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193
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ShareScore release 0.9.0
Dataset results
193 results for “crop modelling”
Model-to-crop conserved NUE Regulons enhance machine learning predictions of nitrogen use efficiency
GEO Series GSE280343. Zea mays. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Model-to-crop conserved NUE Regulons enhance machine learning predictions of nitrogen use efficiency
GEO Series GSE280346. Zea mays. 229 samples. Type: Expression profiling by high throughput sequencing.
Model-to-crop conserved NUE Regulons enhance machine learning predictions of nitrogen use efficiency
GEO Series GSE280342. Arabidopsis thaliana. 8 samples. Type: Expression profiling by high throughput sequencing.
Metrics of neural network models in 2022 crops in Extremadura, Spain
<p>Characteristics of the 32 neural network models generated through the analysis of Sentinel-2 images in crops in Extremadura in 2022.</p>
ARTEMIS project - Long-term field experiment (LTE) dataset for crop modelling
<p>The spreadsheets aim at collecting general information and specific data (e.g., crop yield, soil properties and weather) from long-term field experiments (LTE's) that are used to calibrate and validate ARMOSA model for ARTEMIS project - WP3 task 3.1 activity. Particularly, information reported will be useful for providing an overview of the distribution of agro-ecological systems, management strategies, field measures, and weather data available, useful to run ARMOSA model under current and future climate change scenarios.</p>
Selected data analysed in the JGR Atmosphere manuscript "Noah-MP with the generic crop growth model Gecros in the WRF model: Effects of dynamic crop growth on land-atmosphere interaction"
<p>This depository contains the simulated 3-hr data of 2m-temperature (tas), latent heat flux (hfls), sensible heat flux (hfss), soil moisture (mros) of the top 1 m, convective available potential energy (cape), convection inhibition (cin), leaf area index (lai) for the model domain, which centers Germany. Further it contains the namelist.input of the WRF simulations of the CTRL and EXP_CROP run. The simulations are described in the manuscript "Noah-MP with the generic crop growth model Gecros in the WRF model: Effects of dynamic crop growth on land-atmosphere interaction" by Warrach-Sagi et al., 2022</p>
First model + smart crop
First model reconstructed in Autodesk ReMake with smart crop option Source: Objaverse 1.0 / Sketchfab
Daily climate and rainfall data for Niger 1983-2021, for use in SARRA-O crop simulation model
<p>This dataset contains daily rainfall and climate data for Niger, that can be used as input of the <a href="https://github.com/SARRA-cropmodels/SARRA-O">SARRA-O spatialized crop simulation model</a>. This data can be directly put as input of SARRA-O model to perform computations and obtain simulation results.</p> <p>The archive contains :</p> <ul> <li>AgERA5 (doi:<a href="https://doi.org/10.24381/cds.6c68c9bb">10.24381/cds.6c68c9bb</a>) climatic data for Niger, with daily geotiff files for minimum, maximum, mean temperature (°C), reference evapotranspiration calculated with Hargraeves formula (mm), and solar radiation flux (kJ/m²) at 0.1° spatial resolution from 01/01/1981 to 31/12/2021</li> <li>TAMSAT v3.0 (doi:<a href="http://doi.org/10.1038/sdata.2017.63">10.1038/sdata.2017.63</a>) satellite rainfall estimation data for Niger (mm), with daily geotiff files at 0.0375° spatial resolution from 01/01/1983 to 31/12/2021</li> <li>CHIRPS v2.0 (doi:<a href="https://doi.org/10.1038/sdata.2015.66">10.1038/sdata.2015.66</a>) satellite rainfall estimation data for Niger (mm), with daily geotiff files at 0.05° spatial resolution from 01/01/1981 to 31/12/2022</li> </ul> <p>This data has been extracted from their original sources using the <a href="https://github.com/SARRA-cropmodels/SARRA-data-download">SARRA-data-downloader tool</a>, on June 14th and 15th, 2023.</p> <p>The applicable licences are the licences of the respective datasets.</p>
Daily climate and rainfall data for northern Cameroon 2020-2022, for use in SARRA-Py crop simulation model
<p>This dataset contains daily rainfall and climate data for north Cameroon, that can be used as input of the SARRA-Py spatialized crop simulation model. This data can be directly put as input of SARRA-O model to perform computations and obtain simulation results.</p> <p>The archive contains :</p> <ul> <li>AgERA5 (doi:<a href="https://doi.org/10.24381/cds.6c68c9bb">10.24381/cds.6c68c9bb</a>) climatic data for north Cameroon, with daily geotiff files for minimum, maximum, mean temperature (°C), reference evapotranspiration calculated with Hargraeves formula (mm), and solar radiation flux (kJ/m²/d) at 0.1° spatial resolution from 01/01/2020 to 31/12/2022</li> <li>CHIRPS v2.0 (doi:<a href="https://doi.org/10.1038/sdata.2015.66">10.1038/sdata.2015.66</a>) satellite rainfall estimation data for north Cameroon (mm), with daily geotiff files at 0.05° spatial resolution from 01/01/2020 to 31/12/2022</li> </ul> <p>This data has been extracted from their original sources using the <a href="https://github.com/SARRA-cropmodels/SARRA-data-download">SARRA-data-downloader tool</a>.</p> <p>The applicable licences are the licences of the respective datasets.</p>
Model-to-crop conserved NUE Regulons enhance machine learning predictions of nitrogen use efficiency
GEO Series GSE280345. Zea mays. 58 samples. Type: Expression profiling by high throughput sequencing.
Potential Impacts of Climate Change on World Food Supply: Datasets from a Major Crop Modeling Study
The Potential Impacts of Climate Change on World Food Supply: Datasets from a Major Crop Modeling Study contain projected country and regional changes in grain crop yields due to global climate change. Equilibrium and transient scenarios output from General Circulation Models (GCMs) with three levels of farmer adaptations to climate change were utilized to generate crop yield estimates of wheat, rice, coarse grains (barley and maize), and protein feed (soybean) at 125 agricultural sites representing major world agricultural regions. Projected yields at the agricultural sites were aggregated to major trading regions, and fed into the Basic Linked Systems (BLS) global trade model to produce country and regional estimates of potential price increases, food shortages, and risk of hunger. These datasets are produced by the Goddard Institute for Space Studies (GISS) and are distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
nitrogen starvation and re-supply-Improving the nitrogen use efficiency : from model plant to crop species.
GEO Series GSE8031. Arabidopsis thaliana; Brassica napus. 72 samples. Type: Expression profiling by array.
Model-to-crop conserved NUE Regulons enhance machine learning predictions of nitrogen use efficiency
GEO Series GSE280353. Arabidopsis thaliana; Zea mays. 354 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.