AndreaBozzo/ceres-open-data-index huggingface dataset:
Data from: Population growth of native and invasive strains of the larger grain borer, Prostephanus truncatus on three maize hybrids

<p><strong>Insects</strong>
Two different populations of <em>Prostephanus truncatus</em> were used in the bioassays, one originated from the invaded range in Ghana, and the other from the native range in Mexico. Both populations were maintained in the Laboratory of Entomology and Agricultural Zoology (LEAZ), at the Department of Agriculture, Crop Production and Rural Environment, University of Thessaly, Greece, on whole maize kernels, at 26°C and 55% relative humidity (RH) and continuous darkness.
<strong>European Maize Hybrids</strong>
Three different maize hybrids (“PICO”, “HAMILTON”, and “AGN 672”) were obtained from American Genetics SA, Sindos, Greece. All hybrids were cultivated at Serres, in northern Greece according to the local farming practices. The hybrid “PICO” has a great production potential and it is adapted to multiple soil types and can produce high-weight grain. The hybrid “HAMILTON” is a dual-purpose hybrid, that has excellent early vigor and it is tolerant to fungi, and the hybrid “AGN 672” has excellent early vigor and it is also tolerant to fungi.
<strong>Population Growth on Different Maize Hybrids</strong>
Three different maize hybrids (PICO, Hamilton, and AGN 672) were used for experimentation. These hybrids were untreated and uninfested, and kept at ambient conditions until the beginning of the experiments. Before proceeding with the bioassays, grain moisture content (M.C.) was assessed, using a moisture meter (mini-GAC plus, Dickey-John Europe S.A.S., Colombes, France). Standardized plastic vials as in prior work (Quellhorst et al. 2023; Lampiri et al. 2022) were used here (3 cm in diameter, 8 cm in height). Vials were then filled with 20 g of one of the three maize hybrids with lids added after. The commodity was weighed with a Precisa XB3200D compact balance (Alpha Analytical Instruments, Gerakas, Greece). The upper rings of the vials were treated with Fluon (Northern Products Inc., Woonsocket, USA) to prevent insects from moving away from the grain and/or escaping. The top of each vial also had small holes punched to allow ventilation. Each vial then received 10 <em>P. truncatus</em> adults of mixed sex and age from one of two different strains. Two different populations of <em>P. truncatus</em> were used as mentioned above. The vials were placed inside incubators set at 30°C and 65% R.H. in continuous darkness. The vials were removed from the incubators after 45 d and adult progeny production was recorded. We also recorded the weight of frass, the number of insect-damaged kernels (IDK), and the total weight of the kernels within each vial. For each combination, i.e. hybrid × strain, there were n = 9 replicates.</p>

Tags: ars, cgahr, cgahr-lab-colony, data-gov, europe, ghana, greece, host-plant-resistance, hybrids, invasive-species, larger-grain-borer, maize, mexico, np304, population-growth, progeny-trial, prostephanus-truncatus, stored-grain, stored-product-pests
Organization: Department of Agriculture
Data from: Groundwater trend comparison during 1985 - 2019 in a critical groundwater area of northeastern Arkansas

<p>Groundwater level measurements (depth to groundwater) in a critical groundwater area in northeast Arkansas.  Group A well measurements are select United States Geological Survey (USGS) measurements during 1985-2012.  Group B well measurements are select USGS and United States Department of Agriculture-Agricultural Research Service Delta Water Management Research Unit well data in northeast Arkansas during 2012-2019. These data could be used to further understand groundwater levels and trends in a critical groundwater area of eastern Arkansas.</p>
<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Group A groundwater well coordinates and measurements 1985-2012.</p> <p>File Name: Group A Well Data.xlsx</p><p>Resource Software Recommended: Microsoft Exel,url: www.microsoft.com </p></li><br><li><p>Resource Title: Group B groundwater well coordinates and measurements 2012-2019.</p> <p>File Name: Group B Well Data.xlsx</p><p>Resource Software Recommended: Microsoft Excel,url: www.microsoft.com </p></li></ul>

Tags: arkansas, ars, data-gov, groundwater-levels, mississippi-river-valley-alluvial-aquifer, np211
Organization: Department of Agriculture
Bruner Farm Study for Resilient Economic Agricultural Practices in Ames, Iowa

