AndreaBozzo/ceres-open-data-index huggingface dataset:
Know Your Farmer, Know Your Food Projects

This dataset reflects USDA funded projects to develop local and regional food systems. It includes data from virtually all USDA Agencies and 9 other Federal Departments.

Tags: careers, farmers-market-promotion-program, federal-state-marketing-improvement-program, food-hubs, healthy-food-access, know-your-farmer, local-food, local-meat, regional-food-systems, specialty-crop-block-grant
Organization: Department of Agriculture
Terrestrial Condition Assessment (TCA) Tree Mortality 0 to 5 years (Map Service)

Data are derived from 2015-2019 (0 - 5 years) aerial detection surveys for tree defoliation and mortality from the USFS Forest Health Assessment and Applied Sciences Team (FHAAST) National Forest Pest Conditions Database. Polygons are created by aerial sketch mapping, and coded for defoliation and mortality, in addition to other damage codes. Defoliation and mortality layers were created from the polygon data and the attribute codes. The layers were merged to compensate for difficulties in identifying defoliation separately from mortality in hardwoods vs. conifer forests. Areas that were defoliated during three of the years recorded in the five-year dataset are thought to have significant impacts and likely mortality, so these polygons were added to the mortality layer. The layer includes areas with mortality classed as very light.

Tags: gtac, open-data, tca, tree-mortality, usfs
Organization: Department of Agriculture
Terrestrial Condition Assessment (TCA) Tree Mortality 6 to 10 years (Map Service)

Data are derived from 2010-2014 (6-10 years) aerial detection surveys for tree defoliation and mortality from the USFS Forest Health Assessment and Applied Sciences Team (FHAAST) National Forest Pest Conditions Database. Polygons are created by aerial sketch mapping, and coded for defoliation and mortality, in addition to other damage codes. Defoliation and mortality layers were created from the polygon data and the attribute codes. The layers were merged to compensate for difficulties in identifying defoliation separately from mortality in hardwoods vs. conifer forests. Areas that were defoliated during three of the years recorded in the five-year dataset are thought to have significant impacts and likely mortality, so these polygons were added to the mortality layer. The layer includes areas with mortality classed as  very light .

Tags: gtac, open-data, tca, tree-mortality, usfs
Organization: Department of Agriculture
Global TempSIM - Version 1.0

<p>The purpose of this tool is to estimate daily maximum and minimum air temperatures for a yearly cycle at any location on the globe. Global TempSIM predicts the daily average air temperature based upon 30-yr (1961 • 1990) temperature records that were compiled and interpolated by Legates and Willmott (1990a and 1990b) with further improvements by Willmott and Matsuura (1995) (data located at <a href="http://climate.geog.udel.edu/~climate/">http://climate.geog.udel.edu/~climate/</a>). </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Global TempSIM - Version 1.0.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=158&modecode=50-60-05-00">https://www.ars.usda.gov/research/software/download/?softwareid=158&modecode=50-60-05-00</a> </p><p>download page</p></li></ul><p></p>

Tags: ars, data-gov, np305
Organization: Department of Agriculture
Physical Mapping of the Wheat D Genome (Aegilops tauschii)

<p>This is an Aegilops tauschii genome database containing genetic and physical maps, genetic markers and genomic sequences and up-to-date releases on Ae. tauschii genome mapping. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Web Page.</p> <p>File Name: Web Page, url: <a href="https://probes.pw.usda.gov/WheatDMarker/">https://probes.pw.usda.gov/WheatDMarker/</a> </p></li></ul><p></p>

Tags: ars, data-gov, genetics-genomics-breeding, online-database
Organization: Department of Agriculture
Non-dominated Sorting Genetic Algorithm-II

<p>This code is implements the nondominated sorting genetic algorithm (NSGA-II) in the R statistical programming language. The function is theoretically applicable to any number of objectives without modification. The function automatically detects the number of objectives from the population matrix used in the function call. NSGA-II has been applied in ARS research for automatic calibration of hydrolgic models (whittaker link) and economic optimization (whittaker link). </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Non-dominated Sorting Genetic Algorithm-II.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=393&modecode=20-72-05-00">https://www.ars.usda.gov/research/software/download/?softwareid=393&modecode=20-72-05-00</a> </p><p>download page</p></li></ul><p></p>

