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54 results for “rye”
Rye Reference NLRome
<p>Annotation of nucleotide-binding leucine-rich repeat, NB-LRR, or NLR, the major family of resistance genes, in the recent 'Lo7' and 'Weining' rye reference genomes. </p> <p>Shared in the hope that it provides a valuable and easily-accessible resource for further studies in the NLRome of rye and breeding of novel resistant cultivars.</p>
Rye microgrid load and generation data, and meteorological forecasts.
<p>This dataset contains timeseries for Rye Microgrid, Trondheim, Norway. The timeseries include solar and wind power generation, consumption and historical weather forecasts.</p> <p>From <a href="https://github.com/TronderEnergi/tronderenergi-ai-hackathon-2021">https://github.com/TronderEnergi/tronderenergi-ai-hackathon-2021</a>:</p> <p><em>"The Rye microgrid is a pilot within the EU research project REMOTE. It is a small microgrid placed at Langørgen, in the outskirts of Trondheim, and is a small energy system designed to supply electricity to a modern farm and three households. The REMOTE projects goal for Rye Microgrid is to run the system in islanded mode.</em></p> <p><em>The system has two sources of generation – a wind turbine and a rack of PV panels. In addition, the system has two storages – a battery with high charge and discharge response, but with limited storage and losses, and a hydrogen energy system, with lower charge and discharge rates, higher losses and storage capacity. When you want to charge the hydrogen system, electricity is used to run an electrolyser that makes hydrogen from water and stores the resulting hydrogen in a tank. The process can be reversed by producing electricity from hydrogen using a fuel cell. (...)</em></p> <p><em>Morover, when local production or discharges from storages are not sufficient to cover the demand, the microgrid can draw electricity from the grid at some costs."</em></p> <p> </p> <p>For further details, see: <a href="https://www.remote-euproject.eu/remote18/rem18-cont/uploads/2019/03/REMOTE-D2.2.pdf">https://www.remote-euproject.eu/remote18/rem18-cont/uploads/2019/03/REMOTE-D2.2.pdf</a> and <a href="https://github.com/TronderEnergi/tronderenergi-ai-hackathon-2021">https://github.com/TronderEnergi/tronderenergi-ai-hackathon-2021</a></p> <p>rye_generation_and_load.csv is a comma-separated csv-file with the following columns (all values in <em>kW </em>and time as UTC):</p> <ul> <li>Consumption: Consumption of loads in system (residential and agriculture).</li> <li>Solar: Total production from all solar PV racks.</li> <li>Wind: Power production from wind turbine.</li> </ul> <p>met_data.h5: Contains historical weather forecasts data from The Norwegian Meteorological Institute (met.no) updated every 6 hours for the given location. The file is in hdf5 format. The forecasts include the following parameters: air_pressure_at_sea_level [Pa], air_temperature_2m [K], cloud_area_fraction [pu], integral_of_surface_downwelling_shortwave_flux_in_air_wrt_time [J/m<sup>2</sup>s], wind_direction_10m [deg], wind_speed_10m [m/s]</p> <p>The structure of the file is as follows:</p> <ul> <li>lat63_41_lon10_11 (coordinates) <ul> <li>[forecasted parameter] <ul> <li>forecast <ul> <li>2020-01-01T00Z (time forecast was issued) <ul> <li>axis0 (columns, index where each represent a point in a geographical grid. For example if axis=0,1,2,3, the tables contains the forecasts for the four closes points to the microgrid.)</li> <li>axis1 (rows, timestamps)</li> <li>block0_items (equal to axis0)</li> <li>block0_values (matrix, forecast values)</li> </ul> </li> </ul> </li> </ul> </li> </ul> </li> </ul>
Herbarium specimen image of Petrophile septemfida Rye & K.A.Sheph., part of the collection of Royal Botanic Gardens, Kew
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.<br>- A lossless TIFF image from which the JPEG image has been derived.<br>- Two PNG files containing segmented image overlays of the scanned herbarium sheet. The _all extension indicates that all labels, color charts and pieces of text have received a different color against a black background color. The _sel extension indicates that these elements are white if they're barcode labels, yellow if they're color charts and red if they're anything else.
