AndreaBozzo/ceres-open-data-index huggingface dataset:
Data from: Changes in plant architecture in Brazilian peppertree damaged by the biological control agent, <i>Pseudophilothrips ichini</i> Hood (Thysanoptera: Phlaeothripidae)

<p dir="ltr">These data come from a roughly 4-year study on the growth response of a highly invasive woody plant to the damage induced by its biological control agent (an insect) and to soil fertilizer levels. The study design was an interrupted time series in which data were collected from plants for 2 years ("pre"), agents were introduced, and data collection continued for 2 years with sustained agent releases ("post"). Each month, stem tip counts and other measurements were collected from roughly 200 plants: 100 in each of two garden plots (IPRL and UF/IRREC). As plants grew larger (eventually to ~250 cm tall), data collection was spaced to roughly every 2 months and some replicates within each treatment were dropped. In addition to the "interruption" of introducing the agents, the other treatment was the addition of various concentrations of liquid fertilizer to the soil throughout the study. While there were no control plants that did not receive insects, each plant was followed over the course of the pre-post design experiment and Bayesian mixed modelling was used to interpret the effect of releasing the insect on how plant growth parameters changed over time and under different fertilizer levels. We have included raw data in .csv and .xlsx formats, one set for each garden plot as plots were analyzed separately. The Excel files have notes in the header column providing more information about each variable. However, not all variables were analyzed in the published study. The R code is also attached, which runs the Bayesian analyses for each plot and each response variable of interest in the published study. Raw data are also provided for soil and foliar nitrogen content. Soil nitrogen was analyzed at both plots, but foliar nitrogen was only analyzed at one of the plots (IPRL).</p>

Tags: bayesian-mixed-model, foliar-nitrogen-n, interrupted-time-series-study, plant-demography, stem-tip-density, stem-tip-mortality
Organization: Department of Agriculture
Data from: Heritable differences in abundance of bacterial rhizosphere taxa are correlated with fungal necrotrophic pathogen resistance

<p>This Ag Data Commons submission includes the 94 sunflower paired-end sequencing FASTQ files, the corresponding 16S bacterial FASTQ files, and other relevant data to the study described below:</p>
<p>Host-microbe interactions are increasingly recognized as important drivers of organismal health, growth, longevity, and community-scale ecological processes. However, less is known about how genetic variation affects hosts' associated microbiomes and downstream phenotypes. We demonstrate that sunflower <em>Helianthus annuus</em> harbors substantial, heritable variation in microbial communities under field conditions. We show that microbial communities co-vary with heritable variation in resistance to root infection caused by the necrotrophic pathogen <em>Sclerotinia sclerotiorum</em>, and that plants grown in autoclaved soil showed almost complete elimination of pathogen resistance. Association mapping suggests at least 59 genetic locations with effects on both microbial relative abundance and <em>Sclerotinia</em> resistance. Although the genetic architecture appears quantitative, we have elucidated previously unexplained genetic variation for resistance to this pathogen. We identify new targets for plant breeding and demonstrate the potential for heritable microbial associations to play important roles in defense in natural and human-altered environments.</p>
<p>See README for details of each table in the spreadsheet and related information.</p>

Tags: 16s-and-its-amplicon, ars, association-mapping, bacteria, bioinformatics, community-ecology, data-gov, earth-science-agriculture-agricultural-plant-science-plant-breeding-and-genetics, genetic-variation, helianthus-annuus, heritable-resistance, host-microbe-interactions, microbial-community, nectrotrophic-pathogen, np301, pathogen-resistance, plant-breeding, quantitative-genetics, sclerotinia-sclerotiorum, soil-microbiome, sunflower
Organization: Department of Agriculture
Growth and Yield Data for the Bushland, Texas, Sorghum Datasets

