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1,418 results for “Grasses”
The grass–microbiome-rumen axis in grazing sheep farming intervened by supplementary feeding
GEO Series GSE278012. Ovis aries. 6 samples. Type: Expression profiling by high throughput sequencing.
De Novo Genome Assembly of Guinea Grass Exposed to Elevated CO2 and Temperature
GEO Series GSE122194. Megathyrsus maximus. 33 samples. Type: Expression profiling by high throughput sequencing.
Metabolic Regulations by ceRNA under Grass-fed and Grain-fed regimens in Angus Beef Cattle [miRNA-Seq]
GEO Series GSE145376. Bos taurus. 6 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Lack of allergy to timothy grass pollen is not a passive phenomenon but associated with allergen specific modulation of immune reactivity
GEO Series GSE70050. Homo sapiens. 76 samples. Type: Expression profiling by high throughput sequencing.
Cell-specific transcriptomics and silencing reveal aquaporin function in grass stomatal movements
GEO Series GSE309067. Zea mays. 16 samples. Type: Expression profiling by high throughput sequencing.
Metabolic Regulations by ceRNA under Grass-fed and Grain-fed regimens in Angus Beef Cattle
GEO Series GSE145377. Bos taurus. 10 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
Grasses suppress shoot-borne roots to conserve water during drought
GEO Series GSE78054. Setaria viridis. 24 samples. Type: Expression profiling by high throughput sequencing.
Distinguishing reproductive phasiRNAs in grasses from other identically-sized small RNAs using machine learning methods
GEO Series GSE108105. Zea mays. 4 samples. Type: Non-coding RNA profiling by high throughput sequencing.
DNA barcode trnH-psbA is a promising candidate for efficient identification of forage legumes and grasses
<p><strong>Objective</strong></p> <p>Grasslands are widespread ecosystems that fulfil many functions. Plant species richness (PSR) is known to have beneficial effects on such functions and monitoring PSR is crucial for tracking the effects of land use and agricultural management on these ecosystems. Unfortunately, traditional morphology-based methods are labor-intensive and cannot be adapted for high-throughput assessments.</p> <p>DNA barcoding could aid increasing the throughput of PSR assessments in grasslands. In this proof-of-concept work, we aimed at determining which of three plant DNA barcodes (<em>rbcLa</em>, <em>matK</em> and <em>trnH-psbA</em>) best discriminates 16 key grass and legume species common in temperate sub-alpine grasslands.</p> <p><strong>Results</strong></p> <p>Barcode <em>trnH-psbA</em> had a 100% correct assignment rate (CAR) in the five analyzed legumes, followed by <em>rbcLa </em>(93.3%) and <em>matK</em> (55.6%). Barcode <em>trnH-psbA</em> had a 100% CAR in the grasses <em>Cynosurus cristatus</em>, <em>Dactylis glomerata</em> and <em>Trisetum flavescens</em>. However, the closely related <em>Festuca, Lolium </em>and <em>Poa</em> species were not always correctly identified, which led to an overall CAR in grasses of 66.7 %, 50.0% and 46.4% for<em> trnH-psbA</em>, <em>matK</em> and <em>rbcLa</em>, respectively. Barcode <em>trnH-psbA</em> is thus the most promising candidate for PSR assessments in permanent grasslands and could greatly support plant biodiversity monitoring on a larger scale.</p> <p><strong>Content of data file</strong></p> <p>This data file contains all raw data obtained during the study. The full information on the project can be found on the BOLD database (<a href="http://www.boldsystems.org/index.php/Public_SearchTerms">http://www.boldsystems.org/index.php/Public_SearchTerms</a>) using the search term SWFRG</p>
Raster files catalog to forest growth simulation performed by r.recovery module (Grass Gis).
