AndreaBozzo/ceres-open-data-index huggingface dataset:
Data from: Impact of <i>Aedes aegypti</i> V1016I and F1534C knockdown resistance genotypes on operational interventions

<p dir="ltr">Resistance to pyrethroids is common in <i>Aedes aegypti</i> populations. Mutations in the voltage gated sodium channel have an influence on the insecticide resistance (IR) phenotype. In much of the Western hemisphere, two of these knockdown resistance (<i>kdr)</i> mutations, V1016I and F1534C, are widely found and result in six commonly found <i>kdr</i> genotype combinations in field populations. Strong pyrethroid IR and the failure of permethrin treated uniforms have been linked to the presence of the homozygous double <i>kdr</i> genotype (IICC) but the effects of these various <i>kdr</i> combinations have not been rigorously examined. To better understand the impacts of these mutations<i>, </i>we isolated three <i>kdr</i> haplotypes (VF, VC, & IC) from a field collected strain to produce six <i>Ae. aegypti </i>isoline strains with all common <i>kdr</i> genotypes. We then characterized the effects of these <i>kdr</i> genotypes by CDC bottle bioassay and topical application and found increasing resistance to permethrin and deltamethrin as the number of IC haplotypes increased. Neither enzymatic activity nor malathion IR increased as pyrethroid IR increased. Field and wind tunnel spray of a pyrethrin formulation showed that even moderate resistance could significantly reduce knockdown and mortality. Studies with a synergized pyrethroid formulation showed effective recovery of mortality against all genotypes except for the IICC. In human bite studies, one or two IC haplotypes compromised the efficacy of permethrin treated fabrics. This study demonstrates that <i>kdr</i> mutations have distinct phenotypic effects in both the laboratory and operational interventions, and that the strength of pyrethroid resistance is linked to the number of IC haplotypes present in the <i>kdr </i>gene. Assessing <i>kdr</i> genotype is therefore critical for understanding target-site-mediated IR in <i>Ae. aegypti</i>.</p>

Tags: aedes-aegypti, insecticide-resistance, knockdown-resistance-kdr, operational-efficacy, voltage-gated-sodium-channel
Organization: Department of Agriculture
Data from: Isoerodent surfaces of the continental US for conservation planning with the RUSLE2 water erosion model

<p dir="ltr">This is the dataset contains data used to make Figures 4 and 5 and the final Erosivity data generated and evaluated in the study entitled: “Isoerodent surfaces of the continental US for conservation planning with the RUSLE2 water erosion model”</p><p><br></p><p dir="ltr">The citation for the publication is: H.G. Momm, R.R. Wells, R. ElKadiri, T. Seever, D. Yoder, R.P. McGehee, R.L. Bingner and C.J.G. Darnault. (2025). Isoerodent surfaces of the continental US for conservation planning with the RUSLE2 water erosion model. Catena, 253, pp. 108879. <a href="https://doi.org/10.1016/j.catena.2025.108879" target="_blank">https://doi.org/10.1016/j.catena.2025.108879</a></p><p dir="ltr">How the dataset was generated: These datasets were generated following the steps in the methodology described in the manuscript. The protocol used extends the standard RUSLE2 procedure to include the inclusion of small events, determination of spatially varying recurrence intervals, and consideration of two-axis trend interpolation enhanced with additional weighting accounting for data gaps. To generate this dataset, the following publicly available data sets were used as input: (a) 15min precipitation data from the U.S. National Oceanic and Atmospheric Administration (NOAA) – National Centers for Environmental Information, (b) elevation information from the Global Multi-resolution Terrain Elevation Data, (c) distance to the closest coast from the U.S. National Oceanic and Atmospheric Administration - National Ocean Service, and (d) 30-year annual precipitation normal from the Precipitation-elevation Regressions on Independent Slopes Model (PRISM) for 1991 to 2020. Complete description of steps and datasets can be found in the published manuscript.</p><p><br></p><p dir="ltr">Why the dataset was generated: These datasets were generated to evaluate the proposed methodology designed to generate continuous Erosivity (R) surfaces specifically for the U.S. Department of Agriculture - Revised Universal Soil Loss Equation, Version 2 (RUSLE2) water erosion model.</p>