<p>This dataset consists of growth and yield data for each season when sorghum [<em>Sorghum bicolor</em> (L.)] was grown at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU) research weather station, Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL). In the 1988, 1991, 1993, 1997, 1998, 1999, 2003 through 2007, 2014, and 2015 seasons (13 years), sorghum was grown on from one to four large, precision weighing lysimeters, each in the center of a 4.44 ha square field also planted to sorghum. The square fields were themselves arranged in a larger square with four fields in four adjacent quadrants of the larger square. Fields and lysimeters within each field were thus designated northeast (NE), southeast (SE), northwest (NW), and southwest (SW). Sorghum was grown on different combinations of fields in different years. When irrigated, irrigation was by linear move sprinkler system years before 2014, and by both sprinkler and subsurface drip irrigation in 2014 and 2015. Irrigation protocols described as full were managed to replenish soil water used by the crop on a weekly or more frequent basis as determined by soil profile water content readings made with a neutron probe to 2.4-m depth in the field. Irrigation protocols described as deficit typically involved irrigation at rates established as percentages of full irrigation ranging from 33% to 75% depending on the year.</p>
<p>The growth and yield data include plant population density, height, plant row width, leaf area index, growth stage, total above-ground biomass, leaf and stem biomass, head mass (when present), seed mass, and final yield. Data are from replicate samples in the field and non-destructive (except for final harvest) measurements on the weighing lysimeters. In most cases yield data are available from both manual sampling on replicate plots in each field and from machine harvest. Machine harvest yields are commonly smaller than hand harvest yields due to combine losses.</p>
<p>These datasets originate from research aimed at determining crop water use (ET), crop coefficients for use in ET-based irrigation scheduling based on a reference ET, crop growth, yield, harvest index, and crop water productivity as affected by irrigation method, timing, amount (full or some degree of deficit), agronomic practices, cultivar, and weather. Prior publications have focused on sorghum ET, crop coefficients, crop water productivity, and simulation modeling of crop water use, growth, and yield. Crop coefficients have been used by ET networks. The data have utility for testing simulation models of crop ET, growth, and yield and have been used for testing, and calibrating models of ET that use satellite and/or weather data.</p>
<p>See the README for descriptions of each data file.</p>

Tags: ars, data-gov, evapotranspiration, growth-and-yield, np211, sorghum-bicolor
Organization: Department of Agriculture
Data from: Mortality Dynamics of a Polyphagous Invasive Herbivore Reveal Clues in Its Agroecosystem Success

<p>Field-based, partial life table data for immature stages of silverleaf whitefly, <em>Bemisia argentifolii</em>, on 6 host plants including alfalfa, broccoli, spring and fall cantaloupe, cotton, ornamental lantana, and several species of annual weeds in Maricopa, Marana and Yuma Arizona, USA. Data were collected on a total of 73 individual cohorts (each replicated 4 times) from November 2000 to April 2003 at all three study sites. For each cohort, data were generated on approximately 400 individual insects (200 eggs and 200 first instar nymphs). Data provide the marginal, cause-specific mortality for eggs, and 1st, 2nd, 3rd, and 4th instar nymphs collectively and stage-specific marginal mortality for each stage over all causes. Mortality was characterized as caused by inviability (eggs only), dislodgement, predation, parasitism (nymphs only), desiccation, and unknown. Detailed methods can be found in Naranjo and Ellsworth 2005 (<em>Entomologia Experimentalis et Applicata</em> 116(2): 93-108; <a href="https://doi.org/10.1111/j.1570-7458.2005.00297.x">https://doi.org/10.1111/j.1570-7458.2005.00297.x</a> ; and Naranjo and Ellsworth 2017 (<em>Journal of Visualized Experiments</em>, 129; <a href="https://doi.org/10.3791/56150">https://doi.org/10.3791/56150</a>). The method takes advantage of the sessile nature of immature stages of this insect. Briefly, an observer follows individual eggs or settled first instar nymphs from natural populations on the underside of host plant leaves in the field with a hand lens and determines causes of death for each individual over time. Weather data was monitored using the University of Arizona AzMet system. Note that these life table data do not include adult mortality or reproduction. The life table data were used to generate survivorship curves for each cohort on each host plant based on a physiological time scale of accumulated degree-days above 10C from the initiation of each cohort.  </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Mortality causes over all immature life stages.</p> <p>File Name: MortalityCause.xlsx</p><p>Resource Description: Data of mortality causes over all immature life stages.</p></li><br><li><p>Resource Title: Mortality of each immature life stage over all causes.</p> <p>File Name: MortalityStage.xlsx</p><p>Resource Description: Data for mortality of each immature life stage over all causes.</p></li><br><li><p>Resource Title: Data for pest survivorship curves on each host plant.</p> <p>File Name: SurvivalCurves.xlsx</p><p>Resource Description: Data to generate survivorship curves for pest on each host plant.</p></li></ul><p></p>

