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302 results for “cotton”
Crop diversity and within field multi-species interactions mediate herbivore abundances in cotton fields
<p>Insect herbivore abundances in agricultural fields partly depend on surrounding landscape compositional heterogeneity (e.g., landscape complexity). Landscape complexity can directly (e.g., dilution of host crops) and indirectly (promoting herbivore biocontrol) regulate herbivores in agricultural fields. While much is known about direct (e.g., resource concentration) and indirect effects (i.e., promoting biocontrol) of landscape complexity on herbivore populations, more work is needed to study whether landscape complexity can regulate herbivore populations by mediating within field multi-species interactions among herbivores and their shared natural enemies. During 2019 and 2020, we estimated <em>Bemisia tabaci </em>and<em> Aphis gossypii</em> abundances, their dominant predators (coccinellids, spiders, <em>Orius </em>spp., and <em>Geocoris </em>spp.), and their interaction (using molecular analysis) in 38 cotton fields along a gradient of landscape diversity across Georgia, USA. Within cotton fields, we assessed the effect of predator abundances, their frequency of feeding on herbivores, and the correlation between herbivore abundances (<em>B. tabaci </em>and <em>A. gossypii</em>) on the <em>B. tabaci</em> and <em>A. gossypii</em> abundance. At the landscape scale, crop diversity and different cover types influenced the abundance of <em>B. tabaci</em> and <em>A. gossypii</em> within cotton fields. We found a complex interaction among pests at the field scale, with higher aphid abundance correlated with decreased whitefly abundance. Our results support crop diversification for improving suppression of generalist pests in cotton landscapes through promoting biocontrol and diluting host crop area. Our result further suggests that the landscape complexity effect on whiteflies can indirectly mediate aphid abundance in cotton fields, indicating the importance of within field species interactions.</p>
Leaf trait covariation and controls on leaf mass per area (LMA) following cotton domestication
<p class="MsoNormal"><span>The process of domestication has driven dramatic shifts in plant functional traits including leaf mass per area (LMA). It remains unclear whether domestication has produced concerted shifts in the lower-level anatomical traits that underpin LMA and how these traits in turn affect photosynthesis. </span><span>In this study, we investigated controls of LMA and leaf gas exchange by leaf anatomical properties at the cellular, tissue and whole leaf levels, comparing 26 wild and 31 domesticated genotypes of cotton </span><span>(<em>Gossypium</em>). </span><span>As expected, domesticated plants expressed lower LMA, higher photosynthesis and stomatal conductance</span><span>, suggesting a shift towards the 'faster' end of the leaf economics spectrum. At whole-leaf level, variation in LMA was predominantly determined by leaf density (LD) both in wild and domesticated genotypes. At tissue level, higher leaf volume per area (<em>V</em><sub>leaf</sub>) in domesticated genotypes was driven by a simultaneous increase in the volume of epidermal, mesophyll and vascular bundle tissue and airspace, while lower LD resulted from a dilution effect of lower increased volume of palisade tissue and vascular bundle of high mass density by higher increased volume of epidermis and airspace of low mass density. The volume of spongy mesophyll exerted direct control on photosynthesis in domesticated genotypes but only indirect control in wild genotypes. At cellular level, a shift to larger but less numerous cells with thinner cell walls underpinned a lower proportion of cell wall mass, and thus a reduction in LD. </span><span>Taken together, cotton domestication has triggered synergistic shifts in the underlying determinants of LMA but also photosynthesis, at cell, tissue and whole-leaf level, resulting in a marked shift in plant ecological strategy.</span></p>
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Henry Cotton facemask edition
photogrammetry study of Henry Cotton, the first Chancellor at Liverpool John Moore University. I am not the rascal that put a mask on him, however i found it amusing so i took a scan Source: Objaverse 1.0 / Sketchfab
Imaging and Tracking for Cotton et al PIP-H2A Intestinal monolayers
<p>Imaging files for growing PIP-H2A human intestinal monolayers. The .tif fil encompasses the raw imaging data that had quadrants stitched together, Z-stacking flaaten using max projection, Channel 1 and Channel 2 added together to create Channel 3, then segmentation via CellPose2 saved as Channel 4.</p> <p>The .xml file is the working file staring all tracking information for TrackMate.</p>
AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: CLM-Crop cotton
<p>This is model output from CLM-Crop for cotton 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>
Figure 2. a in Determining some biological parameters of Aenasius arizonensis (Girault) (Hymenoptera: Encyrtidae) on cotton mealybug and the rate of parasitism in field conditions
Figure 2. a) Male of Aenasius arizonensis, b) Female of Aenasius arizonensis.
