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

<p style='margin-top:0px; margin-bottom:0.75rem; max-width:100%; font-family:&quot;Avenir Next W01&quot;, &quot;Avenir Next W00&quot;, &quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, sans-serif; font-size:16px;'><span style='max-width:100%; display:inherit;'>Feature layer containing authoritative guardrail information in the City of Sioux Falls, South Dakota.</span></p>

Tags: guardrail, lincoln, minnehaha, sd, sioux-falls, south-dakota, transportation
Organization: City of Sioux Falls
Pigs lacking TMPRSS2 displayed fewer lung lesions and reduced inflammatory response when infected with Influenza A virus

<p>An experimental challenge of Influenza A virus in genetically modified TMPRSS2 knockout pigs.</p>
<p>Resources in this dataset:</p>
<ul>
<li>Resource Title: Pigs lacking TMPRSS2 displayed fewer lung lesions and reduced inflammatory response when infected with Influenza A virus
File Name: TMPRSS2 dataset.xlsx
Resource Description: Supporting data for: Nasal shedding of A/swine/Iowa/A02524480/2020 (IA/20) H1N1 by virus titration on cell culture or qRT-PCR; Infection of IA/20 H1N1 in WT and TMPRSS2-/- pigs; Immunohistochemical (IHC) staining of Influenza A virus nucleoprotein; Cytokine and chemokine panel performed on bronchioalveolar lavage fluid.</li>
</ul><p></p>

Tags: ars, data-gov, disease-resistance, influenza-a-virus, np103, swine, tmprss2
Organization: Department of Agriculture
Genome annotation data from Calonectria species

<p>Annotation data were generated from existing genome assemblies of Calonectria henricotiae JAC13-131 (aka P-10-5865) and C. pseudonaviculata JAC13-27 (aka CT1). Gene prediction and annotations were conducted using the Funannotate v1.8.1 pipeline (<a href="https://funannotate.readthedocs.io/en/latest/">https://funannotate.readthedocs.io/en/latest/</a>).</p>

Tags: ars, data-gov, fungal-genome, np303, plant-pathogens
Organization: Department of Agriculture
AmeriFlux Observation Datasets, Reynolds Creek Experimental Watershed, Wyoming Big Sagebrush shrubland

<p>The site is located on the USDA-ARS's Reynolds Creek Experimental Watershed. It is dominated by Wyoming big sagebrush on land managed by USDI Bureau of Land Management.</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/347233fc-69ea-4df0-8148-9f3a5e3ea5cc" target="_blank">https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/347233fc-69ea-4df0-8148-9f3a5e3ea5cc</a> </p></li></ul>

Tags: ars, biota, carbon-storage, data-gov, earth-science-agriculture-soils-soil-moisture-water-content, earth-science-atmosphere-atmospheric-chemistry-carbon-and-hydrocarbon-compounds-carbon-dioxide, earth-science-atmosphere-atmospheric-radiation, earth-science-atmosphere-atmospheric-radiation-radiative-flux, earth-science-atmosphere-atmospheric-temperature-surface-temperature-air-temperature, earth-science-atmosphere-atmospheric-water-vapor-evapotranspiration, earth-science-atmosphere-atmospheric-water-vapor-humidity, earth-science-atmosphere-precipitation, earth-science-biosphere-vegetation-photosynthetically-active-radiation, ecosystem-productivity, environment, farming, in-situ-laboratory-instruments-current-wind-meters-sonic-anemometer, in-situ-laboratory-instruments-pressure-height-meters-apsair-pressure-sensor, in-situ-laboratory-instruments-temperature-humidity-sensors, np211, np215
Organization: Department of Agriculture
<b>Data from: Do species respond to multi-year disturbance rhythms and are we missing the beat?</b>

<div>A 15-yr (2006-2020) experiment testing factorially-arranged combinations of fire seasonality (summer, fall, spring) and fire return interval (2, 3, 6-yr) plus non-burned controls was conducted in northern mixed prairie to evaluate effects on <em>Hesperostipa comata</em>. Plots were 20-by-15 m with 3 replicates per treatment. Summer fires were conducted during summer quiescence, fall fires after a <-2.2<sup>o</sup>C frost and spring fires when <em>Bouteloua gracilis</em> initiated growth. Current-year aboveground biomass was estimated annually by clipping four 0.25-m<sup>2</sup> quadrats from each plot during peak biomass. Biomass samples were dried to a constant weight at 60°C and weighed to the nearest 0.01 g before being separated into current and past years’ growth and reweighed to determine current-year biomass as an estimate of productivity.</div><p></p>

