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422 results for “Weed”
Figure 3 in Preliminary assessment of weed population in vegetable and fruit farms of Taif, Saudi Arabia
Figure 3. The density of various weed families in vegetable (CROP A) and fruit (CROP B) farms.
Figs. 1-2 in Primera cita de Plocamaphis flocculosa (Weed, 1891) (Hemiptera: Aphididae: Aphidinae: Macrosiphini) en la Península Ibérica.
Figs. 1-2.- Plocamaphis flocculosa (Weed).
Delivering metribuzin from biodegradable nanocarriers: Assessing herbicidal effects for soybean plant protection and weed control
<p>The data presents the indicators of soybean and soil health after metribuzin biodegradable nanocarriers and conventional metribuzin. Besides, the uptake and distribution of metribuzin in soil and weed plants (Amaranthus retroflexus) were associated with weed control evaluations.</p>
Data from: Direct and indirect effects of landscape and field management intensity on carabids through trophic resources and weeds
<p>Carabids are important biological control agents of weeds and other pests in agricultural fields. The carabid community is built upon direct and indirect ecological effects of landscape complexity, field management intensity and biotic components that in interaction make any prediction of community size and composition challenging.</p> <p>We analyse a large-scale sample of 60 European cereal fields using Structural Equation Modelling to quantify the direct effects of field management intensity and the surrounding landscape, and their indirect effect via biotic components, on carabid diversity.</p> <p>Our results highlight that direct and indirect effects of increasing landscape complexity, mediated by trophic resources, mainly affect carabids positively. Field management intensity only ever affects carabids through indirect effects that are generally negative, by suppressing standing weeds and weed seeds.</p> <p>Indirect effects on granivore carabid species depended on weed seed availability whereas omnivores depended on the availability of both weed seeds and animal prey.</p> <p><i>Synthesis and applications</i><span>: A consideration of both the direct and indirect effects of landscape and field management is necessary for predicting carabid communities and with interactions. These effects, mediated via trophic resources, supports the diversity and abundance of carabid communities and their provision of ecosystem services. Our results show that promoting crop diversity and connectivity to semi-natural habitats will directly enhance carabid communities in farmland by manipulating their migration from source habitats. A reduction in field management intensity will preserve local standing weeds and weed seeds, and indirectly support carabid communities. These local and landscape modifications could contribute to improve the natural regulation of pests and weeds by carabids.</span></p>
Do early-successional weeds facilitate or compete with seedlings in forest restoration? Disentangling abiotic vs. biotic factors
<p>Census data for seedlings part of a weed exclusion experiment at Sal del Rey, Texas within a larger field where ~100,000 seedlings were planted in October-November 2018. Records seedling height, vigor (0 - dead, > 0 - alive), branching, and animal damage for 158 individuals of eight species classified by growth habit (fast/slow) and distributed in control and exclusion (mowed) plots across seven censuses.</p>
Figure 3 Alhagi maurorum, plant with typical Aceria alhagi n in A new Aceria species (Acari:Trombidiformes: Eriophyoidea) from West Asia, a potential biological control agent for the invasive weed camelthorn, Alhagi maurorum Medik. (Leguminosae)
Figure 3 Alhagi maurorum, plant with typical Aceria alhagi n. sp. symptoms where the shoot tips
A non-native earthworm shifts the seed predation dynamics of a native weed
<p class="BodyAA"><span>Seed predators both consume and disperse seeds, with important consequences for the population dynamics of many plant species. The net effect of multiple seed predators depends on the relative proportion of the seed pool each predator obtains, and this proportion should reflect species-specific habitat preferences. We studied the effect of the non-native earthworm, <i>Lumbricus terrestris</i>, on seed loss dynamics in the native weed, <i>Ambrosia trifida</i> (giant ragweed)<i>. </i>Giant ragweed seeds are predated by mice, but <i>L. terrestris</i> may protect the seeds against rodent predation by caching them in its burrows. We investigated these interactions, as well as how environmental factors affected net seed losses by competing seed predators. </span></p> <p class="Default">A two-year field study was conducted in which we measured removal of experimentally dispersed