Tags: algorithms, computer-software, evolution, multi-criteria-decision-making, operations-research, population-size, progeny
Organization: Department of Agriculture
Ecological Subsections (Feature Layer)

This data set includes polygons for ecological subsections within Subregions within the conterminous United States. This data set contains regional geographic delineations for analysis of ecological relationships across ecological units. <a href='https://data.fs.usda.gov/geodata/edw/edw_resources/meta/S_USA.EcomapSubsections.xml' target='_blank' rel='nofollow ugc noopener noreferrer'>Metadata</a>

Tags: biota, ecological-subsections, ecology, open-data
Organization: Department of Agriculture
FilmPC

<p>Plastic tarps currently used during soil fumigation to control emissions have been shown to be permeable to fumigant vapors, resulting in appreciable losses to the atmosphere. New low-permeability films are being developed to reduce fumigant emissions and increase efficacy.</p>
<p>A rapid, reliable, and sensitive method is required to measure the permeability of various films that may be used in new management practices. This manuscript presents an approach for estimating the mass transfer coefficient (h) of fumigant compounds across agricultural films. The h is a measure of the resistance to diffusion which, unlike other measures of permeability, is a property of the film-chemical combination and independent of the concentration gradient across the film.</p>
<p>This method uses static sealed cells; fumigant vapor is spiked to one side of the film and the concentrations on both sides of the film are monitored until equilibrium. An analytical model is fitted to the data to obtain h. This model relies on a mass balance approach and includes sorption to and diffusion across the film membrane. The method was tested using two polyethylene films and a very low-permeability film and showed that the method produces a sensitive and reproducible measure of film permeability. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: FilmPC download page.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=302&modecode=20-36-05-00">https://www.ars.usda.gov/research/software/download/?softwareid=302&modecode=20-36-05-00</a> </p></li></ul><p></p>

Tags: computer-software, emissions, fumigants, mass-transfer, models, natural-resources-earth-and-environmental-sciences, permeability, polyethylene-film, soil-fumigation, sorption, vapors
Organization: Department of Agriculture
DepositScan

<p>DepositScan is a scanning program that can quickly evaluate spray deposit distribution on water sensitive paper or Kromekote cards. The program consists of a set of custom plugins that are used by an image-processing program to produce a number of measurements useful for expressing spray deposit distribution. The DepositScan program offers a convenient solution for on-the-spot evaluation of spray quality even under field working conditions.</p>
<p>To download and install the DepositScan software:</p>
<ol>
<li>Fill in the form below and click <strong>Take me to the download</strong></li>
<li>Create a folder named <strong>DepositScan</strong> on your hard drive.</li>
<li>Click <strong>DepositScanInstall.exe</strong> and choose to save the file to your <strong>DepositScan</strong> folder</li>
<li>When the download is complete, double-click <strong>DepositScanInstall.exe</strong>.  In the Win-zip Self-Extractor window, click Unzip to extract the program files to the <strong>DepositScan</strong> folder.  </li>
</ol>
<p><br>
<br></p>
<p>Refer to the DepositScanManual.pdf in the DepositScan folder for guidance in setting up your scanner and using DepositScan.</p>
<p>Update 12/4/2009:</p>
<p>We have added ExtractResults_v1.1, a tool for consolidating output files of the DepositScan program.  Refer to the ExtractResults Manual provided for assistance in using the program.  </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: DepositScan.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=247&modecode=50-82-05-00">https://www.ars.usda.gov/research/software/download/?softwareid=247&modecode=50-82-05-00</a> </p><p>download page</p></li></ul><p></p>

