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746 results for “Brassica”
FIGURE 3 in A new species of Brassica (Brassicaceae) from Bolkar Mountains (Türkiye) with morphological and molecular evidence
FIGURE 3. Habitus and habitat of Brassica huseyin-duralii, A-B) habitus, C-D) habitat of new species [above Meydan Platea, photos were taken by Ahmet Savran (A) and Ali Keskin (B,C,D)]
FIGURE 2 in A new species of Brassica (Brassicaceae) from Bolkar Mountains (Türkiye) with morphological and molecular evidence
FIGURE 2. Phylogenetic placement of Brassica huseyin-duralii based on Internal Transcribed Spacer (ITS). Phylogenetic tree is derived from Bayesian analysis. Posterior probabilities (> 0.5) and bootstrap values (derived from maximum likelihood analysis) are given above and belowe the branches, respectively. Brassica huseyin-duralii and its close relatives B. elongata and B. repanda are highlighted by color.
FIGURE 4 in A new species of Brassica (Brassicaceae) from Bolkar Mountains (Türkiye) with morphological and molecular evidence
FIGURE 4. The digital image of some morphological characteristics of Brassica huseyin-duralii, A) flowering stem, B)fruity stem, C) rosette leaves, D) rosette leaf hairs, E) glabrous pedicel, F) hairy pedicel, G, H, I) Inflorescence and flowers, J) sepal shape and hairs, K) petal shape, L) stamens, M) pistil, N) siliqua, O) valve (carpel) sructure, P) valve and seed, R) seeds.
Aphid-induced phytochemicals in Brassica juncea (L.) Czern & Coss. afflicting host preference and bionomics of Lipaphis erysimi (Kaltenbach)
<p>Bionomics of an insect and metabolic flux of the host plant are important tools to decipher the status of plant resistance against insect species. This study illuminates vital information on aphid-induced levels of phytochemicals in the siliquae<em> </em>of <em>Brassica juncea</em> cultivars and their effect on host selection and population growth parameters of <em>Lipaphis erysimi</em>. The current study unveiled that the siliquae preference, intrinsic rate of increase (r), finite rate of increase (λ), gross reproductive rate (GRR) and net reproductive rate (R0) were significantly lower on Pusa Mustard 27, DRMR 150-35, RLC 3, NRCHB 101, Pusa Mustard 26 and Pusa Mustard 25. However, mean generation time (T) and doubling time (DT) of <em>L. erysimi</em> were significantly longer (P<0.001) in these genotypes. These cultivars were also found with elevated levels of aphid-induced phytochemicals and their associated enzymes, except in a few cases. Total antioxidants, FRAP, chlorophyll A, total chlorophyll, AO, catalase, PAL and myrosinase were found to contribute 49.18 to 85.30% variation for siliquae preference and bionomics of <em>L. erysimi</em> on the test <em>B. juncea</em> cultivars. The study revealed that phenols, antioxidants, chlorophyll A, chlorophyll B, total carotenoids, AO, APX, PAL, TAL and myrosinase had significant and negative direct consequences on the siliquae preference and bionomics, thus can be exploited as biochemical markers to identify sources of resistance against <em>L. erysimi</em>. Further, DRMR 150-35, NRCHB 101, RLC 3, Pusa mustard 26, RH 749, and Pusa Mustard 27 were found with greater aphid-induced defence phytochemicals and detrimental effects on the host selection and bionomics of <em>L. erysimi</em>, thus can be deployed in <em>Brassica</em> improvement program.</p>
DeepCanola: Phenotyping Brassica Pods Using Semi-Synthetic Data and Active Learning