giant ragweed seeds by earthworms and mice in habitats varying in plant cover. We analyzed the relative proportion of seeds taken by each species under the varying experimental conditions. </p> <p class="Default">Species-specific responses to abiotic conditions and plant cover drove variation in the share of seeds taken by earthworms versus mice, with earthworms gaining relatively more seeds under warmer, wetter conditions and low plant cover habitats, and mice obtaining more seeds under colder, drier conditions and high plant cover habitats. </p> <p class="Default">Plant cover and weather conditions also determined which predator species accessed seeds first, and this conferred a competitive advantage that was compounded over time.</p> <p class="Default">Earthworms cached some seeds under all experimental conditions, suggesting that <i>L. terrestris </i>can<i> </i>act mutualistically with giant ragweed by making seeds inaccessible to rodent seed predators. </p> <p class="Default"><i>Synthesis and applications. </i>Our results support the view that interactions among the environment and competing seed predators determine the fate of seed pools. The data also support the hypothesis that <i>L. terrestris</i> facilitates giant ragweed by competing with mice for giant ragweed seeds, likely contributing to its spread across the landscape and hindering effective weed management. <i>Lumbricus terrestris </i>is prevalent throughout temperate regions and may similarly affect seed predation dynamics of other large-seeded species, impacting plant communities across a range of habitats.</p>
T2.3 Raw data: Allelochemicals in different wheat cultivars in presence of two weed species
<p>The dataset contains raw data in various MS Excel sheets related to a manuscript.</p> <p>Content:</p> <p>Sheet 1: Metadata and abbreviations<br> Sheet 2: Data of chemical analyses for benzoxazinoids of 4 winter wheat cultivars (i.e., Adesso, Element, Maurizio, NS 40S) grown alone or in the presence of 2 weed species (i.e., <em>Lolium rigidum</em>, <em>Portulaca oleracea</em>)<br> Sheet 3: Means and standard deviations of the benzoxazinoids data<br> Sheet 4: Data of chemiocal analyses for polyphenols for the 4 wheat cultivars grown alone or in presence of the 2 weed species<br> Sheet 5: Means and standard deviations of the polyphenols data<br> Sheet 6: Germination and growth data of the bioassays carried out with the wheat cultivars and the weed species<br> Sheet 7: Means and standard deviations of the germination and growth data</p>
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>
Datasets related to identification of invasive weeds S. elaeagnifolium, S. rostratum and S. nigrum as potential ToBRFV hosts
<p>These datasets highlight the invasive weeds S. elaeagnifolium, S. rostratum and S. nigrum as potential ToBRFV hosts, and support the data provided directly in the scientific publication titled "<em>Solanum elaeagnifolium</em> and <em>S</em>. <em>rostratum</em> as potential hosts of the tomato brown rugose fruit virus", published in the <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0282441#ack">PLOS journal</a>. </p> <p>The data was obtained through a series of viral inoculations and bioassays, serological tests for viral infections (i.e. ELISA), viral RNA extraction and reverse transcription (RT)-PCR, as well as quantitative RT-PCR (RT-qPCR). The methods are described directly in the scientific publication with indicators allowing for interoperability and reusability by fellow researchers. </p> <p>The provided datasets are discussed and interpreted in detail, as well as their subsequent results, in the scientific publication.</p> <p>This research was conducted within the VIRTIGATION project, which is part of the EU Open Research Data pilot. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 101000570.</p>
Microsatellite genotypes for adult and seedlings of the temperate seagrass (ribbon weed), Posidonia australis, from four meadows at Rottnest Island, Western Australia
<p>Adult shoots and seedings of the ribbon weed (<em>Posidonia australis</em> Hook.f.), a widespread temperate seagrass, were sampled from four meadows around Rottnest Island, Western Australia. The data set contains multilocus genotypes for adult shoots from four meadows and seedlings from three meadows over two consecutive years. The metadata file contains: Pop number (1 – 10), Sample site, Latitude (S), Longitude (E), individual sample code, year of sampling, life stage (adult shoot or seedling), genotypes (2 columns per locus). The seven polymorphic microsatellite loci are: <em>Pa</em>A1, <em>Pa</em>A105, <em>Pa</em>A120, <em>Pa</em>B6, <em>Pa</em>B8, <em>Pa</em>B112, <em>Pa</em>D113. Most genotypes are diploid, however, 3N genotypes are included.</p>