<p>This repository contains all publicly available raster files to calibrate/validate the parameters of the Diffusive-logistic growth (DLG) model and generate prognostics by means of the GRASS-GIS module r.recovery (Richit et al., 2019).</p> <p>Three .tiff files are needed for perform calibration/validation: two are EVI raster maps (two time-lapsed conditions of forest density) and a soil use file. In the repository the example files are:</p> <p>Calibration_EVI_2000;</p> <p>Calibration_EVI_2011 and</p> <p>Calibration_soil_use_2000, respectively.</p> <p>The others files in the repository are four EVI .tiff files and their respectively soil use .tiff files that were used to perform simulations by the means of calibrated parameters of the DGL model. The files are:</p> <p>AMNP_EVI_2016 and AMNP_soil_use_2016;</p> <p>FPSP_EVI_2016 and FPSP_soil_use_2016;</p> <p>MDRB_EVI_2016 and MDRB_soil_use_2016;</p> <p>MNPTS_EVI_2016 and MNPTS_soil_use_2016.</p> <p>For more details on r.recovery module please check </p> <p>Richit, L.A., Bonatto, C., da Silva, R.V., Grzybowski, J.M.V., 2019. Prognostics of forest recovery with r.recovery grass-gis module: an open source forest growth simulation model based on the diffusive-logistic equation. Environmental modelling & software 111, 108–120.</p>
Hilltop Arboretum Landform Dataset for GRASS GIS
<p><strong>Hilltop Arboretum Dataset for GRASS GIS</strong></p> <p>This geospatial dataset contains raster data for the landform at Hilltop Arboretum, Baton Rouge, Louisiana, USA. This data was collected in an aerial survey with a DJI Phantom 4 Pro drone over Hilltop Arboretum on 12/31/2019 by Brendan Harmon and Josef Horacek. The aerial photographs were processed in Agisoft Metashape using Structure from Motion (SfM) to generate a point cloud, orthophotograph, and digital surface model. The point cloud was processed in CloudCompare to generate a bare earth point cloud. The orthophoto, digital surface model, and bare earth point cloud were imported into GRASS GIS. The bare earth point cloud was interpolated as a digital elevation model using the Regularized Spline with Tension method. The top level directory <em>lousiana_s_spm_hilltop</em> is a GRASS GIS location for the North American Datum of 1983 (NAD 83) / Louisiana South State Plane Meters with <a href="https://epsg.io/26982">EPSG code 26982</a>. Inside the location there are the PERMANENT mapset, a license file, and readme file.</p> <p><strong>Survey</strong></p> <ul> <li>Location: LSU Hilltop Arboretum, Baton Rouge, Louisiana, USA.</li> <li>Drone: DJI Phantom 4 Pro</li> <li>Software: Agisoft Metashape, CloudCompare, GRASS GIS</li> <li>Team: Brendan Harmon and Josef Horacek</li> <li>Date: 12/31/2019</li> <li>GCPs: 10 AeroPoints</li> </ul> <p><strong>Instructions</strong><br> Install <a href="https://grass.osgeo.org/">GRASS GIS</a>, unzip this archive, and move the location into your <a href="https://grass.osgeo.org/grass77/manuals/grass_database.html">GRASS GIS database</a> directory. If you are new to GRASS GIS read the <a href="https://grass.osgeo.org/documentation/first-time-users/">first time users guide</a>.</p> <p><strong>License</strong><br> This dataset is licensed under the <a href="https://opendatacommons.org/licenses/pddl/index.html">ODC Public Domain Dedication and License 1.0 (PDDL)</a> by Brendan Harmon.</p>
Fi. 16. Tetraneura ulmi (Linnaeus, 1758). Apt. and juv. on grass root. in Identification guide to Nordic aphids associated with mosses, horsetails and ferns (Bryophyta, Equisetophyta, Polypodiophyta) (Insecta, Hemiptera, Aphidoidea)
Fi. 16. Tetraneura ulmi (Linnaeus, 1758). Apt. and juv. on grass root.
Figure 2 from: Gardiner T (2020) Slipping a disc! Utilisation of harrowed strips by Orthoptera on a Breckland grass-heath. Journal of Orthoptera Research 29(2): 127-131. https://doi.org/10.3897/jor.29.51900
Figure 2 Nymph (both species combined) and adult density for two grasshopper species.
Data from: When perception reflects reality: non-native grass invasion alters small mammal risk landscapes and survival
1. Modification of habitat structure due to invasive plants can alter the risk landscape for wildlife by, for example, changing the quality or availability of refuge habitat. Whether perceived risk corresponds with actual fitness outcomes, however, remains an important open question. We simultaneously measured how habitat changes due to a common invasive grass (cheatgrass, <i>Bromus tectorum</i>) affected the perceived risk, habitat selection, and apparent survival of a small mammal, enabling us to assess how well perceived risk influenced important behaviors and reflected actual risk. 2. We measured perceived risk by nocturnal rodents using a giving-up density foraging experiment with paired shrub (safe) and open (risky) foraging trays in cheatgrass and native habitats. We also evaluated microhabitat selection across a cheatgrass gradient as an additional assay of perceived risk and behavioral responses for deer mice (<i>Peromyscus maniculatus</i>) at two spatial scales of habitat availability. Finally, we used mark-recapture analysis to quantify deer mouse apparent survival across a cheatgrass gradient while accounting for detection probability and other habitat features. 3. In the foraging experiment, shrubs were more important as protective cover in cheatgrass dominated habitats, suggesting that cheatgrass increased perceived predation risk. Additionally, deer mice avoided cheatgrass and selected shrubs, and marginally avoided native grass, at two spatial scales. 4. Deer mouse apparent survival varied with a cheatgrass-shrub interaction, corresponding with our foraging experiment results, and providing a rare example of a native plant mediating the effects of an invasive plant on wildlife. 5. By synthesizing the results of three individual lines of evidence (foraging behavior, habitat selection, and apparent survival), we provide a rare example of linkage between behavioral responses of animals indicative of perceived predation risk and actual fitness outcomes. Moreover, our results suggest that exotic grass invasions can influence wildlife populations by altering risk landscapes and survival.