Tags: agroecosystem, ars, bemisia-argentifolii, data-gov, decision-tree-partition-models, ecological-release, life-table, marginal-mortality, natural-enemies, survivorship
Organization: Department of Agriculture
SGA (farm)

<p><strong>What is Stored Grain Advisor?</strong></p>
<p>Stored Grain Advisor (SGA) is a decision support system for the managemement of insect pests of farm-stored wheat. SGA predicts the likelihood of insect infestation, and recommends preventative and remedial action. It also provides advice on how to sample and identify insect pests of stored wheat.</p>
<p>Computer models of insect population growth allow SGA to predict future insect populations in the grain bin, as well as the breakdown of insecticides, the effects of fumigation, and cooling the wheat with aeration. The ability of Stored Grain Advisor to graphically show insect population trends makes it a powerful educational tool.</p>
<p><strong>Requirements</strong></p>
<p>Version 3.04 runs under Microsoft Windows 98, 2000, XP, and 32 bit Vista.</p>
<p><strong>Instructions</strong></p>
<p>Remove any previous versions of SGA using the uninstaller included with the program.
Download SgaSetup.exe to your computer.
Run SgaSetup.exe and follow the Installer's instructions.
Delete SgaSetup.exe.</p>
<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: SGA (farm) download page.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=82&modecode=30-20-05-20" target="_blank">https://www.ars.usda.gov/research/software/download/?softwareid=82&modecode=30-20-05-20</a> </p></li></ul>

Tags: ars, data-gov, grain, insect-pests, wheat
Organization: Department of Agriculture
Data From: Microplate bioassays to examine effects of grapevine-isolated stilbenoids on survival of root knot nematodes

<p>This dataset consists of a data file with raw data from a bioassay that assessed the survival of root knot nematode (J2 life-stage) in the presence of different stilbenoid compounds, as well as another file showing summary descriptive statistics and a summary graph. The experiment consisted of counting the survival of J2 stage root knot nematodes in microplate wells with water amended with 0, 1.25, 2.5, 5, or 10 ppm of the stilbenoid monomer piceid, the stilbenoid dimer epsilon-viniferin, the stilbenoid trimer miyabenol C, or a mix of stilbenoid tetramers vitisin B and hopeaphenol. Counts were made at the beginning of the experiment and 1, 3, or 5 days later. The percent of surviving nematodes at day 5 was used to observe if the stilbenoid compounds would  have effects on the root knot nematodes.  </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: RootKnotBioassayData.</p> <p>File Name: RootKnotBioassayData.xlsx</p><p>Resource Description: Raw count data from an experiment assessing the mortality or survival of J2 root knot nematodes over time when exposed to piceid, epsilon-viniferin, miyabenol C, and vitisin B/hopeaphenol at 0, 1.25, 2.5, 5, or 10 ppm.</p></li><br><li><p>Resource Title: RootKnotBioassaySummary.</p> <p>File Name: RootKnotBioassaySummary.xlsx</p><p>Resource Description: Descriptive statistics (means and deviations) and ANOVA statistics for survival percentage data of root knot nematodes exposed to four different stilbenoid compounds at different concentrations 1, 3, or 5 days after initial exposure. A graph of survival at day 5 is also provided.</p></li></ul><p></p>

