the paper "Cultivar resistance to common scab disease of potato is dependent on the pathogen species."</p></li><br><li><p>Resource Title: R script for estimating disease severity.</p> <p>File Name: DiseaseSeverityEstimateScript.txt</p><p>Resource Description: R script used in combination with the "18.4.2updatedfileAllDataPotAssay.csv" file for generating the disease severity estimates (Figures 2-4) in the paper "Combined qPCR data from Figure 6 of the paper "Cultivar resistance to common scab disease of potato is dependent on the pathogen species."</p></li><br><li><p>Resource Title: Thaxtomin standard curve and quantification - All data.</p> <p>File Name: Thaxtomin_CalCurve_log_log-Scale_12072018 (003).xlsx</p><p>Resource Description: Excel file with two sheets. The first sheet is all of the HPLC data used for calculating the standard curve of thaxtomin using known standards. The second sheet is the quantification data for the abundance of thaxtomin across the experimental groups. Data presented as Figure 6 in the paper "Combined qPCR data from Figure 6 of the paper "Cultivar resistance to common scab disease of potato is dependent on the pathogen species."</p></li></ul><p></p>
</li>
</ol>

Tags: ars, data-gov, np303, plant-pathology
Organization: Department of Agriculture
USDA Plant Hardiness Zone Map (PHZM)

<p>The 2012 USDA Plant Hardiness Zone Map is the standard by which gardeners and growers can determine which plants are most likely to thrive at a location. The map is based on the average annual minimum winter temperature, divided into 10-degree F zones.</p>
<p>For the first time, the map is available as an interactive GIS-based map, for which a broadband Internet connection is recommended, and as static images for those with slower Internet access. Users may also simply type in a ZIP Code and find the hardiness zone for that area.</p>
<p>No posters of the USDA Plant Hardiness Zone Map have been printed. But state, regional, and national images of the map can be downloaded and printed in a variety of sizes and resolutions. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: USDA Plant Hardiness Zone Map.</p> <p>File Name: Web Page, url: <a href="https://planthardiness.ars.usda.gov/pages/view-maps">https://planthardiness.ars.usda.gov/pages/view-maps</a> </p><p>Includes interactive, static, and georeferenced maps, map and data downloads, and information about plant hardiness zones in the United States.</p></li></ul><p></p>

Tags: ars, data-gov, online-database, phzm, plant-hardiness-zone-map
Organization: Department of Agriculture
PeanutBase

<p>PeanutBase (<a href="https://peanutbase.org">peanutbase.org</a>) is the primary genetics and genomics database for cultivated peanut and its wild relatives. It houses information about genome sequences, genes and predicted functions, genetic maps, markers, links to germplasm resources, and maps of peanut germplasm origins.</p>
<p>This resource is being developed for U.S. and International peanut researchers and breeders, with support from The Peanut Foundation and the many contributors that have made the Peanut Genomics Initiative possible. Funded by The Peanut Foundation as part of the Peanut Genomics Initiative. Additional support from USDA-ARS. Database developed and hosted by the USDA-ARS SoyBase and Legume Clade Database group at Ames, IA, with NCGR and other participants. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: PeanutBase.org.</p> <p>File Name: Web Page, url: <a href="https://peanutbase.org">https://peanutbase.org</a> </p><p>Website pointer for PeanutBase.org - Genetic and genomic data to enable more rapid crop improvement in peanuts.</p>
<p>The peanut genome has been sequenced and analyzed as part of the <a href="https://peanutbase.org/IPGI">International Peanut Genomic Initiative</a>, in order to accelerate breeding progress and get more productive, disease-resistant, stress-tolerant varieties to farmers. The two diploid progenitors <a href="https://peanutbase.org/browse_search">have been sequenced and are available</a>, along with predicted genes and descriptions. The genomes of the diploid progenitors will be used to help identify and assemble the similar chromosomes in cultivated peanut. Cultivated peanut, <a href="https://peanutbase.org/Arachis/hypogaea">Arachis hypogaea</a>, is an allotetraploid (2n=4x=40) that contains two complete genomes, labeled the A and B genomes. <a href="https://peanutbase.org/Arachis/duranensis">A. duranensis</a> (2n=2x=20) has likely contributed the A genome, and <a href="https://peanutbase.org/Arachis/ipaensis">A. ipaensis</a> has likely contributed the B genome. It may be helpful to remember these two associations by using the mnemonic: "A" comes before "B" and "duranensis" comes before "ipaensis". Because of the difficulty of assembly a tetraploid genome, the two diploids, A. duranensis and A. ipaensis, have been sequenced and assembled first. Together these provide a good initial basis for the tetraploid genome. Additionally, the two will help guide assembly of the tetraploid genome. Sequencing work on the tetraploid genome is underway; stay tuned for updates in 2015.</p></li></ul><p></p>