<p>Bruner Farm Study for Resilient Economic Agricultural Practices in Ames, Iowa
Soil P analyzed by Bray P extractant.  Soil K analyzed by Ammonium Acetate extractant.  For MeasSoilCover estimates: Photos were taken with a Canon, 12.3 megapixel  EOS Rebel T3 mounted on a Van-Guard QS-46 large format quick shoe. The monopod that the amera/shoe assembly was attached to is a Wooster Sherlock model R056 telescoping pole.  A mounting racket and spirit level (part #’s MSRMB and MSRSLA respectively, available from Cropscan inc. <a href="http://www.cropscan.com/mpscs.html)" target="_blank">http://www.cropscan.com/mpscs.html)</a> were attached to the pole in a manner so that when the camera is mounted, and the bubble in the spirit level is centered, then the focal plane of the camera is perpendicular to the ground resulting in a nadir image of the ground beneath the camera.  The fully extended pole camera assembly was carried diagonally across each plot in field 70/71 an East to West or West to East transect with photos being taken every 9 paces.  The unit was angled in such a way that the shadow from the pole and camera was not included in the photo.  In the larger plots at the Uthe farm and the Poets facility, 30 to 40 paces were taken between each photo.  The self timer on the camera was set for a 10 second delay and the camera was focused before initiating the timer. In most instances, 10 seconds was ample time to maneuver the camera into position for the photo.  The cameras motion stabilizer function was turned on and the18mm zoom setting was always used to capture the maximum amount of area in each photo. Cold days, and wind speeds in excess of 30mph present a challenge.  Photos were downloaded from the camera with the EOS utility software supplied with the camera and analyzed with sample point version 1.51 with a grid size of 10x10 chosen.  A newer version of sample point is available at http://www.samplepoint.org/.</p> <div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Bruner Farm Study for Resilient Economic Agricultural Practices in Ames, Iowa.</p> <p>File Name: BrunerFarmStudy.zip</p></li></ul>

Tags: ammonium-acetate, ars, cameras, data-gov, environment, farming, models, np211, np212
Organization: Department of Agriculture
Data from: Antigenic distance between North American swine and human seasonal H3N2 influenza A viruses as an indication of zoonotic risk to humans

<p>An investigation of antigenic relationships between North American swine H3N2 influenza A viruses (IAV) and human seasonal vaccine strains was conducted to assess the zoonotic risk to humans. Human seasonal H3N2 vaccine strains isolated from 1973 to 2014 (n=20) were obtained from the World Health Organization Global Influenza Surveillance and Response Network through St. Jude Children’s Research Hospital to use for serological assays, such as hemagglutination inhibition (HI) assays. Human seasonal vaccine strains were cultured on MDCK cells or eggs and the HA gene was verified by sequencing on a Sanger method at National Animal Disease Center (NADC). A consensus HA sequence was generated using Geneious Software.</p>
<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Consensus sequences of hemagglutinin (HA) gene segments.</p> <p>File Name: Vincent_H3N2 HuVac strains.rtf</p><p>Resource Description: The data set includes sequences of hemagglutinin (HA) gene of human seasonal influenza A vaccine strains used in hemagglutination inhibition (HI) assays as references to assess the zoonotic risk of North American swine H3N2 strains to humans. The text file lists the consensus sequence of HA gene segment from each human H3N2 influenza A vaccine strain.
</p></li></ul>

Tags: antigenic-cartography, ars, data-gov, h3n2, human-vaccine, influenza, np103
Organization: Department of Agriculture
Data from: Genomic regions associated with Mycoplasma ovipneumoniae presence in nasal secretions of domestic sheep

<p>Genotypes of significant SNPs in all breed and individual breed analysis with detected <em>Mycoplasma ovipneumoniae</em> DNA copy number and log10 <em>M. ovipneumoniae</em> DNA copy number.   SNP is denoted in the column headers with its rs number and the first 7 SNP are from the all breed analysis, the following 9 SNP from the Rambouillet analysis, the following 3 from the Polypay analysis, and the final 9 from the Suffolk analysis. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Data from: Genomic regions associated with Mycoplasma ovipneumoniae presence in nasal secretions of domestic sheep.</p> <p>File Name: PLoS ONE Data.xlsx</p></li></ul><p></p>