Tags: ars, data-gov, grapevine, np303, root-knot-nematode, stilbenoids
Organization: Department of Agriculture
Ring Nematode Induction of and Sensitivity to Grapevine Phenolic Compounds

<p>[NOTE - 5/31/2022: this dataset was updated to include two additional resources: <em>Ring Nematode Phenolic Project Materials</em> and <em>Methods and Ring nematode phenolic induction and sensitivity data summaries</em>. No other changes to the data were made.]</p>
<p>This dataset includes data collected from two experiments, one in 2018 and one in 2019, that examined the potential induction of phenolic compounds in the roots of grapevines fed upon by ring nematodes, <em>Mesocriconema xenoplax</em>. Furthermore, a bioassay on 96-well plates was performed to examine the ability of a subclass of phenolics in grapevines (i.e. stilbenoids available as monomers, dimers, trimers, or tetramers) to affect ring nematode mortality. There appeared no significant effects of ring nematode feeding on phenolic levels, nor did these compounds affect survival in the in vitro tests. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Ring Nematode Grapevine Phenolic Induction and Sensitivity.</p> <p>File Name: Ring Nematode- Phenolic Study.xlsx</p><p>Resource Description: This dataset includes two tabs. One tab involves data regarding phenolic compounds in grapevine roots that were healthy or infected by ring nematodes, in one of four different rootstock cultivars (two considered resistant and two considered susceptible). The other tab involves an in vitro study whereby ring nematodes were exposed to different phenolic compounds and mortality was assessed after 24 hours. </p></li><br><li><p>Resource Title: Ring Nematode Phenolic Project Materials and Methods.</p> <p>File Name: Ring Nematode Phenolic Project Materials and Methods.docx</p><p>Resource Description: This files contains a comprehensive Materials and Methods write-up to describe how the data were obtained for the project entitled "Ring nematode induction of and sensitivity to grapevine phenolic compounds", which is the dataset that this is filed under.</p></li><br><li><p>Resource Title: Ring nematode phenolic induction and sensitivity data summaries.</p> <p>File Name: Ring nematode phenolic induction and sensitivity data summaries.docx</p><p>Resource Description: This Word document provides two figures that summarize the data of the project entitled "Ring Nematode Induction of and Sensitivity to Grapevine Phenolic Compounds." The first Figure summarizes the data that involves phenolic compound analyses from healthy and infected roots. The second Figure summarizes the data from the study that examined mortality effects of stilbenoids on ring nematodes.</p></li></ul><p></p>

Tags: ars, data-gov, grapevine, np303, phenolics, ring-nematode, roots, stilbenoids
Organization: Department of Agriculture
Effect of Holstein genotype on immune response to an intramammary Escherichia coli challenge

<p>Since 1964, the University of Minnesota has selectively bred a Holstein herd to maintain genetically static, unselected Holsteins (UH). Comparison of these UH cows with contemporary Holstein (CH) has demonstrated that the UH cows not only produce less milk but also have fewer health concerns than their CH herdmates. The objective of this study was to determine the effects of Holstein genotype on innate immune response in an experimental intramammary <em>E. coli</em> challenge model. Primiparous UH (n= 5) and CH (n = 7) cows received 430 cfu E. coli strain P4 in 1 quarter. Blood samples were collected at 0, 0.5, 1, 2, 7d relative to E. coli infusion. RNA Sequencing was conducted using the HiSeq 2500 platform (Illumina, San Diego, CA) to generate an average of 46.96 ± 2.67 million 100 bp paired end reads per sample.</p>
<p>For more information about this dataset contact:
John Lippolis: john.lippolis@usda.gov
Hao Ma: hao.ma@usda.gov </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Effect of Holstein genotype on immune response to an intramammary Escherichia coli challenge.</p> <p>File Name: Supplemental Table 1.csv</p><p>Resource Description: The results of RNA sequencing analysis. The raw sequencing data were submitted to NCBI SRA database with reference PRJNA808034.</p></li></ul><p></p>