Early-season biomass and weather enable robust cereal rye cover crop biomass predictions
<p>Farmers need accurate estimates of winter cover crop biomass to make informed decisions on termination timing or to estimate potential release of nitrogen from cover crop residues to subsequent cash crops. Utilizing data from an extensive experiment across 11 states from 2016 to 2020, this study explores the most reliable predictors for determining cereal rye cover crop biomass at the time of termination. Our findings demonstrate a strong relationship between early-season and late-season cover crop biomass. Employing a random forest model, we predicted late-season cereal rye biomass with a margin of error of approximately 1,000 kg ha<sup>-1</sup> based on early-season biomass, growing degree days, cereal rye planting and termination dates, photosynthetically active radiation, precipitation, and site coordinates as predictors. Our results suggest that similar modeling approaches could be combined with remotely sensed early-season biomass estimations to improve the accuracy of predicting winter cover crop biomass at termination for decision support tools.</p>
U.S. cereal rye winter cover crop growth database
<p>Winter cover crop performance metrics (i.e., vegetative biomass quantity and quality) affect ecosystem services provisions but vary widely due to differences in agronomic practices, soil properties, and climate. Cereal rye (Secale cereale) is the most common winter cover crop in the United States due to its winter hardiness, low seed cost, and high biomass production. We compiled data on cereal rye winter cover crop performance metrics, agronomic practices, and soil properties across the eastern half of the United States. The dataset includes a total of 5,695 cereal rye biomass observations across 208 site-years between 2001–2022 and encompasses a wide range of agronomic, soil, and climate conditions. Cereal rye biomass values had a mean of 3,428 kg ha−1, a median of 2,458 kg ha−1, and a standard deviation of 3,163 kg ha−1. The data can be used for empirical analyses, to calibrate, validate, and evaluate process-based models, and to develop decision support tools for management and policy decisions.</p>
Rye microgrid historical weather forecasts and stochastic scenarios
<p>This datasets connects historical weather forecasts from the Norwegian Meteorological Institute (met.no) and historical observations from Rye microgrid (https://doi.org/10.5281/zenodo.4448894).</p> <p>Each csv file represents a historical weather forecast for approximately 60 hours ahead. Each csv-file also contains the corresponding observations in the same time interval. Finally, the files also contain load, wind generation and solar PV generation predicitons.</p> <p>The predictions are generated using gradient boosting. The predictions ending with "_ls" are based on least square. The predictions ending with "_quantile_i" represent a quantile prediction. For example, "wind_quantile_2" means that there is a 20% probability the wind will be less than this value.</p> <p>The gradient boosting predictor has been trained to predict the wind power, solar power and load using the explanatory variables below:</p> <p>Solar PV: Cloud area fraction, initial production, clear sky production and forecast look-ahead time</p> <p>Wind power: wind speed, wind direction, wind power converted from wind speed forecast, initial production and forecast look-ahead time</p> <p>Load: hour of day, month of year</p>
Selective sweeps identification in distinct groups of cultivated rye (Secale cereale L.) germplasm provides potential candidate genes for crop improvement
<p><strong>Background</strong></p> <p>During domestication and subsequent improvement, plants were subjected to intensive positive selection for desirable traits. Identification of selection targets is important with respect to the future targeted broadening of diversity in breeding programmes. Rye (<em>Secale</em> <em>cereale</em> L.) is a cereal that is closely related to wheat, and it is an important crop in Central, Eastern and Northern Europe. The aim of the study was (i) to identify diverse groups of rye accessions based on high-density, genome-wide analysis of genetic diversity within a set of 478 rye accessions, covering a full spectrum of diversity within the genus, from wild accessions to inbred lines used in hybrid breeding, and (ii) to identify selective sweeps in the established groups of cultivated rye germplasm and putative candidate genes targeted by selection. <strong> </strong></p> <p><strong>Results</strong></p> <p>Population structure and genetic diversity analyses based on high-quality SNP (DArTseq) markers revealed the presence of three complexes in the <em>Secale</em> genus: <em>S. sylvestre, S. strictum </em>and<em> S. cereale/vavilovii</em>, a relatively narrow diversity of <em>S. sylvestre</em>, very high diversity of <em>S. strictum</em>, and signatures of strong positive selection in <em>S. vavilovii</em>. Within cultivated ryes, we detected the presence of genetic clusters and the influence of improvement status on the clustering. Rye landraces represent a reservoir of variation for breeding, and especially a distinct group of landraces from Turkey should be of special interest as a source of untapped variation. Selective sweep detection in cultivated accessions identified 133 outlier positions within 13 sweep regions and 170 putative candidate genes related, among others, to response to various environmental stimuli (such as pathogens, drought, cold), plant fertility and reproduction (pollen sperm cell differentiation, pollen maturation, pollen tube growth), and plant growth and biomass production.</p> <p><strong>Conclusions</strong></p> <p>Our study provides valuable information for efficient management of rye germplasm collections, which can help to ensure proper safeguarding of their genetic potential and provides numerous novel candidate genes targeted by selection in cultivated rye for further functional characterisation and allelic diversity studies.</p>
Selective sweeps identification in distinct groups of cultivated rye (Secale cereale L.) germplasm provides potential candidate genes for crop improvement
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Early-season biomass and weather enable robust cereal rye cover crop biomass predictions
Open the record for dataset details and reuse information.