Tags: disturbance-regime, fire, rangeland, return-interval, seasonality, semi-arid-grassland
Organization: Department of Agriculture
Database of USDA ARS JETs on channel boundary materials

<p dir="ltr">This dataset contains 1253 jet erosion tests (JETs) conducted <i>in situ</i> on stream-related materials by staff of the USDA-ARS National Sedimentation Laboratory, Oxford, MS, across the contiguous U.S. between 1997 and 2023. For each JET, its location in the channel cross section (e.g., bed, bank toe, and bank face), type of jet test device used, and time series of scour hole depth and associated pressure head are provided. The JET is comprehensively described by Hanson and Cook (2004). The JET is used to measure the erosion resistance of soils. A submerged jet formed by forcing pressurized flow through a nozzle is used to exert a shear stress on an erodible soil surface. The rate at which the soil surface erodes is measured over time. Erosion rate and applied shear stress can be calculated from the time series of scour hole depth and pressure head provided for each JET in this dataset. The relation between erosion rate and shear stress, termed erosion function, is then used to describe soil erosion resistance. The ARS post-processing tools for JETs (PP-JET) are available from GitHub (Langendoen, 2025). The derived erosion functions can be used for developing improved JET post-processing methods, evaluating the influence of different jet test devices, developing new mechanistic descriptions of the erosion of channel boundary materials, and as information required to assess best management practices for river management.</p>

Tags: jet-erosion-test, soil-erodibility, soil-erosion-resistance
Organization: Department of Agriculture
Data from: Insecticidal Management of Rangeland Grasshoppers Using Remotely Piloted Aerial Application System

<p>Grasshoppers are integral parts of rangeland ecosystems but also have the potential to reach population densities high enough (outbreaks) to cause serious economic damage from forage loss and affect adjacent crops. The objective of this study was to investigate the efficacy of treating grasshopper population hotspots with a liquid insecticide using a remotely piloted aerial application system (RPAAS), as opposed to fixed-wing aircraft, which is the most common method currently in use. A liquid insecticide, Sevin XLR PLUS (containing carbaryl), was applied on replicated 4.05-hectare (10-acre) plots with an RPAAS on a ranch in New Mexico. Our results demonstrated that Sevin XLR PLUS significantly suppressed grasshopper populations over a 14-day period (normalized population reduction was 79.11 ± 8.35% SEM) and quite rapidly (mostly by day 3) compared to untreated controls. These results are comparable to those achieved with fixed-wing aircraft. The RPAAS covered the whole test area in a single flight in approximately 5 min, making these population hotspot treatment applications relatively rapid, potentially more cost-effective, and more targeted in comparison to fixed-wing aircraft. Before adoption as an application method option, further research is recommended on using an RPAAS to cover larger areas in combination with using diflubenzuron-based insecticides, which are often preferred.</p>

Tags: ars, data-gov, mormon-crickets, np305, rangeland-grasshoppers, rpaas, rpas, sevin-xlr-plus, uas, uav
Organization: Department of Agriculture
Irrigator Pro

<p>Irrigator Pro is an expert system designed to provide irrigation scheduling recommendations based on scientific data resulting in conservation minded irrigation management. The success of Irrigator Pro for Peanuts created interest in other groups. A collaborative effort between the NPRL, Cotton Commission, University of Georgia, and the Peanut Foundation was established to create comparable models for cotton and corn.</p>
<p>Irrigator Pro is an irrigation scheduling tool for peanuts, corn, and cotton developed by the USDA Agricultural Research Service National Peanut Research Lab. Irrigator Pro is an expert system designed to provide recommendations based on scientific data resulting in conservation-minded irrigation management while maintaining high yields.</p>
<p>The Flint River Soil and Water Conservation District, with funding from USDA NRCS, partnered with the Peanut Lab and University of Georgia to develop a smartphone app and cloud-based platform for Irrigator Pro. The new version has been in beta testing for the last two crop seasons with a full launch planned for 2019.</p>
<p>Irrigator Pro is a trusted tool by farmers, crop consultants, Extension agents, and researchers across the Southeast. The original version is a desktop software that requires manual reading of soil moisture sensors in the field and manual data entry. The new smartphone app and cloud platform have automated the data collection process, integrating remote upload of soil moisture and temperature data with the Irrigator Pro model through the app and cloud platform.</p>
<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Website pointer to Irrigator Pro.</p> <p>File Name: Web Page, url: <a href="https://irrigatorpro.org/" target="_blank">https://irrigatorpro.org/</a> </p></li></ul>