Tags: erosivity, rusle2
Organization: Department of Agriculture
Data from: Crop Sequence affects horseweed density and productivity in oats

<p dir="ltr">Diversified crop rotations can provide many benefits that include greater yield stability, better nutrient cycling, and improved pest management. In a long-term experiment, we observed weed differences in oat that was the result of whether the previous crop was corn or grain sorghum. Horseweed, a common weed in North America, was more prevalent in oat when the previous crop was corn. We speculate that grain sorghum, considered to have allelopathic compounds, suppressed horseweed the following year better than corn. We show that crop sequence within diversified can result in distinct differences in weed presence and production.</p>

Tags: crop-rotation-strategies, horseweed-control, ltar, nebraska-usa, oats-avena-sativa
Organization: Department of Agriculture
National Invertebrate Genetic Resources

<p dir="ltr">Insects impact American agriculture both as destructive and beneficial organisms. Insect pests, parasites, predators, products, and pollinators are all economically important. It is critically important to distinguish between different species, races, stocks, strains, biotypes, and other genetic entities and to document their different interactions with agriculture and the environment.</p><p dir="ltr">The goals of the National Invertebrate Genetic Resources Program include:</p><ol><li>Preservation of reference specimens</li><li>Maintenance of genetically important germplasm</li><li>Documentation of specific insect stocks</li><li>Management of databases</li><li>Distribution of material to researchers and breeders<br>Resources in this dataset:<br></li><li><ul><li>Resource Title: National Invertebrate Genetic Resources.File Name: Web Page, url: <a href="https://www.ars-grin.gov/Collections#animal-germplasm" rel="noreferrer" target="_blank">https://www.ars-grin.gov/Collections#animal-germplasm</a>  </li></ul></li></ol><p><br></p>

Tags: ars, data-gov, np301, online-database
Organization: Department of Agriculture
Data from: Sugarcane Genotype by Environment interaction (G × E) in Clonal Trials in the U.S. Texas Rio Grande Valley

<p dir="ltr">The file “Texas Data Series 11-14.xlsx” contains field data from breeding plots in the later stage off station farms were used for this study. This included approximately 20-25 experimental genotypes from USDA-ARS at Canal Point (CP and CPCL), USDA-ARS Houma (Ho), Louisiana State University (L), Ho genotypes crossed at Canal Point (HoCP) and 2 check cultivars that were planted at 4-5 locations, and 2 check cultivars that were planted at 4-5 locations. These were planted in 4 planting series (2011 – 2014, hereafter, named as Series 11 to 14 (SERIES)) based on when the clones were received with 3 crops (plant cane-second ratoon) each except 2011 which had 4 crop cycles (plant cane-third ratoon). The years evaluated were 2015-2020. Field trial plantings, harvest and yield data were done according to Todd et al. (2019). Yield data included cane yield or tons cane per acre (TCA), sugar yield or tons sucrose per acre (TSA), and sucrose content or commercially recoverable sucrose or pounds of sucrose per ton of cane (CRS). Each planting series had unique sets of genotypes and locations, so analysis was done by series.</p><p dir="ltr">The file “Texas Ratooning data series 11-14” Utilized the same data as in “Texas Data Series 11-14.xlsx” but created the ratooning index for each yield component according to Dlamini et. al (2024).</p><p dir="ltr">The results from this study are in Todd et al. (In press.)</p><p><br></p><p dir="ltr">Dlamini NE, Franke AC, Zhou M (2024) Indices for measuring ratooning ability of sugarcane varieties. Crop Sci 64:667–677. DOI: 10.1002/csc2.21191</p><p dir="ltr">Todd JR, Hale AL, Pan Y.-B., Tew TL, Milligan SB, <a href="" target="_blank">Dufrene Jr EO, Duet Jr MJ, Verdun DL, Landry CJ, Grisham MP,</a> Comstock JC (2019) Registration of ‘HoCP 11‐537’ Sugarcane. J of Plant Regis 13(2):187-192</p><p dir="ltr">Todd JR, Arbelo OC, Hale AL, Pan Y-B, Dufrene EO, Jr, Verdun D., Momotaz A, Kimbeng CA, Waguespack HL, Jr., Scott, AW Jr.<sup>,</sup> Hernandez<sup> </sup>E, and Klostermann M. () Sugarcane Genotype by Environment interaction (G × E) in Clonal Trials in the U.S. Texas Rio Grande Valley. Euphytica</p>