U.S. cereal rye winter cover crop growth database
Open the record for dataset details and reuse information.
MIcrobiota - different dietary inclusion of rye in broilers
<p>The dataset contains an experiment that was conducted to investigate the effects of dietary inclusion of rye, a model ingredient to increase gut viscosity, between 14 and 28 d of age on immune competence-related parameters and performance of broilers.</p> <p>A total of 960 day-old male Ross 308 chicks were weighed and randomly allocated to 24 pens (40 birds per pen), and the birds in every 8 replicate pens were assigned to 1 of 3 experimental diets including graded levels, 0%, 5%, and 10% of rye.</p> <p>Here, the microbiota of jejunal digesta samples is reported, i.e. the raw fastq data, as well as the metadata.</p> <p>The accompanying (peer-reviewed) scientific article can be found here: </p> <ul> <li>PMID: 28854752</li> <li>DOI: <a href="https://doi.org/10.3382/ps/pex152">10.3382/ps/pex152</a></li> </ul> <p> </p>
The genetic mechanism of B chromosome drive in rye illuminated by chromosomescale assembly
<p>Figures, tables and supplementary data from the paper: The genetic mechanism of B chromosome drive in rye illuminated by chromosomescale assembly<br><br>Abstract: The genomes of many plants, animals, and fungi frequently comprise dispensable B chromosomes that rely upon various chromosomal drive mechanisms to counteract the tendency of non-essential genetic elements to be purged over time. The B chromosome of rye – a model system for nearly a century – undergoes targeted nondisjunction during first pollen mitosis, favouring segregation into the generative nucleus, thus increasing their numbers over generations. However, the genetic mechanisms underlying this process are poorly understood. Here, using a newly-assembled, ~430Mb-long rye B chromosome pseudomolecule, we identify five candidate genes whose role as trans-acting moderators of the chromosomal drive is supported by karyotyping, chromosome drive analysis and comparative RNA-seq. Among them, we identify DCR28, coding a microtubule-associated protein related to cell division, and detect this gene also in the B chromosome of Aegilops speltoides. The DCR28 gene family is neo-functionalised and serially-duplicated with 15 B chromosome-located copies that are uniquely highly expressed in the first pollen mitosis of rye.</p>
AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJ-GUESS rye
<p>This is model output from LPJ-GUESS for rye as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.</p> <p>The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).</p> <p>References:</p> <p>Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015</p> <p>Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017</p> <p>Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8</p>
AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: CGMS-WOFOST rye
<p>This is model output from CGMS-WOFOST for rye as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.</p> <p>The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).</p> <p>References:</p> <p>Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015</p> <p>Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017</p> <p>Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8</p>
Intralymphatic Immunotherapy With Polvac Grass & Rye Allergen Extract
ClinicalTrials.gov study NCT05297760. IPD Sharing: NO. Countries: 1. Publications: 12.
No yield benefit from starter fertilizer in soybean no-till planted into rolled-crimped cereal rye
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Data from: Rye planting date impacts biomass production more than seeding rate and nitrogen fertilizer
<p>This zipped folder contains the code and datasets used for an experiment conducted over six years (2015–2020) at the Wiregrass Research and Extension Center in Headland, AL to examine rye biomass production. Treatments included four planting dates (late October, early November, late November, and early December), two seeding rates ( 67 and 101 kg ha<sup>-1</sup>), and four nitrogen rates (0, 34, 67, and 101 kg ha<sup>-1</sup>) replicated four times for a total of 128 observations each year. Measured and/or calculated variables from the data set included biomass, total C and N concentrations for the plant material, C:N ratio, N uptake values, as well as cost info for the biomass. In addition, there are three years of peanut yield data (2015, 2017, 2019) and only two years of cotton yield data (2016, 2020). No cotton data was collected for 2018 due to hurricane damage. Initial and final soil total C values were also measured across the 0 and 101 kg N ha<sup>-1 </sup>rates for the 67 kg ha<sup>-1</sup> seeding rate. </p>
High Fiber Rye Foods for Weight and Body Fat Reduction
ClinicalTrials.gov study NCT03097237. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Effects of Rye Crisp Bread on Appetite and Metabolic Function
ClinicalTrials.gov study NCT02011217. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Rye Bread Trial; Antioxidative and Cholesterol Lowering Effects
ClinicalTrials.gov study NCT01084226. IPD Sharing: Not stated. Countries: 1. Publications: 2.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.