Tags: ars, autosketch, data-gov, imageplus, laserjet, pixel
Organization: Department of Agriculture
Long-read sequencing data from pure cultures of <i>Escherichia coli</i> O157:H7 and ground beef inoculated with <i>E. coli</i> O157:H7

<p dir="ltr">Foodborne pathogens are a significant cause of illness and infection with Shiga toxin-producing <i>Escherichia coli</i> (STEC) has the potential to produce life-threatening complications. The current methods to identify STEC in meat involve culture-based, molecular, and proteomic assays and take at least four days to complete. This time could be reduced by using long-read whole genome sequencing to identify foodborne pathogens. Therefore, the goal of this project was to evaluate using long-read sequencing to detect STEC in ground beef. The objectives of the project included: establishing optimal sequencing parameters, determining the limit of detection of all STEC virulence genes of interest in pure cultures and spiked ground beef, and evaluating selective sequencing to enhance STEC detection in ground beef. Sequencing libraries were run on Oxford Nanopore Technologies’ MinION sequencer. Optimal sequencing output was obtained using the default parameters in MinKNOW, except for setting the minimum read length to 1 kb. All genes of interest (<i>eae</i>, <i>stx1</i>, <i>stx2</i>, <i>fliC</i>, <i>wzx</i>, <i>wzy</i>, <i>rrsC</i>) were detected in DNA extracted from STEC pure cultures within 1 hour of sequencing, and 30X coverage was obtained within 2 hours. All virulence genes were confidently detected in STEC DNA quantities as low as 12.5 ng. In STEC inoculated ground beef, software-controlled selective sequencing improved virulence gene detection; however, several virulence genes were not detected due to high bovine DNA concentrations in the samples. Growth enrichment of inoculated meat samples in mTSB resulted in a 100-fold increase in virulence gene detection as compared to the unenriched samples. The results of this project suggest that further development of long-read sequencing protocols may result in a faster, less labor-intensive method to detect STEC in ground beef. The sequencing data from this project has been uploaded.</p>

Tags: escherichia-coli-o157-h7, food-safety, food-testing, long-read-sequencing, meat
Organization: Department of Agriculture
BK-Economics

<p>BK-Economics is a software package that was developed by a team of scientists at the Carl Hayden Bee Research Center in Tucson, Arizona to assist commercial beekeepers in streamling their business practices.  This software allows beekeepers to simulate years of business, taking into account factors like equipment purchases, labor force, transportation, marketing strategies, loans, honey flow, and other hive products without taking the usual risks.  This software, when used in combination with the marketing strategy information in publication, can help beekeepers formulate a successful business plan when making financial decisions, expanding an operation or just starting out. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: BK-Economics download page.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=76&modecode=20-22-05-00">https://www.ars.usda.gov/research/software/download/?softwareid=76&modecode=20-22-05-00</a> </p><p>Link to the download page: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=76&modecode=20-22-05-00">https://www.ars.usda.gov/research/software/download/?softwareid=76&modecode=20-22-05-00</a></p></li></ul><p></p>

Tags: arizona, beekeepers, bees, business-enterprises, business-planning, computer-software, equipment, honey, labor-force, loans, marketing-strategies, risk, scientists, transportation
Organization: Department of Agriculture
National Wild and Scenic Rivers (Feature Layer)

A depiction of areas designated as Wild and Scenic Rivers. <a href='https://data.fs.usda.gov/geodata/edw/edw_resources/meta/S_USA.WildScenicRiver.xml' target='_blank' rel='nofollow ugc noopener noreferrer'>Metadata</a>

Tags: blm, fs, fws, hydrography, inland-waters, nhd, nps, open-data, recreation, river, scenic, wild, wild-and-scenic-rivers
Organization: Department of Agriculture
SeedChaser - Version 2.0