Tags: sugarcane-agroindustry
Organization: Department of Agriculture
Data from: Full-length 16S rRNA sequencing on target microbe establishment in laboratory and mass-reared Mediterranean fruit fly

<p dir="ltr">Study aim was to determine establishment success of antibiotic resistance bacteria in laboratory and mass-reared Mediterranean fruit fly (<i>Ceratitis capitata</i>). Experiments conducted in Hilo, HI, USA by the USDA ARS. Datasets include two different datatypes: 1) data from plate counts (CFUs) on nutrient-rich and antibiotic-amended data and 2) amplicon sequence variant (ASVs) count data from full-length 16S rRNA sequencing using PacBio Kinnex mas-Seq on a PacBio Revio sequencer and associated taxonomy and .fasta files. Experiments were performed with two different fly lines, one maintained by the USDA ARS and another by California Department of Agriculture (CDFA). Experiments were performed with a target <i>Enterobacter </i>strain that was transformed with mScarlet and antibiotic resistance selection markers. Experiments evaluated the impact of fly age and inoculation formulation (via diet) on the conditions in which bacteria would be established under different dietary conditions. Data show that liquid diets support establishment of bacteria, regardless of age class and source. Sequence data suggest additional <i>Enterobacter </i>strains are present in flies beyond the target strain and these can be distinguished via full-length 16S rRNA sequencing, but not by shorter amplicon fragments.</p>

Tags: 16s-rrna, enterobacter, mediteranean-fruit-fly, microbiome
Organization: Department of Agriculture
Data from: Random forest regression to predict Farinograph traits from GlutoPeak output in wheat wild relative backcross lines

<p dir="ltr">Flour quality is a key breeding target in hard winter wheat cultivar development. The Farinograph is perhaps the most important device for assessing quality prior to cultivar release in the United States, but large sample size requirements and long test times make in impracticable for early-stage selection. We used random forest regression to predict key Farinograph parameters from novel features we calculated from the raw data output of the GlutoPeak, which requires less time and less sample, in a winter wheat population containing wild relative introgressions. Here, we present the raw GlutoPeak data and Farinograph data used in model development.</p><p dir="ltr">GlutoPeak output for 68 wheat samples, contained in folder "GP_upload". Some lines including wild relative introgressions. Files with the same number prior to the underscore represent multiple replications of the same sample - one file was randomly selected for model construction.<br><br>FarinoGraph output for 68 wheat samples, some lines including wild relative introgressions.</p>

Tags: glutopeak, wheat-flour-quality
Organization: Department of Agriculture
Weather data associated with sugarcane and sugar beet processing seasons and facilities in the United States

<p dir="ltr">This data is a collection of publicly available weather data for sugarcane and sugar beet processing facilities in the U.S. Sugarcane weather parameters include high temperature, low temperature, dew point, relative humidity, rain, and wind for the preceding day ("D-1") and current day ("D") associated with the given date. Sugar beet weather includes high temperature, low temperature, and precipitation for the given date. This data is used on conjunction with studies of sugar crop processing parameters, to explore influences that weather conditions have on sugarcane and sugar beet factory manufacturing productivity and raw sugar quality. Publications will be linked when available. This work is supported by USDA-ARS (Southern Regional Research Center), the American Sugar Cane League, and the Beet Sugar Development Foundation.</p>

Tags: raw-sugar, sugar-beet, sugarcane, weather
Organization: Department of Agriculture
Administrative Data Repository (ADR)

<p>ADR provides an authoritative data store for shared administrative, demographic, enrollment, and eligibility information which is managed as a corporate asset. This administrative database system offers mission-critical database support for all VA Medical 21st Century Core applications such as Enrollment Systems, Identity Management System, Community Care Program, Veterans's Choice program, President's Affordable Care Act project, Patient Advocacy Tracking System, Veterans 360, and others.</p>

Tags: adr, health
Organization: Department of Veterans Affairs
Eklof et al, 2025 dataset

The dataset provides an excel file summary of the information used to generate Figures 2 and 4 in the journal article. The other figures in the paper are not based on datasets. The data used to generated Figures 2 and 4 combinates information found in Table 1 of the main text and Tables S3 and S5 in the Supporting Information. Citation information for this dataset can be found in Data.gov's References section.