Raw data: Potential of different common (Fagopyrum esculentum Moench) and Tartary (Fagopyrum tataricum (L.) Gaertn.) buckwheat accessions to sustainably manage surrounding weeds
<p>Twenty-nine accessions of two buckwheat species (<em>Fagopyrum esculentum</em> Moench (common buckwheat) and <em>Fagopyrum tataricum</em> (L.) Gaertn. (Tartary buckwheat) were evaluated for their allelopathic potential against two resistant weeds, i.e. the monocot <em>Lolium rigidum</em> Gaud. and the dicot <em>Portulaca oleracea</em> L. The bulking use of synthetic herbicides and their consequent contamination of the environment and resulting increment of resistant weeds, imminently requires a solution to achieve sustainable weed management without the use of chemical inputs. The results obtained in this study suggest that buckwheat accessions can sustainably manage weeds through plant interference as competition or allelopathy. This research showed that accessions differ in their potential for sustainably manage both weeds, with <em>F. esculentum</em> accessions being more effective against <em>L. rigidum</em> and <em>F. tataricum</em> accessions against both, monocot and dicot weeds. The chemical profile of buckwheat accessions was evaluated to know the content of polyphenols in common and Tartary buckwheat accessions and to know more about their ability to sustainably manage weeds. Differences in the chemical profile between the two buckwheat species were clear. While common buckwheat accessions showed more orientin, vitexin and hyperoside, Tartary buckwheat accessions had higher amounts of rutin, quercetin and kaempferol. We propose that the screening and selection of accessions with strong polyphenol content and vigorous growth can be a step towards organic farming due to its relation to the weed management.</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>
Ancient varieties can help control weed density while preserving weed diversity
<p>Weeds are a major component of agricultural diversity affecting crop yield and ecosystem services. Compared to modern varieties, ancient wheat cultivars (released before 1960) are taller and this trait can be used to control weeds in organic farming systems, especially without herbicides. However, there is still a lack of quantitative assessments of the relative contribution of wheat breeding-history (ancient vs modern varieties) and synthetic inputs in explaining weed density and community structure. In this study, a field experiment was undertaken where five modern and five ancient varieties were either treated as in a conventional system with synthetic inputs (nitrogen, herbicide and fungicide) or as in an organic system without synthetic inputs. Crop light interception and weed density was recorded for 12 weeks until crop maturity. On average, ancient varieties reduced weed density by 17% compared with modern varieties, while the application of chemical inputs was responsible for an average reduction of 37%. The stronger competitive effect of ancient varieties was associated with increased sunlight interception. Species richness was higher in the absence of inputs for some weeks, but not by the end of the experiment. The field-based results illustrated that ancient varieties helped to control weed density in organic systems that do not rely on synthetic inputs to control weeds. Despite this effect of crop interference on weed density, a reduction in weed diversity was not observed. These findings could be of particular interest to promote agrobiodiversity in agricultural systems without synthetic inputs.</p>
Data from : Both long-term grasslands and crop diversity are needed to limit pest and weed infestations in agricultural landscapes
<p>Data used for analysis in Both long-term grasslands and crop diversity are needed to limit pest and weed infestations in agricultural landscapes </p>
Developing hierarchical density-structured models to study the national-scale dynamics of an arable weed
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Data from: Genome assembly of the ragweed leaf beetle, a step forward to better predict rapid evolution of a weed biocontrol agent to environmental novelties
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Data from: Not all weeds are created equal: a database approach uncovers differences in the sexual system of native and introduced weeds
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Effects of canopy cover on fruiting intensity and fruit removal of a tropical invasive weed
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Efficacy of cover crops for pollinator habitat provision and weed suppression
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OpenNeuro
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