Tags: allopolyploidy, arachis-hypogaea, ars, data-gov, database, diploidy, genes, genomics, germplasm, np301, online-database, peanut, plant-breeding, tetraploidy
Organization: Department of Agriculture
Virtual Grower 3

<p>Several years ago, our group released the Virtual Grower software to the public.  Initially designed to help greenhouse growers determine heating costs and do simple simulations to figure out where heat savings could be achieved, it has slowly added features so that now, Virtual Grower can help not only identify those savings through different greenhouse designs, but predict crop growth, assist in scheduling, make real-time predictions of energy use, and see the impact of supplemental lighting on plant growth and development. In other words, the software can be a safety net and allow users to experiment with "what if" scenarios in a risk-free setting.</p>
<p>Virtual Grower 3.0 is the next installment in the software series.  Released in August, 2011, this version is the first to be both Mac- and PC-compatible, meaning no one is excluded from being able to use the software.  Return users will find the same easy-to-use sections for designing greenhouse structures, heating systems, and lighting systems, and adding up to 40 plant species or varieties to your simulation.</p>
<p>New Features:</p>
<ul>
<li>The new version has nearly 800 locations across the U.S. represented by their weather, which is an increase of over 500 sites.  </li>
<li>Many of the new and old features are bolstered with graphics including a location map, photographs, responsive schematic drawings of your simulated greenhouse, and graphs and charts of the output. </li>
<li>Virtual Grower 3 can now accommodate dual-stage heating systems and apply them to as many greenhouses as you want.  This allows for the simulation of the increasingly common case of having a very high-efficiency system running most of the time and a lower-efficiency, less expensive system supply heat when additional heat is needed during cold periods. </li>
<li>Users can now enter a target finish date and "backtrack" to predict when the crop should be started from plug stage.  </li>
<li>Students in the greenhouse industry can view photographs and track down additional information for all of the crops included in the software.  </li>
<li>Improved support in instructional videos.</li>
</ul>
<p><br><br></p>
<p>Like it? Don't like it? Wish we would change something?  We want to hear from you.  Please contact us through the help desk at virtualgrower@ars.usda.gov.  Most of the features that are in the software now came from users like you.  This is an ongoing project with no expiration date, so your suggestions will be considered and hopefully incorporated into the next version.  </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Virtual Grower 3.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=309&modecode=50-82-05-00">https://www.ars.usda.gov/research/software/download/?softwareid=309&modecode=50-82-05-00</a> </p><p>download page</p></li></ul><p></p>

Tags: ars, data-gov, np303, np305
Organization: Department of Agriculture
WEPPCAT

<p>Global warming is expected to lead to a more vigorous hydrological cycle, including more total rainfall and more frequent high intensity rainfall events. Rainfall amounts and intensities increased on average in the United States during the 20th century and, according to climate change models, they are expected to continue to increase during the 21st century. These rainfall changes, along with expected changes in temperature, solar radiation, and atmospheric CO2 concentrations, will have significant impacts on soil erosion rates. The processes involved in the impact of climate change on soil erosion by water are complex, involving changes in rainfall amounts and intensities, number of days of precipitation, ratio of rain to snow, plant biomass production, plant residue decomposition rates, soil microbial activity, evapo-transpiration rates, and shifts in land use necessary to accommodate a new climatic regime. WEPPCAT is a web-based erosion simulation tool that allows for the assessment of changes in erosion rates as a consequence of user-defined climate change scenarios. This tool is based on the USDA-ARS Water Erosion Prediction Project (WEPP) erosion model. It has the capability of taking into account all of the erosion-affecting processes listed above.</p>
<p>This applications has been packaged into a virtual machine. Please fill out the form below to download the application. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: WEPPCAT.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=WEPPCAT&modecode=20-22-10-00">https://www.ars.usda.gov/research/software/download/?softwareid=WEPPCAT&modecode=20-22-10-00</a> </p><p>This applications has been packaged into a virtual machine. Please fill out the form below to download the application.</p></li></ul><p></p>