Tags: ars, conservation, corn, cotton, data-gov, irrigation, irrigation-management, peanuts, scheduling-tool
Organization: Department of Agriculture
Crop Sequence Calculator Version 3.1

<p>The Crop Sequence Calculator software is an interactive program for viewing crop sequencing information. The Crop Sequence Calculator program is designed to assist agricultural managers determine workable cropping sequences for the northern Great Plains.  Version (3.1)  contains the previous version (3.0) and adds new information gathered from additional cropping sequence research, as well as supplemental information related to use of annual crops as cover crops.</p>
<p>Cropping systems need to be inherently flexible to take advantage of economic opportunities and/or adapt to environmental realities. Therefore, this program applies the principles of Dynamic Cropping Systems to help users select cropping sequences best suited to their particular situation. The research data used to develop the Crop Sequence Calculator were collected from no-till farming experiments conducted near Mandan, ND from 1998 to 2005. This version (3.1) contains the previous version (3.0) and adds new information gathered from additional cropping sequence research, as well as supplemental information related to use of annual crops as cover crops. Users are asked to select the appropriate data set for answering questions unique to their enterprise. The first data set is what we call Phase II. The Phase II experiment consisted of predominantly cool-season crops, and the weather conditions were considerably wetter than average. The ten crops used for this phase are shown in the Phase II Crops box. The Phase III experiment used some of the same crops as the Phase II, but included other crops considered to be warm-season crops. These crops are listed in the Phase III Crops box. The crops used in both phases are highlighted. Precipitation received during the Phase III experiment was below average. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Crop Sequence Calculator Version 3.1 download page.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=398&modecode=30-64-05-00#downloadForm">https://www.ars.usda.gov/research/software/download/?softwareid=398&modecode=30-64-05-00#downloadForm</a> </p></li></ul><p></p>

Tags: agricultural-management, ars, crop-production, cropping-sequences, cropping-systems, data-gov, dynamic-cropping-systems
Organization: Department of Agriculture
Irrigator Pro for Cotton

<p>Irrigator Pro is an expert system designed to provide irrigation scheduling recommendations based on scientific data resulting in conservation minded irrigation management. The success of Irrigator Pro for Peanuts created interest in other groups. A collaborative effort between the NPRL, Cotton Commission, University of Georgia, and the Peanut Foundation was established to create comparable models for cotton and corn.</p>
<p>Irrigator Pro is an irrigation scheduling tool for peanuts, corn, and cotton developed by the USDA Agricultural Research Service National Peanut Research Lab. Irrigator Pro is an expert system designed to provide recommendations based on scientific data resulting in conservation-minded irrigation management while maintaining high yields.</p>
<p>The Flint River Soil and Water Conservation District, with funding from USDA NRCS, partnered with the Peanut Lab and University of Georgia to develop a smartphone app and cloud-based platform for Irrigator Pro. The new version has been in beta testing for the last two crop seasons with a full launch planned for 2019.</p>
<p>Irrigator Pro is a trusted tool by farmers, crop consultants, Extension agents, and researchers across the Southeast. The original version is a desktop software that requires manual reading of soil moisture sensors in the field and manual data entry. The new smartphone app and cloud platform have automated the data collection process, integrating remote upload of soil moisture and temperature data with the Irrigator Pro model through the app and cloud platform.</p>
<p>The mobile version of the app can be downloaded at <a href="https://irrigatorpro.org">https://irrigatorpro.org</a> </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Irrigator Pro for Cotton.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=249&modecode=60-44-05-00">https://www.ars.usda.gov/research/software/download/?softwareid=249&modecode=60-44-05-00</a> </p><p>download page</p></li></ul><p></p>