Tags: ars, data-gov, domestic-sheep, gwas, mycoplasma-ovipneumoniae-detection
Organization: Department of Agriculture
Central Plains Experimental Range Study for Long-Term Agroecosystem Research in Nunn, Colorado

<p>Central Plains Experimental Range Study for Long-Term Agroecosystem Research in Nunn, Colorado
The Central Plains Experimental Range (CPER) is a site with the The Long-Term Agroecosystem Research (LTAR) Network, which consists of 18 sites across the continental United States (US) sponsored by the US Department of Agriculture, Agricultural Research Service, universities and non-governmental organizations. LTAR scientists seek to determine ways to ensure sustainability and enhance food production (and quality) and ecosystem services at broad regional scales.  They are conducting common experiments across the LTAR network to compare traditional production strategies (“business as usual or BAU) with aspirational strategies, which include novel technologies and collaborations with farmers and ranchers. Within- and cross-site network success towards achieving the desired outcomes of enhancing quality food production and reducing environmental impact requires that LTAR scientists and collaborators have well-timed access to various data.  We are striving to create opportunities to package and share long-term legacy observations from each site, with new data and metadata in useable, well documented and consistent formats for them.</p> <div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Nunn, CO Central Plains Experimental Range Study (CONUCPER) CSV data.</p> <p>File Name: CONUCPER_csv_data.zip</p><p>Resource Description: CSV format data on Experimental Units, Field Sites, Grazing Plants, Grazing, Persons, Treatments, Weather Daily, Weather Station.</p></li></ul>

Tags: agriculture, ars, biomass, crop-yields, data-gov, environment, farming, np216, plants
Organization: Department of Agriculture
Data from: Whole Genome Sequences of the Raspberry and Strawberry Pathogens Phytophthora rubi and P. fragariae

<p><em>Phytophthora rubi</em> and <em>P. fragariae</em> are two closely related soil-borne oomycete plant pathogens that exhibit strong morphological and physiological similarities but are specialized to infect different hosts of economic importance, namely, raspberry and strawberry. Here, we report the draft genome sequences of these two <em>Phytophthora</em> species as a first step toward understanding the genomic processes underlying plant host adaptation in these pathogens. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Whole Genome Sequences of the Raspberry and Strawberry Pathogens Phytophthora rubi and P. fragariae.</p> <p>File Name: Web Page, url: <a href="https://doi.org/10.1094/MPMI-04-17-0081-A">https://doi.org/10.1094/MPMI-04-17-0081-A</a> </p><p>Data links from the paper can be found in the related content section of this record. </p></li></ul><p></p>

Tags: ars, data-gov, genome-sequences, p-fragariae, pathogens, phytophthora-rubi, plants, soil
Organization: Department of Agriculture
Estimated spring crop yields using Flex Cropping Tool

<p>Average estimated yields and associated CV values for current (2018) model runs. Based on work done by Harsimran Kaur et al in 2017.  The following is from her thesis:

Agro-ecological classes (AECs) of dryland cropping systems in the inland Pacific Northwest have been predicted to become more dynamic with greater use of annual fallow under projected climate change. At the same time, initiatives are being taken by growers either to intensify or diversify their cropping systems using oilseed and grain legume crops. The main objective of this study was to use a mechanistic model (CropSyst) to provide yield and soil water forecasts at regional scales which could compare fallow versus spring crop choices (flex/opportunity crop). Model simulations were based on historic weather data (1981-2010) as well as combined with actual year weather data for simulations at pre-planting dates starting in Dec. for representative years. Yield forecasts of spring pea, canola and wheat were compared to yield simulations using only weather of the representative year via linear regression analysis to assess pre-plant forecasts. Crop yield projections on pre-plant forecast date of Feb 1st had higher R2 with yield simulated using actual years weather data and lower CVs across the region as compared to forecasts based on historic weather data and other pre-season forecast dates (Dec. 1st and Jan. 1st).  Therefore, Feb. 1st was considered the most reliable time to predict yield and other relevant outputs such as available water forecasts on a regional scale. Regional forecast maps of predicted spring crop yields and CVs showed ranges of 1 to 4367 kg/ha and 11 to 293% for spring canola, 72 to 2646 kg/ha and 11 to 143% for spring pea and 39 to 5330 kg/ha and 11 to 158% for spring wheat across study region for a representative year. These data combined with predicted available water after fallow and following spring crop yield as well as estimates of winter wheat yield reduction would collectively serve as information contributing to decisions related to crop intensification and diversification.</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/459d2dba-a346-4e54-9750-ef3178c18f38" target="_blank">https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/459d2dba-a346-4e54-9750-ef3178c18f38</a> </p></li></ul>