<p>Dataset accomapnying the publication: <em>DeepCanola: Phenotyping Brassica Pods Using Semi-Synthetic Data and Active Learning </em>by Van Vliet, Atkins et al.</p> <p>We provide model weights, training and vlidation datasets, as well as phenotype outputs. Each file/folder is outlined below:</p> <ul> <li><em>deepcanola.pth - </em>Model weights for the final Model 4, named DeepCanola</li> <li><em>generated_datasets</em> - Datasets generated at each stage of the active learning process, datasets 1-4 <ul> <li>Each folder is an iteration of the active learning process, inside each folder are the generated images and associated annotations stored in the COCO format.</li> </ul> </li> <li><em>real_world_datasets - </em>Real-world datasets used for either creation of the pod pools or validation. Datasets include: <ul> <li><em>br9</em> - Ordered and disordered dataset of images with generated pod length data of the ordered images stored in the `br9_gt_lengths.csv` file</li> <li><em>br11</em> - Ordered and disordered dataset of images only</li> <li><em>br17</em> - Ordered dataset with ground-truth of images with length annotations collected in ImageJ and stored in the `BR017 POD SCAN DATA.csv` file.</li> <li><em>misc</em> - Dataset of m<span>iscellaneous images including Brassica napus from Rothamstead and brassica relatives</span></li> </ul> </li> <li><em>data_generation_pools</em> - Pools used to generate semi-synthetic data at each step of the active learning process. Pools include: <ul> <li><em>background_pool</em> - Created background images to be selected at random by the semi-synthetic data generation script</li> <li><em>pod_pools - </em>Pools of pods used in the semi-synthetic data generation process. Pod pools include: <ul> <li><em>br9 - </em>673 pods with associated masks</li> <li><em>br9 and br17 - </em>673 + 332 pods with associated masks</li> </ul> </li> </ul> </li> <li><em>deepcanola_outputs - </em>Phenotype data outputs generated by DeepCanola. Each output is stored as a .csv file of both length measurements of each pod (with <em>_objects.csv</em> suffix), and average length measurements per image (with <em>_averages.csv</em> suffix). Outputs include: <ul> <li><em>br9_ordered</em></li> <li><em>br9_disordered</em></li> <li><em>br17</em></li> </ul> </li> </ul>
Predation on sentinel prey increases with increasing latitude in Brassica-dominated agroecosystems
In natural ecosystems, arthropod predation on herbivore prey is higher at lower latitudes, mirroring the latitudinal diversity gradient observed across many taxa. This pattern has not been systematically examined in human-dominated ecosystems, where frequent disturbances can shift the identity and abundance of local predators, altering predation rates from those observed in natural ecosystems. We investigated the how latitude, biogeographical, and local ecological factors influenced arthropod predation in Brassica oleracea dominated agroecosystems in 55 plots spread among 5 sites in the United States and 4 sites in Brazil, spanning at least 15º latitude in each country. In both the United States and Brazil, arthropod predator attacks on sentinel model caterpillar prey were highest at the highest latitude studied and declined at lower latitudes. The rate of increased arthropod attacks per degree latitude was higher in the United States and the overall gradient was shifted poleward as compared to Brazil. PiecewiseSEM analysis revealed that aridity mediates the effect of latitude on arthropod predation and largely explains the differences in the intensity of the latitudinal gradient between study countries. Neither predator richness, predator density, nor predator resource availability predicted variation in predator attack rates. Only greater non-crop plant density drove greater predation rates, though this effect was weaker than the effect of aridity. We conclude that climatic factors rather than ecological community structure shapes latitudinal arthropod predation patterns and that high levels of aridity in agroecosystems may dampen the ability of arthropod predators to provide herbivore control services as compared to natural ecosystems. --
Annotated patches of whole oilseed rape (Brassica napus) plant images created using the MapReader pipeline