Tags: ars, conservation, cotton, data-gov, irrigation, irrigation-management, scheduling-tool
Organization: Department of Agriculture
ComBase: A Web Resource for Quantitative and Predictive Food Microbiology

<p>ComBase includes a systematically formatted database of quantified microbial responses to the food environment with more than 65,000 records, and is used for:</p>
<ul>
<li>Informing the design of food safety risk management plans</li>
<li>Producing Food Safety Plans and HACCP plans</li>
<li>Reducing food waste</li>
<li>Assessing microbiological risk in foods</li>
</ul>
<p>The <strong>ComBase Browser</strong> enables you to search thousands of microbial growth and survival curves that have been collated in research establishments and from publications.</p>
<p>The <strong>ComBase Predictive Models</strong> are a collection of software tools based on ComBase data to predict the growth or inactivation of microorganisms as a function of environmental factors such as temperature, pH and water activity in broth.</p>
<p>Interested users can also contribute growth or inactivation data via the Donate Data page, which includes instructional videos, data template and sample, and an Excel demo file of data and macros for checking data format and syntax. </p>
<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Website Pointer to ComBase.</p> <p>File Name: Web Page, url: <a href="https://www.combase.cc/index.php/en/" target="_blank">https://www.combase.cc/index.php/en/</a> </p><p>ComBase is an online tool for quantitative food microbiology. Its main features are the ComBase database and ComBase models, and can be accessed on any web platform, including mobile devices. The focus of ComBase is describing and predicting how microorganisms survive and grow under a variety of primarily food-related conditions. ComBase is a highly useful tool for food companies to understand safer ways of producing and storing foods. This includes developing new food products and reformulating foods, designing challenge test protocols, producing Food Safety plans, and helping public health organizations develop science-based food policies through quantitative risk assessment. Over 60,000 records have been deposited into ComBase, describing how food environments, such as temperature, pH, and water activity, as well as other factors (e.g. preservatives and atmosphere) affect the growth of bacteria. Each data record shows users how bacteria populations change for a particular combination of environmental factors. Mathematical models (the ComBase Predictor and Food models) were developed on systematically generated data to predict how various organisms grow or survive under various conditions.</p></li></ul>

Tags: ars, combase, combined-database-for-predictive-microbiology, data-gov, np108, online-database
Organization: Department of Agriculture
Corn Residue Removal Plots Study for Resilient Economic Agricultural Practices in Florence, South Carolina

<p>Corn Residue Removal Plots Study for Resilient Economic Agricultural Practices in Florence, South Carolina</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/9dbbb9c4-801c-4ced-be34-8ccc36cd06d3" target="_blank">https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/9dbbb9c4-801c-4ced-be34-8ccc36cd06d3</a> </p></li></ul>

Tags: ars, corn, crop-residues, data-gov, environment, farming, np211, np212
Organization: Department of Agriculture
Reynolds Creek Experimental Watershed, Idaho (Climate)

<p>An extensive, 33 year (1964-1996), climatic database has been developed for three climate stations on the Reynolds Creek Experimental Watershed (RCEW) located near the north end of the Owyhee Mountains in southwest Idaho.  The longest records (1964-1996) are for daily maximum and minimum temperature.  The length of record for other weather elements that include relative humidity, solar radiation,  wind speed and direction, daily Class A pan evaporation and barometric pressure varies, but in general is from 1974-1996.  Weather sensors have varied from hygrothermographs with spring-driven clocks and charts to electronic sensors with the data telemetered daily to the Northwest Watershed Research Center (NWRC) office in Boise, Idaho. Most of the data, since the early 1980's, were measured and stored electronically, therefore, hourly data are available for most climatic elements between the early 1980's and 1996.  These data can be accessed from the USDA-ARS Northwest Watershed Research Center database.</p> <div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Climate Data.</p> <p>File Name: climate.zip</p><p>Resource Description: Climate data</p></li></ul>

Tags: ars, atmospheric-pressure, climate, data-gov, electronic-sensing, evaporation, mountains, np211, np215, relative-humidity, solar-radiation, streams, temperature, watersheds, wind-speed
Organization: Department of Agriculture
Field 70/71 Study for Resilient Economic Agricultural Practices in Ames, Iowa