Tags: ars, biota, data-gov, environment, farming
Organization: Department of Agriculture
LTAR Walnut Gulch Experimental Watershed DAP GIS Layers

<p>The USDA-ARS Southwest Watershed Research Center (SWRC) operates the Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona as an outdoor laboratory for studying semiarid rangeland hydrologic, ecosystem, climate, and erosion processes.

Since its establishment in 1953, the SWRC in Tucson, Arizona, has collected, processed, managed, and disseminated high-resolution, spatially distributed hydrologic data in support of the center’s mission. Data management at the SWRC has evolved through time in response to new computing, storage, and data access technologies. In 1996, the SWRC initiated a multiyear project to upgrade rainfall and runoff sensors and convert analog systems to digital electronic systems supported by data loggers. This conversion was coupled with radio telemetry to remotely transmit recorded data to a central computer, thus greatly reducing operational overhead by reducing labor, maintenance, and data processing time. A concurrent effort was initiated to improve access to SWRC data by creating a system based on a relational database supporting access to the data via the Internet. An SWRC team made up of scientists, IT specialists, programmers, hydrologic technicians, and instrumentation specialists was formed. This effort is termed the Southwest Watershed Research Center Data Access Project (DAP).

The goal of the SWRC DAP is to efficiently disseminate data to researchers; land owners, users, and managers; and to the public. Primary access to the data is provided through a Web-based user interface. In addition, data can be accessed directly from within the SWRC network. The first priority for the DAP was to assimilate and make available rainfall and runoff data collected from two instrumented field sites, the WGEW near Tombstone, Arizona, and the Santa Rita Experimental Range (SRER) south of Tucson, Arizona.

This web map describes the associated GIS layers.</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/fe4ac74f13484a169899b166159e0bb5" target="_blank">https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/fe4ac74f13484a169899b166159e0bb5</a> </p></li></ul>

Tags: ars, biota, boundaries, data-gov, ecological-sites, flumes, gages, geology, geomorphology, location, np211, streamlines, vegetation
Organization: Department of Agriculture
PhenoCam images from JERNOVEL site, Jornada Experimental Range, New Mexico, USA since 2019

<p>This data set consists of repeat digital imagery from the tower-mounted digital cameras (hereafter, PhenoCams) at the Jornada Experimental Range. JER is a member of the PhenoCam network, which has as its mission to serve as a long-term, continental-scale, phenological observatory. Imagery is uploaded to the PhenoCam server every 30 minutes. The archived images provide a permanent record that can be visually-inspected to determine the phenological state of the vegetation at any point in time. Vegetation greenness metrics (e.g., GCC) derived from the ratio of the green color band to sum of red, green, and blue color bands serve as proxies for vegetation greenness.  Greenness metrics can be extracted from the images using simple image processing methods in 1-day or 3-day increments.</p>
<p>This dataset is available to the public and may be freely downloaded. Please keep the designated Contact person informed of any plans to use the dataset. Consultation or collaboration with the original investigators is strongly encouraged. Publications and data products that make use of the dataset must include proper acknowledgement.</p>
<p>The development of PhenoCam has been supported by multiple entities. Those include the Northeastern States Research Cooperative, NSF’s Macrosystems Biology program (award EF-1065029), DOE’s Regional and Global Climate Modeling program (award DE-SC0016011), the US National Park Service Inventory and Monitoring Program, the USA National Phenology Network (grant number G10AP00129 from the United States Geological Survey), and is currently supported by the Department of Agriculture (USDA) Agricultural Research Service.</p>
<p>This research is a contribution from the Long-Term Agroecosystem Research (LTAR) network. LTAR and the Jornada Experimental Range are supported by the United States Department of Agriculture (USDA) Agricultural Research Service.</p>