<p><strong>Background and Dataset Creation:</strong></p> <p>Patches derived from whole images of oilseed rape (<em>Brassica napus</em>) plants from the <a href="https://research.aber.ac.uk/en/datasets/collection-of-side-view-and-top-view-rgb-images-of-brassica-napus">'Collection of side view and top view RGB images of Brassica napus from a large scale, high throughput experiment'</a> dataset and their associated annotations, which were used to train, validate and test patch classification models as described in the following paper:</p> <p>Corcoran, E., Hosseini, K., Siles, L., Kurup, S., and Ahnert, S. 2024. 'Automated dynamic phenotyping of whole oilseed rape (Brassica napus) plants from images collected under controlled conditions', Frontiers in Plant Science (under review). </p> <p>Patches were created and annotated using the <a href="https://github.com/Living-with-machines/MapReader">MapReader</a> pipeline. Please see: </p> <ul> <li>Kasra Hosseini, Daniel C. S. Wilson, Kaspar Beelen, and Katherine McDonough. 2022. MapReader: a computer vision pipeline for the semantic exploration of maps at scale. In Proceedings of the 6th ACM SIGSPATIAL International Workshop on Geospatial Humanities (GeoHumanities '22). Association for Computing Machinery, New York, NY, USA, 8–19. <a href="https://doi.org/10.1145/3557919.3565812" rel="nofollow">https://doi.org/10.1145/3557919.3565812</a></li> <li>Kasra Hosseini, Rosie Wood, Andy Smith, Katie McDonough, Daniel C.S. Wilson, Christina Last, Kalle Westerling, and Evangeline Mae Corcoran. “Living-with-machines/mapreader: End of Lwm”. Zenodo, July 27, 2023. <a href="https://doi.org/10.5281/zenodo.8189653" rel="nofollow">https://doi.org/10.5281/zenodo.8189653</a>.</li> </ul> <p><strong>File structure:</strong></p> <p><em><strong>Annotations</strong></em></p> <p>The <strong>'annotations_six_label_sv_5.zip'</strong> folder contains annotations for the entire patch dataset in .csv format, these files have two columns <strong>'image_id'</strong>, <strong>'label'</strong> in which:</p> <ul> <li><strong>'image_id'</strong> = the path to each image patch</li> <li><strong>'label'</strong> = the label assigned to each patch by the annotator indicated which part of the plant the patch primarily contained, or if it was part of the background. Labels: <strong>'0'</strong> = non-plant background, <strong>'1'</strong> = open flower, <strong>'2'</strong> = flower bud, <strong>'3'</strong> = leaf, <strong>'4'</strong> = greed pod containing seed, <strong>'5'</strong> = branch. </li> </ul> <p><em><strong>Patches</strong></em></p> <p>The 'b_napus_patch_data.zip' folder contains all patches in csv format. Each file is named in a consistent format e.g. "patch-1580-330-1590-340-#2018-07-06_00_VIS_sv_000-0-0-0.png#.PNG" where '1580-330-1590-340' are the x and y coordinates of the patch boundary and '#2018-07-06_00_VIS_sv_000-0-0-0.png#' indicates the image in the <a href="https://research.aber.ac.uk/en/datasets/collection-of-side-view-and-top-view-rgb-images-of-brassica-napus">'Collection of side view and top view RGB images of Brassica napus from a large scale, high throughput experiment'</a> from which the patch was derived. </p>
FIGURE 3 in Brassica trichocarpa (Brassicaceae), a new species from Sicily
FIGURE 3. SEM micrographs of seed surface at different magnification of A. Brassica trichocarpa (from the type locality: Mt. Cuccio, Palermo,). B. B. villosa subsp. villosa (from the type locality: Mt. Occhio, Palermo). C. B. macrocarpa (from the type locality: Favignana, Egadi Islands). D. B. villosa subsp. tinei (from the type locality: Marianopoli, Palermo). E. B. rupestris subsp. rupestris (from the type locality: Mt. Pellegrino, Palermo).
FIGURE 2 in Brassica trichocarpa (Brassicaceae), a new species from Sicily
FIGURE 2. Leaf variability of Brassica trichocarpa. Illustration by Salvatore Brullo based on C. Brullo, S. Brullo, G. Giusso del Galdo & V. Ilardi s. n. (CAT!).