Data files and computer code scripts for reproducing the results of a manuscript on the measurement and ranking of cotton drought tolerance capacity
<p>This upload contains the data files and computer code scripts for reproducing the main results, esp. figures, of the manuscript entitled<br>"Rapid measurement and statistical ranking of leaf drought tolerance capacity in cotton," by X. Dong, D. A. Mott, J. Garg, Q. Zhou, J. Sunoj V. S., and B. M. McKnight. The manuscriptt is currently under peer review.</p>
Forecasting model of seasonal dynamics of boll weevil Anthonomus grandis grandis (Coleoptera: Curculionidae) in cotton crops using artificial neural networks
Open the record for dataset details and reuse information.
Supporting figures for Intelligent Image Classification for Grading Egyptian Cotton Lint
<p>Supporting figures for Intelligent Image Classification for Grading Egyptian Cotton Lint manuscript sent for review in Sensors. </p>
Fig. 4 in The detection of an alien pest, the cotton leaf roller Haritalodes decorata (Lepidoptera: Crambidae), on the Black Sea Coast of Russia
Fig. 4. The localities on the territory of the Russian Black Sea Cost where Haritalodes
Fig. 2 in The detection of an alien pest, the cotton leaf roller Haritalodes decorata (Lepidoptera: Crambidae), on the Black Sea Coast of Russia
Fig. 2. Maximum likelihood COI tree illustrating intraspecific divergence of Haritalodes
Fig. 3 in The detection of an alien pest, the cotton leaf roller Haritalodes decorata (Lepidoptera: Crambidae), on the Black Sea Coast of Russia
Fig. 3. Biology of Haritalodes derogata in Sochi, Yana Fabritsiusa str., 22–27.VIII
CottonWeedDet12: a 12-class weed dataset of cotton production systems for benchmarking AI models for weed detection
<p>The dataset <strong>CottonWeedDet12</strong> consists of 5648 RGB images of 12-class weeds that are common in cotton fields in the southern U.S. states, with a total of 9370 bounding boxes. These images were acquired by either smartphones or hand-held digital cameras, under natural field light condition and throughout June to September of 2021. The images were manually labeled by qualified personnel for weed identification, and the labeling process was done using the VGG Image Annotator (version 2.10).</p> <p>The dataset, at the time of publication, is the largest publicly available multi-class dataset dedicated to weed detection. It expects to facilitate communicate efforts to exploit state-of-the-art deep learning method to push weed recognition to the next level. With the WeedDet12 dataset, a performance benchmark of a suite of YOLO object detectors has been built for weed detection. Detailed documentation of the dataset, model benchmarking and performance results is given in an accompanying journal paper: <a href="https://www.sciencedirect.com/science/article/pii/S0168169923000431">Dang, F., Chen, D., Lu, Y., Li, Z., 2023. YOLOWeeds: A novel benchmark of YOLO object detectors for multi-class weed detection in cotton production systems. Computers and Electronics in Agriculture 205, 107655. https://doi.org/10.1016/j.compag.2023.107655</a><a href="https://doi.org/10.1016/j.compag.2023.107655"> </a></p> <p>If you use the dataset on a published publication, please cite the dataset or the <a href="https://doi.org/10.1016/j.compag.2023.107655">journal article</a> above.</p>
EXPERIMENTAL GROWTH CONDITIONS AFFECT DIRECT AND INDIRECT DEFENCES IN TWO COTTON SPECIES
<p>The file "R code CHappuis et al. 2023.txt" contains the R code for all the analyses shown in the research article "EXPERIMENTAL GROWTH CONDITIONS AFFECT DIRECT AND INDIRECT DEFENCES IN TWO COTTON SPECIES". The other files contain the raw data used for the analyses.</p> <p> </p> <p> </p>
Data from: Cover cropping history affects cotton boll distribution, lint yields, and fiber quality
<p>This is digital research data corresponding to a published manuscript, Cover cropping history affects cotton boll distribution, lint yields, and fiber quality, in Crop Science, Vol. 63 p. 1209–1220. </p> <p>There has been limited introduction of new cover crop species into cotton (<em>Gossypium</em> <em>hirsutum</em> L.) production within the last 30 years. Mounting evidence shows that traditional cover cropping species may be detrimental to cotton production, either by depleting soil fertility with crop removal, immobilizing minerals from high carbon residue, or excessive quantity of residue remaining at planting. The objective of this study was to determine the effects of growing a novel cover crop species, carinata (<em>Brassica</em> <em>carinata</em> A. Braun), as a winter annual cover crop for cotton rotation in the southeastern Coastal Plain. Over a 2-year period, carinata, winter wheat (<em>Triticum</em> <em>aestivum</em> L.), and fallow covers were maintained over winter months, then rotated into cotton. Each year, seedcotton and lint yields were collected, along with subsamples for ginning and subsequent fiber quality analyses. Additionally, end-of-season plant mapping was conducted on plants from 1-m of row per plot to determine cover crop effects on boll formation, retention, and distribution, as well as canopy architecture.</p>