Tags: ars, data-gov, digital-image, long-term-monitoring-sites, ltar, new-mexico, np216, phenocam, phenology, primary-productivity
Organization: Department of Agriculture
Data from: On-farm wildflower plantings generate opposing reproductive outcomes for solitary and bumble bee species

<p dir="ltr">Pollinator habitat can be planted on farms to enhance floral and nesting resources, and subsequently, pollinator populations. There is ample evidence linking such plantings to greater pollinator abundance on farms, but less is known about their effects on pollinator reproduction. We placed <i>Bombus impatiens</i> Cresson (Hymenoptera: Apidae) and <i>Megachile rotundata</i> (F.) (Hymenoptera: Megachilidae) nests out on 19 Mid-Atlantic farms in 2018, where half (n=10) the farms had established wildflower plantings and half (n=9) did not. <i>Bombus impatiens</i> nests were placed at each farm in spring and mid-summer and repeatedly weighed to capture colony growth. We quantified the relative production of reproductive castes and assessed parasitism rates by screening for conopid fly parasitism and <i>Nosema</i> spores within female workers. We also released <i>M. rotundata</i> cocoons at each farm in spring and collected new nests and emergent adult offspring over the next year, recording female weight as an indicator of reproductive potential and quantifying <i>Nosema</i> parasitism and parasitoid infection rates. <i>Bombus impatiens</i> nests gained less weight and contained female workers with <i>Nosema</i> spore loads over 150x greater on farms with wildflower plantings. In contrast, <i>M. rotundata</i> female offspring weighed more on farms with wildflower plantings and marginally less on farms with honey bee hives. We conclude that wildflower plantings likely enhance reproduction in some species, but that they could also enhance microsporidian parasitism rates in susceptible bee species. It will be important to determine how wildflower planting benefits can be harnessed while minimizing parasitism in wild and managed bee species.</p>

Tags: bombus-impatiens-cresson, megachile-rotundata, nosema, wildflower-planting
Organization: Department of Agriculture
PhenoCam images from JERGRASSLAND site, Jornada Experimental Range, New Mexico, USA since 2019

<p>This data set consists of repeat digital imagery from the tower-mounted digital cameras (hereafter, PhenoCams) at the Jornada Experimental Range. JER is a member of the PhenoCam network, which has as its mission to serve as a long-term, continental-scale, phenological observatory. Imagery is uploaded to the PhenoCam server every 30 minutes. The archived images provide a permanent record that can be visually-inspected to determine the phenological state of the vegetation at any point in time. Vegetation greenness metrics (e.g., GCC) derived from the ratio of the green color band to sum of red, green, and blue color bands serve as proxies for vegetation greenness.  Greenness metrics can be extracted from the images using simple image processing methods in 1-day or 3-day increments.</p>
<p>This dataset is available to the public and may be freely downloaded. Please keep the designated Contact person informed of any plans to use the dataset. Consultation or collaboration with the original investigators is strongly encouraged. Publications and data products that make use of the dataset must include proper acknowledgement.</p>
<p>The development of PhenoCam has been supported by multiple entities. Those include the Northeastern States Research Cooperative, NSF’s Macrosystems Biology program (award EF-1065029), DOE’s Regional and Global Climate Modeling program (award DE-SC0016011), the US National Park Service Inventory and Monitoring Program, the USA National Phenology Network (grant number G10AP00129 from the United States Geological Survey), and is currently supported by the Department of Agriculture (USDA) Agricultural Research Service.</p>
<p>This research is a contribution from the Long-Term Agroecosystem Research (LTAR) network. LTAR and the Jornada Experimental Range are supported by the United States Department of Agriculture (USDA) Agricultural Research Service.</p>

Tags: ars, data-gov, digital-image, long-term-monitoring-sites, ltar, new-mexico, np216, phenocam, phenology, primary-productivity
Organization: Department of Agriculture