Tags: forestry-impact, mercury
Organization: U.S. Environmental Protection Agency
GHGSat_landfill_survey_Dataset

Dataset and data dictionary associated with the journal article titled “A High-resolution Satellite Survey of Methane Emissions from Sixty North American Municipal Solid Waste Landfills”, Krause M., Thoma, E.D. (corresponding author), Bryant, A., Brantley, H., MacDonald, M., Green, R., Thorneloe, S., ES&T, 2025, 59 (29), (Published July 7, 2025). ”, by Krause M., Thoma, E.D. (corresponding author), Bryant, A., Brantley, H., MacDonald, M., Green, R., Thorneloe, S., ES&T, 2025, 59 (29), (Published July 7, 2025). DOI: 10.1021/acs.est.5c01409. 

This dataset is associated with the following publication:
Krause, M., E. Thoma, A. Bryant, H. Brantley, M. MacDonald, R. Green, and S. Thorneloe-Howard. A High-Resolution Satellite Survey of Methane Emissions from 60 North American Municipal Solid Waste Landfills.   ACS ES&T Air. American Chemical Society, Washington, DC, USA,  15080-15091, (2025).

Tags: landfill, landfill-methane, satellite-observations
Organization: U.S. Environmental Protection Agency
NESDIS 14 km sea surface temperature for North America, 1993 to 2016

This product presents local sea surface temperatures (degrees C). It is a composite gridded-image derived from 8-km resolution SST observations collected by Advanced High Resolution Radiometer (AVHRR) and HIRS (High Resolution Infrared Radiation Sounder) instruments onboard NOAA and Metop-A satellites. It is generated every 48 hours for North America. SST is defined as the skin temperature of the ocean surface water. Data may be output as netCDF and other formats (GIF, ASCII, spreadsheet). The pixel resolution is .125 x .125 degrees.

Tags: 14 km, level 4, oceanography, satelliteobservation
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
AFSC/FMA/CAMS Data Objects

The CAMS system consists of a set of tables and packages that provide authentication services to all other North Pacific Groundfish and Halibut Observing Program (NPGOP) subsystems.

Tags: alaska fisheries science center, custom user authentication, doc/noaa/nmfs/afsc, national marine fisheries service, noaa, u.s. department of commerce
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
AFSC/FMA/Current Observer Data Interface

North Pacific Groundfish observers collect real-time fisheries dependent data.  This data is used to manage groundfish fisheries in domestic Alaskan waters.  Fisheries dependent data that is collected by observers is in its rawest form.  This data needs to be transformed so that end users of the data can use it for their specific needs.  The purpose of the observer interface (OBSINT) is to take observer raw data and turn it into useable data products for different users of the data.

Tags: 2008 and forward, ai, alaska fisheries science center, bs, bsai, current data, current observer data interface, doc/noaa/nmfs/afsc, fishery statistics, fishery-dependent, goa, national marine fisheries service, noaa, observer, tracked asset, u.s. department of commerce
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
AFSC/FMA/Electronic Monitoring (EM) Data Transformation

One type of electronic monitoring of Alaska groundfish catch has been conducted by Pacific States Marine Fisheries Commission using an electronic monitoring (EM) system to collect catch accounting data using video and sensor data of selected fishing vessels in Alaska.  Video recordings of fish catch composition aboard selected vessels are collected are stored on hard drives in an effort to track vessel catch and discards to accurately debit discarded catch from the individual fishing quota (IFQ) account of each account holder.  This information is collected in place of the sampling for species composition of the catch conducted by human at-sea catch monitors or observers.  Reviewers of the videos enter data from the drives and maintain data integrity and quality.

Raw, reviewed electronic monitoring data collected by Pacific States Marine Fisheries Commission must have additional data items added to it to conform to the standard format of data normally collected by Alaska observers in order for the data to be processed by catch accounting of the NMFS Alaska Regional Office.  The EM_OBSINT tables contain these transformed data.

These data, like data collected by Alaska groundfish observers, and transmitted electronically to the AFSC and are the source data for those interfaces used for fishery management, scientific inquiry and fishing activity monitoring by industry.

