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302 results for “cotton”
Images and statistical analysis of alfalfa root crowns from inside and outside disease rings caused by cotton root rot
<p>This repository contains raw image data of root crowns imaged using the backlit RhizoVision Crown platform of alfalfa plants from either inside or outside disease rings caused by cotton root rot for a manuscript to be submitted. Data files and the R scripts are included for complete statistical analysis associated with the imaged root crown set.</p> <p>Please cite both this repository and below journal article if reusing this data for a publication.</p> <p><strong>Manuscript Title:</strong> Digital imaging to evaluate root system architectural changes associated with soil biotic factors</p> <p><strong>Authors: </strong>Chakradhar Mattupalli, Anand Seethepalli, Larry M. York, Carolyn A. Young</p> <p><strong>Journal Article: </strong><a href="https://doi.org/10.1094/PBIOMES-12-18-0062-R">https://doi.org/10.1094/PBIOMES-12-18-0062-R</a> (open access)</p> <p><strong>Image Files</strong></p> <p>afalfa_roots_raw_images.zip - 264 images in PNG format directly from a monochrome camera with gamma at 3.9 to make near-segmented raw images in greyscale</p> <p>alfalfa_feature_images.zip - 264 images in PNG format with a subset of computed features overlaid</p> <p>alfalfa_segmented_images.zip - 264 black and white, binary images in PNG format that result from simple thresholding of the raw images</p> <p>I_scale_1.png - an image of a 6 inch ruler for extracting pixel to physical unit conversion</p> <p>metadata.csv - metadata output from RhizoVision Analyzer with diameter ranges and other options used for image analysis</p> <p><strong>Statistical Analysis</strong></p> <p>alfalfaCRR_features_10012018.csv - extracted features from RhizoVision Analyzer v1.0.3 - called by name in R script</p> <p>RootArchitectureFieldStudyimagetoIDmap.csv - mapping of image file names to plot identity - called by name in R script</p> <p>manuscript complete root rot RVC analysis.R - R script with all analysis that used the data from the imaged root crowns</p> <p> </p> <p> </p>
Fig. 4 in Terpene chemotypes in Gossypium hirsutum (wild cotton) from the Yucatan Peninsula, Mexico
Fig. 4. Monoterpene composition of the two proposed cotton chemotypes. (a) Scatterplot of the relative abundance of the pinene group (α-Pinene + β-Pinene) against the relative abundance of the summed values of the γ-Terpinene group. (b) Representative chromatograms of plants belonging to chemotype classes A (upper panel) and B (lower panel). 1: (E)-2-Hexenal; 2: 2,4-Hexadienal (E,E); 3: α-Thujene; 4: α-Pinene; 5: Camphene; 6: Sabinene; 7: β-Pinene; 8: β-Myrcene; 9: α-Phellandrene; 10: α-Terpinene; 11: p-Cymene; 12: Limonene; 13: β-Phellandrene; 14: β-Ocimene; 15: γ-Terpinene; 16: Terpinolene; 17: Bornyl acetate; 18: γ-Elemene; 19: β-Caryophyllene; 20: α-Humulene; 21: Bicyclogermacrene. (c) visualisation of proportion of monoterpene compounds from panel (b), for each chemotype class.
Fig. 1 in Terpene chemotypes in Gossypium hirsutum (wild cotton) from the Yucatan Peninsula, Mexico
Fig. 1. Map showing locations of the wild Gossypium hirsutum populations from which seeds were collected along the Yucatan Peninsula.
Fig. 3 in Terpene chemotypes in Gossypium hirsutum (wild cotton) from the Yucatan Peninsula, Mexico
Fig. 3. Theorised monoterpenoid biosynthesis pathway. Compounds highlighted in blue comprise the γ-terpinene compound group, those highlighted in grey comprise the α-pinene compound group. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 5 in Terpene chemotypes in Gossypium hirsutum (wild cotton) from the Yucatan Peninsula, Mexico
Fig. 5. Principal coordinate analysis on relative abundance of monoterpenes in plants grown from seed, showing samples separated based on their compositional similarity.