Tags: ars, data-gov, escherichia-coli, genotype, holstein, immune-response, mastitis, np103
Organization: Department of Agriculture
Agronomic Calendars for the Bushland, Texas Cotton Datasets

<p>This dataset consists of agronomic calendars for each growing season (year) when upland cotton [<em>Gossypium hirsutum</em> (L.)] was grown for fiber and seed at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU) research weather station, Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL). In 2000, 2001, 2008, 2020, and 2021, cotton was grown on four large, precision weighing lysimeters, each in the center of a 4.44 ha square field. In 2002, 2010, and 2012, cotton was grown on two large, precision weighing lysimeters and their surrounding 4.44 ha square fields. In 2003 and 2004, cotton was grown on only one large weighing lysimeter in rotation with sorghum. The four fields were contiguous. The fields were designated northeast (NE), southeast (SE), northwest (NW), and southwest (SW), and were themselves arranged in a larger square with the fields in four adjacent quadrants of the larger square. Irrigation was by linear move sprinkler system in from 2000 through 2012. In 2020 and 2021, the NE and SE fields were irrigated using subsurface drip irrigation (SDI), while the NW and SW fields were irrigated using a linear move system. Cotton was sometimes grown as a dryland crop, sometimes as a fully irrigated crop, and sometimes as a deficit irrigated crop. Irrigations designated as full were managed to replenish soil water used by the crop on a weekly or more frequent basis as determined by soil profile water content readings made with a neutron probe to 2.4-m depth in the field. Irrigations designated as deficit typically involved full irrigation to establish the crop. A crop calendar for each season lists by date the pertinent agronomic and maintenance operations (e.g., planting, thinning, fertilization, pesticide application, lysimeter maintenance, harvest). For each season there is one crop calendar for each two lysimeters (NE and SE, and/or NW and SW).
These datasets originate from research aimed at determining crop water use (ET), crop coefficients for use in ET-based irrigation scheduling based on a reference ET, crop growth, yield, harvest index, and crop water productivity as affected by irrigation method, timing, amount (full or some degree of deficit), agronomic practices, cultivar, and weather. Prior publications have focused on ET, crop coefficients, and crop water productivity. Crop coefficients have been used by ET networks. The data have utility for testing simulation models of crop ET, growth, and yield and have been used for testing, and calibrating models of ET that use satellite and/or weather data.</p>
<p>See the README for descriptions of each data file.</p>

Tags: agronomic-log, ars, cotton, cotton-fiber, cotton-yield, data-gov, evapotranspiration, np211
Organization: Department of Agriculture
SGS-LTER GIS layer with detailed information on Exclosures on Central Plains Experimental Range, Nunn, Colorado, USA 2012

<p>This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (<a href="http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429">http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429</a>). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection.
No Abstract Available </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Website Pointer to html file.</p> <p>File Name: Web Page, url: <a href="https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sgs&identifier=817">https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sgs&identifier=817</a> </p><p>Webpage with information and links to data files for download</p></li></ul><p></p>

Tags: ars, data-gov, geographic-information-systems, gis, np215, nsf-lterlong-term-ecological-research, usda-ars-natural-resources-and-sustainable-agricultural-systems-national-program-215-pasture-fo
Organization: Department of Agriculture
SGS-LTER GIS layer with detailed information on Landforms on Central Plains Experimental Range, Nunn, Colorado, USA 2012

<p>This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (<a href="http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429">http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429</a>). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection.
No Abstract Available </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Website Pointer to html file.</p> <p>File Name: Web Page, url: <a href="https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sgs&identifier=816">https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sgs&identifier=816</a> </p><p>Webpage with information and links to data files for download</p></li></ul><p></p>

Tags: ars, data-gov, geographic-information-systems, gis, np215, nsf-lterlong-term-ecological-research, usda-ars-natural-resources-and-sustainable-agricultural-systems-national-program-215-pasture-fo
Organization: Department of Agriculture