Tags: afsc, ai, alaska, alaska fisheries science center, aleutian islands, bering sea, bering sea and aleutian islands, bs, bsai, doc/noaa/nmfs/afsc, eez, electronic monitoring, exclusive economic zone, fishery-dependent, goa, gulf of alaska, national marine fisheries service, noaa, north pacific, tracked asset, u.s. department of commerce
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
AFSC/FMA/Observer Logistics System (OLS)

Alaska groundfish fisheries observers have been monitoring domestic groundfish fishing activities in the U.S. Exclusive Economic Zone (EEZ) off Alaska for over twenty years. The Fisheries Monitoring and Analysis Division staff has been responsible for training, briefing, debriefing and oversight of these observers.  The Observer Logistics System, launched in December 2011, is the current computer tool used for observer logistics and contains data on individual observers back to 1990.

Tags: afsc, alaska, alaska fisheries science center, anchorage, atsea, badge, briefing, briefing date, class, class date, contractor, cruise, debrief date, debriefing, decertification, deployment history, diembark date, doc/noaa/nmfs/afsc, dutch harbor, embark date, enrollment, evaluation, fishery-dependent, fma, grade, identification number, kodiak, logistics, midcruise, national marine fisheries service, noaa, north pacific (norpac) groundfish and halibut observer data dictionary december 2007 - present, npgop, observer, photograph, report, sampling history, schedule, seadays, seattle, staff, statistics, tracked asset, training, u.s. department of commerce, washington
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
AFSC/FMA/ATLAS Remote Client

Data is collected by observers on deck sheets and other types of paper forms and then the data is keyed into the ATLAS observer software.

Currently the ATLAS software consists of 3 parts: Oracle XE database, Oracle Apex, Oracle Rest Data Services (ORDS)

The FMA database consists of various data collected by fishery biologists while deployed on board commercial fishing vessels or at shoreside processing plants participating in the Bering Sea and Gulf of Alaska groundfish fisheries. Data collection activities began in 1973 and they continue to date. While deployed at their assignments, observers collect data on the catch size, fishing locations, catch composition, length frequencies, age structures, marine mammal interactions, and a variety of research projects.

Tags: alaska fisheries science center, atlas, atlas remote client, atsea, doc/noaa/nmfs/afsc, fishery-dependent, national marine fisheries service, noaa, observer, tracked asset, u.s. department of commerce
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
AFSC/FMA/North Pacific Observer Domestic Data Dictionary

From 1986 when the first NMFS observers were placed on domestic fishing vessels until the rollout of the re-engineered data model in December of 2007. Debriefed and validated observer data was maintained in the "Domestic" set of tables in the NORPAC database.

Tags: 1986, 2007, afsc, ai, alaska fisheries science center, bs, bsai, debriefed, doc/noaa/nmfs/afsc, domestic, domestic observer data dictionary, fishery management, fishery-dependent, fma, goa, national marine fisheries service, noaa, north pacific, observer, tracked asset, u.s. department of commerce
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
AFSC/FMA/Observer Declare and Deploy System (ODDS)

Groundfish vessels fishing in federal waters off Alaska are either in the "full coverage", "partial coverage", or "zero coverage" categories according to the monitoring specifications outlined each year in the Annual Deployment Plan.  Vessels in the Partial Coverage (PC) category are subject to random selection for observer coverage or electronic monitoring on a trip-by-trip basis.  PC vessels are  typically catcher vessels using longline, pot, or trawl gear and are required to log each trip into the Observer Declare and Deploy System (ODDS) prior to departure to determine if the trip is "selected" for observer coverage or electronic monitoring. If a trip is selected vessels must comply with all monitoring requirements on that trip.  Broadly speaking, the Observer Declare and Deploy System is the data system that houses all trip logging data and the associated monitoring rates, and provides a user interface for vessel owners to log trips and for the contracted observer provider(s) to assign observers to selected trips.

Tags: 2013, alaska fisheries science center, doc/noaa/nmfs/afsc, electronic monitoring, fishery-dependent, goa, gulf of alaska, national marine fisheries service, noaa, observer, observer restructure (odds), odds, partial coverage, restructure, tracked asset, trip selection, u.s. department of commerce, vessel selection
Organization: National Oceanic and Atmospheric Administration, Department of Commerce