FIGURE 6 in Brassica trichocarpa (Brassicaceae), a new species from Sicily
FIGURE 6. Diagnostic morphological features of Brassica macrocarpa. A. Flower, upper view. B. Flower, lateral view. C. Petals. D. Outer sepals. E. Inner sepals. F. Bud. G. Stamens and pistil. H. Anthers, dorsal and ventral view. I. Pistils. J. Inner gland. K. Outer gland. L. Dried fruit, dorsal view. M. Dried fruits (lateral view). N. Dried fruit (cross-section). O. Seeds. Illustration by Salvatore Brullo based on S. Brullo, s. n. (CAT!).
FIGURE 5 in Brassica trichocarpa (Brassicaceae), a new species from Sicily
FIGURE 5. Diagnostic morphological features of Brassica villosa subsp. villosa. A. Flower, upper view. B. Flower, lateral view. C. Bud. D. Petal. E. Outer sepals. F. Inner sepals. G. Stamens and pistil. H. Anthers, dorsal and ventral view. I. Pistils. J. Outer gland. K. Inner gland. L. Dried fruit, dorsal view. M. Dried fruits (lateral view). N. Dried fruit (cross-section). O. Seeds. Illustration by Salvatore Brullo based on V.Ilardi s.n. (CAT!) and C. Brullo, S. Brullo, G. Giusso del Galdo & V. Ilardi s. n. (CAT!).
FIGURE 4 in Brassica trichocarpa (Brassicaceae), a new species from Sicily
FIGURE 4. Phenological features of Brassica trichocarpa. A. Flowered plant in natural habitat. B. Basal leaves. C. Fructified inflorescence. D. Inflorescence. E. Open flower with pistil. F. Fruit. G. Fruit (cross section). H. Fruit (longitudinal section) (Photos by V. Ilardi).
FIGURE 1 in Brassica trichocarpa (Brassicaceae), a new species from Sicily
FIGURE 1. Diagnostic morphological features of Brassica trichocarpa. A. Flower, upper view. B. Flower, lateral view. C. Bud. D. Petals. E. Outer sepals. F. Inner sepals. G. Stamens and pistil. H. Anthers, dorsal and ventral view. I. Pistils. J. Inner gland. K. Outer gland. L. Dried fruit, dorsal view. M. Dried fruit, lateral view. N. Dried fruit, cross-section. O. Fresh fruit, lateral view. P. Fresh fruit, cross-section. Q. Seeds. Illustration by Salvatore Brullo based on S. Brullo & V. Ilardi s.n. (CAT!) and C. Brullo, S. Brullo, G. Giusso del Galdo & V. Ilardi s. n. (CAT!).
The Evolutionary History of Wild, Domesticated, and Feral Brassica oleracea (Brassicaceae)
<p>Understanding the evolutionary history of crops, including identifying wild relatives, helps to provide insight for conservation and crop breeding efforts. Cultivated <i>Brassica oleracea</i> has intrigued researchers for centuries due to its wide diversity in forms, which include cabbage, broccoli, cauliflower, kale, kohlrabi, and Brussels sprouts. Yet, the evolutionary history of this species remains understudied. With such different vegetables produced from a single species, <i>B. oleracea </i>is a model organism for understanding the power of artificial selection. Persistent challenges in the study of <i>B. oleracea</i> include conflicting hypotheses regarding domestication and the identity of the closest living wild relative. Using newly generated RNA-seq data for a diversity panel of 224 accessions, which represents 14 different <i>B. oleracea</i> crop types and nine potential wild progenitor species, we integrate phylogenetic and population genetic techniques with ecological niche modeling, archaeological, and literary evidence to examine relationships among cultivars and wild relatives to clarify the origin of this horticulturally important species. Our analyses point to the Aegean endemic <i>B. cretica</i> as the closest living relative of cultivated <i>B. oleracea</i>, supporting an origin of cultivation in the Eastern Mediterranean region. Additionally, we identify several feral lineages, suggesting that cultivated plants of this species can revert to a wild-like state with relative ease. By expanding our understanding of the evolutionary history in <i>B. oleracea</i>, these results contribute to a growing body of knowledge on crop domestication that will facilitate continued breeding efforts including adaptation to changing environmental conditions.</p>
brassica-snps supplementary materials
<p>This repository contains the following files:</p> <ul> <li>brassica-bsa-supplementary.docx - supplementary methods description</li> <li>st1_histogram_flowering_time_Brassica_F1.xlsx - Supplementary Table 1</li> <li>st2_bulk_sequencing_yields.docx - Supplementary Table 2</li> <li>st3_seacompare.html - Supplementary Table 3</li> <li>st4_snpeff.xlsx - Supplementary Table 4</li> <li>st5_seqstats_genome.xlsx - Supplementary Table 5</li> </ul>
Genotyping-by-Sequencing data of weedy and domesticated Brassica rapa L.