<p>Knowledge of the vertical distribution of surface residues, chemicals, or seeds following tillage operations is of paramount importance to a wide variety of soil research areas. SeedChaser is a 1-D empirical vertical soil tillage distribution model with 1 cm grid spacing that predicts vertical redistribution of weed seeds following user selected (a) sequences of tillage implements, and (b) initial seed distribution values. Results of this model are particularly suited for weed seed emergence modeling. However, the model can be adapted easily to any surface broadcasted agrochemical or incorporated residues. The present model can handle up to twenty passes of user selected sequences of sixteen different implements. </p>
<p>Majority of prior models examined only the impact of a more limited list of implements at much larger depth intervals, which reduced the predictability of fine-scale vertical movement that may be needed for simulating movements of seeds or chemical granules. SeedChaser consolidates the results from these previous models along with new data on conservation tillage implements into a prediction tool that would have applications both in weed science, as well as other soil research areas.</p>
<p>This model was developed in JAVA, is simple to use, and runs on multiple platforms (e.g. Mac, PC, Sun). </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: SeedChaser - Version 2.0.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=84&modecode=50-60-05-00">https://www.ars.usda.gov/research/software/download/?softwareid=84&modecode=50-60-05-00</a> </p><p>download page</p></li></ul><p></p>

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

<p>iFEAT (iFARM Economic Analysis Tool) is a spreadsheet based tool developed to allow the user to assess current and potential management options for economic sustainability. The user can evaluate lease arrangements, input costs, government programs, and insurance options to arrive at the best economic combination of these variables.</p>
<p>iFEAT is a user-friendly spreadsheet tool for helping no-till farmers—who often have higher fertilizer costs—quickly assess the economic benefits of various leasing and management options. The spreadsheet provides information on costs and net returns for different management alternatives, enabling them to assess the potential economic outcomes of management changes. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: iFEAT download page.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=240&modecode=30-12-30-25">https://www.ars.usda.gov/research/software/download/?softwareid=240&modecode=30-12-30-25</a> </p></li></ul><p></p>

Tags: computer-software, economic-analysis, economic-sustainability, farmers, fertilizers, financial-economics, governmental-programs-and-projects, input-costs, insurance, leasing, models, no-tillage
Organization: Department of Agriculture
Global RainSIM - Version 1.0

<p>The purpose of this tool is to estimate daily precipitation patterns for a yearly cycle at any location on the globe. The user input is simply the latitude and longitude of the selected location. There is an embedded Zip Code search routine to find the latitude and longitude for US cities.</p>
<p>GlobalRainSIM forecasts the daily rainfall based upon two databases.The first was the average number of days in a month with precipitation (wet days) that were compiled and interpolated by Legates and Willmott (1990a and 1990b) with further improvements by Willmott and Matsuura (1995). The second database was the global average monthly precipitation data collected 1961-1990 and cross-validated by New et al. (1999). These two datasets were then used to establish the monthly precipitation totals and the frequency of precipitation in a month. The average precipitation event was calculated as the monthly mean divided by the number of wet days. This mean value was then randomly assigned to a day of the month looping through the number of wet days. In other words, if the average monthly rainfall was 10 mm/month with 5 average wet days, each rain event was 2 mm. This amount (2 mm) was then randomly assigned to 5 days of that month. The advantage of this tool is that a typical pattern of precipitation can be simulated for any global location arriving at an •average year• as a baseline case for comparison. This tool also outputs the daily rainfall as a file or can be easily embedded within another program. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Global RainSIM Verson 1.0.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=227&modecode=50-60-05-00">https://www.ars.usda.gov/research/software/download/?softwareid=227&modecode=50-60-05-00</a> </p><p>download page</p></li></ul><p></p>