Data from: Genetic diversity and population structure of Urochloa grass accessions from Tanzania using simple sequence repeat (SSR) markers
Urochloa (syn.—Brachiaria s.s.) is one of the most important tropical forages that transformed livestock industries in Australia and South America. Farmers in Africa are increasingly interested in growing Urochloa to support the burgeoning livestock business, but the lack of cultivars adapted to African environments has been a major challenge. Therefore, this study examines genetic diversity of Tanzanian Urochloa accessions to provide essential information for establishing a Urochloa breeding program in Africa. A total of 36 historical Urochloa accessions initially collected from Tanzania in 1985 were analyzed for genetic variation using 24 SSR markers along with six South American commercial cultivars. These markers detected 407 alleles in the 36 Tanzania accessions and 6 commercial cultivars. Markers were highly informative with an average polymorphic information content of 0.79. The analysis of molecular variance revealed high genetic variation within individual accessions in a species (92%), fixation index of 0.05 and gene flow estimate of 4.77 showed a low genetic differentiation and a high level of gene flow among populations. An unweighted neighbor-joining tree grouped the 36 accessions and six commercial cultivars into three main clusters. The clustering of test accessions did not follow geographical origin. Similarly, population structure analysis grouped the 42 tested genotypes into three major gene pools. The results showed the Urochloa brizantha (A. Rich.) Stapf population has the highest genetic diversity (I = 0.94) with high utility in the Urochloa breeding and conservation program. As the Urochloa accessions analyzed in this study represented only 3 of 31 regions of Tanzania, further collection and characterization of materials from wider geographical areas are necessary to comprehend the whole Urochloa diversity in Tanzania.
Data from: Rainfall pulse response of carbon fluxes in a temperate grass ecosystem in the semiarid Loess Plateau
Rainfall pulses can significantly influence carbon cycling in water limited ecosystems. The magnitude of carbon flux component responses to precipitation may vary depending on precipitation amount and antecedent soil moisture, associated with nonlinear responses of plants and soil microbes. The present study was carried out in a temperate grass ecosystem during 2013–2015 in the semiarid Loess Plateau of China, to examine the response of carbon fluxes to precipitation using the "threshold-delay" model. The unique contribution of environmental variables, such as precipitation amount and antecedent soil moisture before rainfall (SWC_antecedent) to carbon fluxes in response to rainfall were also investigated. The lower threshold of effective rainfall was 6.6 mm for gross ecosystem production (GEP), 8.5 mm for net ecosystem production (NEP) and 4.5 mm for ecosystem respiration (RE); and the upper threshold of effective rainfall was 21.4 mm for GEP and NEP, and 16.8 mm for RE. Rainfall amount was positively affected the relative rainfall responses of GEP, NEP and RE. However, SWC_antecedent at 20 cm soil depth offset the response of GEP to rainfall pulses, and SWC_antecedent at 5 cm depth offset the response of NEP and RE to rainfall pulses, with corresponding partial slopes of linear regressions of −0.50, −0.40 and −0.52. These results indicated that NEP was more sensitive to rainfall pulses and RE was more sensitive to SWC_antecedent. These results demonstrate the importance of rainfall events of < 10 mm, and that the negative effect of SWC_antecedent should also be considered when estimating ecosystem carbon fluxes in this semiarid region.
Figure 1 from: Andri Deswati D, Anggadiredja K, Nuryanti Garmana A (2024) Potent antioxidant activity of black grass jelly (Mesona palustris BL) leaf extract and fractions. Pharmacia 71: 1-5. https://doi.org/10.3897/pharmacia.71.e117435
Figure 1 HPLC Spectrogram of black grass jelly extract.
Figure 3 from: de Lange PJ, Smissen RD, Rolfe JR, Ogle CC (2016) Systematics of Simplicia Kirk (Poaceae, Agrostidinae) – an endemic, threatened New Zealand grass genus. PhytoKeys 75: 119-144. https://doi.org/10.3897/phytokeys.75.10328
Figure 3 - NeighborNet graph for AFLP data with all automatically scored polymorphisms.
Figure 4 from: de Lange PJ, Smissen RD, Rolfe JR, Ogle CC (2016) Systematics of Simplicia Kirk (Poaceae, Agrostidinae) – an endemic, threatened New Zealand grass genus. PhytoKeys 75: 119-144. https://doi.org/10.3897/phytokeys.75.10328
Figure 4 - NeighborNet graph for reduced AFLP data with reproduced polymorphisms only.
Figure 1 from: de Lange PJ, Smissen RD, Rolfe JR, Ogle CC (2016) Systematics of Simplicia Kirk (Poaceae, Agrostidinae) – an endemic, threatened New Zealand grass genus. PhytoKeys 75: 119-144. https://doi.org/10.3897/phytokeys.75.10328
Figure 1 - Distribution of Simplicia species and showing locations discussed in text.
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.