Fig. 6 in Terpene chemotypes in Gossypium hirsutum (wild cotton) from the Yucatan Peninsula, Mexico
Fig. 6. Ridgeline plot showing the distribution of the summed values of the γ-terpinene compound group (γ-terpinene, limonene, α-thujene, α-terpinene, terpinolene, and p-cymene; as % relative to total monoterpenes in each plant). In order from top to bottom: the plots coloured red (Celestún) and orange (Sisal) are located at the west of the peninsula. The plot coloured yellow (Chicxulub) is in the centre, and the cream coloured plot (Coloradas) is located at the east of the peninsula. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Terpene chemotypes in Gossypium hirsutum (wild cotton) from the Yucatan Peninsula, Mexico
Fig. 2. Correlation analysis of all mono- and sesquiterpenes analysed in the wild Gossypium hirsutum plants. Red rectangles indicate highly supported groups of monoterpenes (approximately unbiased (AU) p <0.05). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
7in 1 Sensor Dataset for Cotton fields in Pakistan 2023
<p>The crop type, unique device IDs, sowing dates, cultivated area in acres, specific geographical coordinates, location names, relevant document links, monitoring dates, and sensor data are all included in this file. The collection contains several instances of cotton farming, each with its own set of features.</p> <ol> <li>Cotton Crop ID: A unique identifier for the monitoring gadget.</li> <li>Sowing Date: The date the cotton crop was planted.</li> <li>Acreage: The total land area dedicated to cotton farming, measured in acres.</li> <li>Coordinates: The cotton field's specific geographical coordinates, provided in latitude and longitude, which aid in accurate location identification.</li> <li>Location: The name of the area or region in which the cotton crop is grown (for example, Rahimyar Khan, Shah Alam Shah, Matiari, Sindh).</li> <li>Document connection: A connection to related cotton crop documents or records, which may contain further data, reports, or documentation.</li> </ol> <p>The date on which the cotton crop was monitored or evaluated for various parameters.<br> Sensor Data: Information gathered from sensors during monitoring, which may include information on environmental conditions, growth metrics, or other agricultural parameters.<br> This dataset contains numerous cotton cultivation instances, each of which is individually recognized by a combination of crop kind, device ID, and monitoring data. It offers vital information into the cultivation process, allowing researchers and stakeholders to assess cotton crop development, conditions, and performance over time, ultimately contributing to informed agricultural decision-making.</p>
XJ_COTTON10: The 10-m cotton maps in Xinjiang, China during 2018-2021
<p>The datasets accompany the paper "The 10-m cotton maps in Xinjiang, China during 2018–2021" that was published in <a href="https://doi.org/10.1038/s41597-023-02584-3"><i>Scientific Data</i></a> on Oct. 10, 2023. The datasets contain the 10-m cotton maps of Xinjiang (XJ_COTTON10) from 2018 to 2021. They were developed through supervised classification using high-quality in-field samples and multi-source remote sensing data on the Google Earth Engine (GEE) platform.</p><p><strong>Citation</strong>:</p><p>[1] Kang, X., Huang, C., Chen, J.M., Lv, X., Wang, J., Zhong, T., Wang, H., Fan, X., Ma, Y., Yi, X., Zhang, Z., Zhang, L., Tong, Q., 2023. The 10-m cotton maps in Xinjiang, China during 2018-2021. Sci Data 10, 688. doi:10.1038/s41597-023-02584-3</p><p>[2] Lang, P., Zhang, L., Huang, C., Chen, J., Kang, X., Zhang, Z., Tong, Q., 2023. Integrating environmental and satellite data to estimate county-level cotton yield in Xinjiang Province. Frontiers in Plant Science 13, 1048479. doi:10.3389/fpls.2022.1048479</p><p>[3] Kang, X., Huang, C., Zhang, L., Zhang, Z., Lv, X., 2022. Downscaling solar-induced chlorophyll fluorescence for field-scale cotton yield estimation by a two-step convolutional neural network. Computers and Electronics in Agriculture 201, 107260. doi:10.1016/j.compag.2022.107260</p><p>[4] Kang, X., Huang, C., Zhang, L., Wang, H., Zhang, Z., Lv, X., 2023. Regional-scale cotton yield forecast via data-driven spatio-temporal prediction (STP) of solar-induced chlorophyll fluorescence (SIF). Remote Sensing of Environment 299, 113861. doi:10.1016/j.rse.2023.113861</p>
Trauma Patients and Hypothermia in the Emergency Room: ReadyHeat® Versus Cotton Wool Blanket
ClinicalTrials.gov study NCT02353793. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Bulldog vs. Cotton Tourniquet in Laparoscopic Hepatectomy for Patients
ClinicalTrials.gov study NCT04277065. IPD Sharing: Not stated. Countries: 1. Publications: 7.
Multifaceted Intervention for Protection Against Cotton Dust Exposure Among Textile Workers
ClinicalTrials.gov study NCT03738202. IPD Sharing: NO. Countries: 1. Publications: 5.
Incidence of prey DNA in predators from a cotton system utilizing winter cover crops
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Data from: Does prey encounter and nutrient content affect prey selection in wolf spiders inhabiting Bt cotton fields?
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Data from: Changes in the diet and body size of a small herbivorous mammal (Sigmodon hispidus, hispid cotton rat) following the Late Pleistocene megafauna extinction
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Data from: Invasion origin, rapid population expansion, and the lack of genetic structure of cotton bollworm (Helicoverpa armigera) in the Americas
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Data from: Recent long-distance transgene flow conforms to historical patterns of gene flow in wild cotton (Gossypium hirsutum) at its center of origin
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Data from: Assessing the role of non-cotton refuges in delaying Helicoverpa armigera resistance to Bt cotton in West Africa
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Figure 1 from: Li Z, Yao T, Xu Z, Meng L, Li B (2020) A new species of Cheiloneurus Westwood (Hymenoptera, Encyrtidae) as a hyperparasitoid of the invasive cotton mealybug, Phenacoccus solenopsis Tinsley, in China. ZooKeys 974: 23-29. https://doi.org/10.3897/zookeys.974.55528
Figure 1 Cheiloneurus nankingensis sp. nov. (female, holotype) A mesosoma, dorsal view B metasoma, dorsal view C antennae D mandibles E fore wing F head, front view G head, ventral view. Scale bars: 0.10 mm.
Figure 2 from: Li Z, Yao T, Xu Z, Meng L, Li B (2020) A new species of Cheiloneurus Westwood (Hymenoptera, Encyrtidae) as a hyperparasitoid of the invasive cotton mealybug, Phenacoccus solenopsis Tinsley, in China. ZooKeys 974: 23-29. https://doi.org/10.3897/zookeys.974.55528
Figure 2 Cheiloneurus nankingensis sp. nov. (male) A fore wing B antennae C head, front view D head, ventral view E mesosoma, dorsal view F metasoma, dorsal view. Scale bars: 0.10 mm.
ScienceDex guides
Understand access before you commit
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.