<p>Field 70/71 Study for Resilient Economic Agricultural Practices in Ames, Iowa
See REAP brochure</p> <div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Ames, IA Field 70/71 Study (IAAM7071) CSV data.</p> <p>File Name: IAAM7071_csv_data.zip</p><p>Resource Description: CSV format data on Experimental Units, Field Sites, Biomass, Harvest Fraction, Residue Management, Soil Chemistry, Soil Cover, Soil Physics, Amendments, Planting, Tillage, Persons, Treatments, Weather Daily, Weather Station.</p></li></ul>

Tags: ars, cameras, data-gov, environment, farming, models, np211, np212
Organization: Department of Agriculture
ARS-Media

<p>Understanding the ion-specific effects of the mineral elements is a central theme of biology because these ions are fundamental to the composition and maintenance of life. However, experiments concerned with determining ion-specific effects are generally performed with salt, as opposed to ion, manipulations. This means that researchers have had to accept a co-variance in the co-ion of the salt used to manipulate the ion of interest. The result is that the effect of a single ion cannot be determined as it is confounded with the potential combined effects of the other ions that are co-varied. Because of this difficulty, the majority of research studies concerned with determining ion-specific effects exhibit ion confounding.  The software application ARS-Media utilizes a linear programming optimization algorithm to determine the combination of salts, acids, and bases that satisfies any given target solution of ions.  ARS-Media therefore allows researchers to construct experimental designs that use ions, as opposed to salts, as individual factors and, hence, experimentally determine ion-specific effects on biological responses relating to ion type, concentration, and proportion.</p>
<p>ARS-Media for Excel is an ion solution calculator that uses Excel's linear programming optimization add-in Solver.</p>
<p>ARS-Media utilizes Excel’s internal linear programming optimization algorithm to determine the combination of salts, acids, and bases that satisfy any given target solution of ions.  The spreadsheet is designed for the formulation of nutrient media used in such applications as plant tissue culture, hydroponics, algal culture, fertilizer formulations, microbial culture, and any application that requires the definition of a specific culture media by its ion composition.  The spreadsheet is formula-based and uses no macros that can sometimes conflict with institutional IT security systems.</p>
<p>Web download of these resources can be found at:
<a href="https://www.ars.usda.gov/research/software/download/?softwareid=148&modecode=60-34-05-00">ARS-Media</a>
<a href="https://www.ars.usda.gov/research/software/download/?softwareid=482&modecode=60-34-05-05">ARS-Media for Excel</a> </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: ARS-Media Ion Solution Calculator.</p> <p>File Name: ARS-Media Ion Solution Calculator.zip</p><p>Resource Description: ARS-Media Ion Solution Calculator.zip</p></li><br><li><p>Resource Title: ARS-Media for Excel.</p> <p>File Name: ARS-Media_Excel_p_5-15-15.xlsx</p></li><br><li><p>Resource Title: ARS-Media Excel Instructions.</p> <p>File Name: ARS-Media_Excel_Instructions_5-15-15[2].docx</p></li></ul><p></p>

Tags: ars, data-gov, np301
Organization: Department of Agriculture
Metadata for: Comparative studies on water- and vapor-based hydrothermal carbonization: process analysis

<p>This is digital research data corresponding to a published manuscript in "Comparative studies on water- and vapor-based hydrothermal carbonization: process analysis" Energies 2020, 13, 5733. Dataset may be assessed via the included link at the Dryad data repository.</p>
<p>Hydrothermal carbonization (HTC) reactor systems used to convert wet organic wastes into value-added hydrochar are generally classified in the literature as liquid water-based (HTC) or vapor-based (VTC). However, the distinction between the two is often ambiguous. In this paper, we theoretically developed models for predicting reactor pressure, volume fraction of liquid water and water distribution between phases as a function of temperature.  </p>
<p>Methods are described in the manuscript <a href="http://dx.doi.org/10.3390/en13215733">http://dx.doi.org/10.3390/en13215733</a>. Descriptions corresponding to each figure and table in the manuscript are placed on separate tabs to clarify abbreviations and summarize the data headings and units.</p>

Tags: ars, data-gov, environmental-engineering, hydrothermal-carbonization, np212, phase-distribution-of-water, process-conditions, reactor-pressure, vapothermal-carbonization
Organization: Department of Agriculture