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

<p>The findmap.f90 program aligns sequence reads to reference map, calls previous variants, and identifies new variants. Program and download information can be found at the Animal Improvement Program (AIP) web site: <a href="http://aipl.arsusda.gov/software/findhap">http://aipl.arsusda.gov/software/findhap</a></p>
<p>Sequencing research requires efficient computation. Few programs use already known information about DNA variants when aligning sequence data to the reference map. New program findmap.f90 reads the previous variant list before aligning sequence, calling variant alleles, and summing the allele counts for each DNA source in a single pass. Advantages are faster processing, more precise alignment, more useful data summaries, more compact output, and fewer steps. Programs findmap and BWA were compared using simulated paired end reads of length 150 from fragments of length 1,000 at random locations within the UMD3.1 bovine reference assembly. Each base had 1% probability of error and 1% probability of missing. The 39 million variants from run 5 of the 1,000 bull genomes project were included, with every other variant set to reference or alternate. With 1 processor, BWA required 629 minutes per 1X for alignment, whereas findmap required 12 minutes per 1X for alignment and variant calling. Percentage of correctly mapped reads was 90.5% from BWA and 92.9% from findmap. Variant calls were output by findmap only for the 88.2% of pairs where both ends were located within the fragment length and of opposite orientation. Percentages of variants called correctly were 99.8% for SNPs and 99.9% for deletions, while insertions had 99.9% of alternate calls correct but only 98.6% of reference calls. Memory required by BWA was 4.6 Gbytes / processor, whereas findmap required 46 Gbytes that could be shared by multiple processors. Simultaneous alignment and variant calling is an efficient and accurate strategy. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: FINDMAP.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=495&modecode=80-42-05-30">https://www.ars.usda.gov/research/software/download/?softwareid=495&modecode=80-42-05-30</a> </p><p>download page</p></li></ul><p></p>

Tags: alleles, animals, autosomes, bulls, computer-software, computers, dna, genome, heterozygosity, homozygosity, humans, memory, mitochondrial-dna, models, probability, reading, single-nucleotide-polymorphism
Organization: Department of Agriculture
SNPdb: Haplotype Polymorphism in Polyploid Wheats and their Diploid Ancestors

<p>This is a tool to discover and map single nucleotide polymorphisms in tetraploid and hexaploid wheat and to characterize genetics and structure of the genepools of wheat and wheat diploid ancestors. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Web Page.</p> <p>File Name: Web Page, url: <a href="https://wheat.pw.usda.gov/snpworld/Search">https://wheat.pw.usda.gov/snpworld/Search</a> </p></li></ul><p></p>

Tags: ars, data-gov, genetics-genomics-breeding
Organization: Department of Agriculture
PhotoSim

<p>PhotoSim: Leaf Photosynthesis Model for Floriculture Crops program models the photosynthetic response of 13 floriculture crops to light, temperature, or carbon dioxide (CO2) and allows users to estimate the impact of adjusting their greenhouse environment. You can predict the impact on photosynthesis for different management changes (shading, supplemental high pressure sodium lighting, CO2 injection,or heating or cooling). </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: PhotoSim .</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/midwest-area/wooster-oh/application-technology-research/docs/photosim-leaf-photosynthesis-model-for-floriculture-crops/">https://www.ars.usda.gov/midwest-area/wooster-oh/application-technology-research/docs/photosim-leaf-photosynthesis-model-for-floriculture-crops/</a> </p><p>download page: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=447">https://www.ars.usda.gov/research/software/download/?softwareid=447</a></p></li></ul><p></p>

Tags: carbon-dioxide, computer-software, floriculture-crops, greenhouses, heat, leaves, lighting, models, photosynthesis, shade, sodium, temperature
Organization: Department of Agriculture
AgroEcosystem Performance Assessment Tool

<p>The AgroEcosystem Performance Assessment Tool is a computer program used to evaluate the agronomic and environmental performance of management practices in long-term agroecosystem experiments.  The program employs a simple scoring method to quantify the performance of management practices using indicators grouped within agroecosystem functions.  Management practices are evaluated on a relative basis using the method, thereby internalizing comparisons.  Because of its specialized application to long-term experiments, the program is designed primarily for use by agricultural researchers. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: AgroEcosystem Performance Assessment Tool download page.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=365&modecode=30-64-05-00">https://www.ars.usda.gov/research/software/download/?softwareid=365&modecode=30-64-05-00</a> </p></li></ul><p></p>

Tags: agroecosystems, computer-software, environmental-performance, long-term-experiments, models, natural-resources-earth-and-environmental-sciences
Organization: Department of Agriculture