Comparative transmission genetics of introgressed chromatin in reciprocal advanced backcross populations in Gossypium (cotton) polyploids
<p>Introgression is a potential source of valuable genetic variation and interspecific introgression lines are important resources for plant breeders to access novel alleles. Experimental advanced-generation backcross populations contain individuals with genomic compositions similar to those resulting from natural interspecific hybridization and provide opportunities to study the nature and transmission pattern of donor chromatin in recipient genomes. Here, we analyze transmission of donor chromatin in reciprocal backcrosses between <em>G. hirsutum</em> and <em>G. barbadense</em>. Across the genome, recurrent backcrossing in both backgrounds yielded donor chromatin at slightly higher frequencies than the Mendelian expectation in BC<sub>5</sub>F<sub>1</sub> plants, while the average frequency of donor alleles in BC<sub>5</sub>F<sub>2</sub> segregating families was less than expected. In the two subgenomes of polyploid cotton, the rate of donor chromatin introgression was similar. Although donor chromatin was tolerated over much of the recipient genomes, 21 regions recalcitrant to donor alleles were identified. Only limited correspondence is observed between the recalcitrant regions in the two backgrounds, suggesting the effect of species background on introgression of donor segments. Genetic breakdown was progressive, with floral abscission and seed inviability ongoing during backcrossing cycles. Regions of either high or low introgression tended to be in terminal chromosomal regions that are generally rich in both genes and crossover events, with long stretches around the centromere having limited crossover activity resulting in relatively constant low introgression frequencies. Constraints on fixation and selection of donor alleles highlights the challenges of utilizing introgression breeding in crop improvement.</p>
Data from: Using perennial groundcover crops to suppress weeds and thrips in the southeast cotton belt
<p>This is digital research data corresponding to a published manuscript, Using perennial groundcover crops to suppress weeds and thrips in the southeast cotton belt, in Crop Science, Vol. 63 p. 3037 - 3050.</p> <p>Modern cotton production (<em>Gossypium hirsutum L.</em>) in the United States relies on chemical and physical inputs that increase the environmental and monetary costs of managing the crop. Perennial groundcover crops (PGCC) may reduce inputs by persisting in the interrow spaces of the cotton crop during summer months. A 2-year field study was conducted in Florence, SC, to evaluate growing PGCCs with cotton using a 4 × 4 Latin square consisting of four cover crop treatments: (1) a fallow, unplanted control, (2) annual ryegrass (<em>Lolium multiflorum Lam.</em>) monoculture, (3) a binary red clover (<em>Trifolium pratense L.</em>) and white clover (<em>Trifolium repens L.</em>) mixture, and (4) a trinary mixture of annual ryegrass, red clover, and white clover. Fallow and annual ryegrass treatments were killed with a burndown herbicide application, while treatments containing clovers were mowed. Plots were strip-tilled and planted with cotton in May each year. Interrow biomass, weed and thrips populations, and perennial clover populations were collected from June to October along with annual lint yields from cotton harvest in October.</p>
Efficacy of Cotton as a Dampener for Vibration Anesthetic Device
ClinicalTrials.gov study NCT06916468. IPD Sharing: NO. Countries: 1. Publications: 4.
DryShield vs Cotton Roll Isolation During Sealants Placement: Efficiency and Patient Preference
ClinicalTrials.gov study NCT02995369. IPD Sharing: NO. Countries: 1. Publications: 5.
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International Brain Laboratory public data
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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.