Tags: agricultural-research-service, biomass-production, carbon-dioxide, computer-software, evapotranspiration, global-warming, hydrologic-cycle, internet, land-use, microbial-activity, models, phytomass, plant-residues, rain, snow, soil, soil-erosion, solar-radiation, temperature, united-states, water-erosion-prediction-project
Organization: Department of Agriculture
GRACEnet (Greenhouse gas Reduction through Agricultural Carbon Enhancement network)

<p>GRACEnet (Greenhouse gas Reduction through Agricultural Carbon Enhancement network) is a research program initiated in the early 2000s . Goals are to better quantify greenhouse gas GHG emissions from cropped and grazed soils under current management practices and to identify and further develop improved management practices that will enhance carbon (C) sequestration in soils, decrease GHG emissions, promote sustainability and provide a sound scientific basis for carbon credits and GHG trading programs. This program generates information that is needed by agro-ecosystem modelers, producers, program managers and policy makers. Coordinated multi-location field studies follow standardized protocols to compare net GHG emissions (carbon dioxide, nitrous oxide, methane), C sequestration, crop/forge yields, and broad environmental benefits under different management systems that:</p>
<ol>
<li>Typify existing production practices</li>
<li>Maximize C sequestration</li>
<li>Minimize net GHG emissions</li>
<li>
<p>Meet sustainable production and broad environmental benefit goals (including C sequestration, net GHG emissions, water, air and soil quality, etc.)</p>
<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: GRACEnet Brochure 2016.</p> <p>File Name: GRACENET brochure  REVISED June 2017.pdf</p></li><br><li><p>Resource Title: Data Entry Template 2017.</p> <p>File Name: DET_GRACEnet_REAP.zip</p><p>Resource Description: Includes Excel templates for Experiment description worksheets, Site characterization worksheets, Management worksheets, Measurement worksheets where experimental unit data are reported, and Information that may be useful to the user, including drop down lists of treatment specific information and ranges of expected values. General and introductory instructions, as well as a Data Validation check are also included.</p></li><br><li><p>Resource Title: GRACEnet Brochure 2017.</p> <p>File Name: GRACENET brochure  REVISED July 2017 final.pdf</p></li><br><li><p>Resource Title: GRACEnet-NUOnet Data Dictionary.</p> <p>File Name: GRACEnet-NUOnet_DD.csv</p></li><br><li><p>Resource Title: GRACEnet Data Search.</p> <p>File Name: natres.zip</p><p>Resource Description: The attached file contains data from all sites as of February 9, 2022. For an interactive and up to date version of data visit https://usdaars.maps.arcgis.com/apps/MapSeries/index.html?appid=b66de747da394ed5aeab07dc9f50e516</p></li></ul>
</li>
</ol>

Tags: ars, biomass-yield, carbon-credits, chemical-composition, data-gov, energy-characteristics, fertilizer, ghg, gracenet, greenhouse-gas-fluxes, greenhouse-gas-reduction-through-agricultural-carbon-enhancement-network, harvesting-schedule, land-management, np211, np212, nutrient-characteristics, online-database, plant-biomass, planting-schedule, soil-carbon-stocks, soil-class, weather
Organization: Department of Agriculture
Terrestrial Condition Assessment (TCA) Climate Exposure Temperature Fall (Map Service)

The difference in Fall temperature (F) between the reference time period of 1900-2014 and the current time period 2015-2019. Fall months include September, October, and November. Data used are sourced from PRISM, Oregon State University. Data were summarized at the Subsection scale of the USFS National Hierarchy of Ecological Units and applied to the corresponding LTA.

Tags: gtac, open-data, tca, temperature, usfs
Organization: Department of Agriculture