<p>The study of domestication contributes to our knowledge of evolution and crop genetic resources. Human selection has shaped wild <em>Brassica rapa</em> into diverse turnip, leafy, and oilseed crops. Despite its worldwide economic importance and potential as a model for understanding diversification under domestication, insights into the number of domestication events and initial crop(s) domesticated in <em>B. rapa</em> have been limited due to a lack of clarity about the wild or feral status of conspecific non-crop relatives. To address this gap and reconstruct the domestication history of <em>B. rapa</em>, we analyzed 68,468 genotyping-by-sequencing-derived SNPs for 416 samples in the largest diversity panel of domesticated and weedy <em>B. rapa</em> to date. To further understand the center of origin, we modeled the potential range of wild <em>B. rapa</em> during the mid-Holocene. Our analyses of genetic diversity across <em>B. rapa</em> morphotypes suggest that non-crop samples from the Caucasus, Siberia, and Italy may be truly wild, while those occurring in the Americas and much of Europe are feral. Clustering, tree-based analyses, and parameterized demographic inference further indicate that turnips were likely the first crop type domesticated, from which leafy types in East Asia and Europe were selected from distinct lineages. These findings clarify the domestication history and nature of wild crop genetic resources for <em>B. rapa</em>, which provides the first step toward investigating cases of possible parallel selection, the domestication and feralization syndrome, and novel germplasm for <em>Brassica</em> crop improvement.</p>
data on life table and biology of Brevicoryne brassicae and Lipaphis pseudobrassicae
<p>A file on the biology and another on the life table and fertility of Brevicoryne brassicae and Lipaphis pseudobrassicae. The Life Table and Fertility Archive is a program for obtaining results called "Tabvida". The handbook for understanding the program can be obtained at the link: https://www.embrapa.br/busca-de-publicacoes/-/publicacao/870882/tabvida-sistema-computacional-para-calculo-de-parametros-biologicos- aphid-population-growth-and</p>
Seed coating for Brassica napus L.
<p>These .xlsx files contain results of seed coating analyses in canola (<em>B. napus</em> L.) plants.</p> <p>1. Biomass.xlsx and Length.xlsx files include the results showing the effect of seed coating on canola seedlings growth. </p> <p>2. Gene_expression.xlsx file includes the relative expression level of <em>BnRSH</em> genes in the canola seedlings germinated from uncoated (control) or coated seeds. </p> <p>3. Germination.xlsx file includes final germination percentage (FGP), index of germination velocity (IGV), and mean germination time (MGT) of canola seeds depending on seed coating.</p> <p>4. Seed_weight.xlsx file includes the seed weight depending on different variants of seed coating.</p> <p>5. SOD.xlsx file includes results of the measurements of the activity of SOD in canola seedlings germinated from uncoated and coated seeds.</p> <p>6. Fungi_growth.xlsx file includes results showing the growth inhibition of fungi plant pathogens species<em>.</em></p> <p><em>7. S</em>tatistical analysis.</p>
Molecular markers used to test brassica oleracea for resistance to downy mildew
<p>Molecular markers used to test brassica oleracea for resistance to downy mildew</p>
Fig. 4. A in Hairy root transformation of Brassica rapa with bacterial halogenase genes and regeneration to adult plants to modify production of indolic compounds
Fig. 4. A. Growth of wild type root cultures on different Trp derivatives as compared to growth on MS medium only. B. Correlation of the relative growth and the production of different Cl-Trp compounds.
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