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126 results for “banana”
Figure 3 from: Prathapan KD, Poorani J, Amritha Kumari S, Anuradha C, Padmanaban B, Thanigairaj R (2019) Species composition and diagnoses of leaf- and fruit-scarring beetles (Coleoptera, Chrysomelidae) infesting bananas and plantains (Zingiberales, Musaceae) in the Indian subcontinent. Deutsche Entomologische Zeitschrift 66(2): 179-202. https://doi.org/10.3897/dez.66.47447
Figure 3 Basilepta subcostata (Jacoby). a. Head, dorsal view, male; b. Head, dorsal view, female; c. Pronotum, male; d. Pronotum, female; e. Middle leg; f. Hind leg.
Figure 15 from: Prathapan KD, Poorani J, Amritha Kumari S, Anuradha C, Padmanaban B, Thanigairaj R (2019) Species composition and diagnoses of leaf- and fruit-scarring beetles (Coleoptera, Chrysomelidae) infesting bananas and plantains (Zingiberales, Musaceae) in the Indian subcontinent. Deutsche Entomologische Zeitschrift 66(2): 179-202. https://doi.org/10.3897/dez.66.47447
Figure 15 Maximum Likelihood phylogeny of B. subcostata populations from Assam and Uttar Pradesh, India. The evolutionary history was inferred by using the Maximum Likelihood method and Tamura-Nei model. The tree with the highest log likelihood (-3489.32) is shown. The percentage of trees in which the associated taxa clustered together is shown next to the branches. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood (MCL) approach, and then selecting the topology with superior log likelihood value. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. This analysis involved 16 nucleotide sequences. Codon positions included were 1st+2nd+3rd+Noncoding. There was a total of 660 positions in the final dataset. Evolutionary analyses were conducted in MEGA X.
Figure 8 from: Prathapan KD, Poorani J, Amritha Kumari S, Anuradha C, Padmanaban B, Thanigairaj R (2019) Species composition and diagnoses of leaf- and fruit-scarring beetles (Coleoptera, Chrysomelidae) infesting bananas and plantains (Zingiberales, Musaceae) in the Indian subcontinent. Deutsche Entomologische Zeitschrift 66(2): 179-202. https://doi.org/10.3897/dez.66.47447
Figure 8 Naturally occurring epizootic of fungal pathogen, Beauveria bassiana on Basilepta subcostata.
Figure 14 from: Prathapan KD, Poorani J, Amritha Kumari S, Anuradha C, Padmanaban B, Thanigairaj R (2019) Species composition and diagnoses of leaf- and fruit-scarring beetles (Coleoptera, Chrysomelidae) infesting bananas and plantains (Zingiberales, Musaceae) in the Indian subcontinent. Deutsche Entomologische Zeitschrift 66(2): 179-202. https://doi.org/10.3897/dez.66.47447
Figure 14 Sphaeroderma cruenta sp. nov. a. Abdominal apex, male; b. Abdominal apex, female; c–f. Male genitalia: c. Aedeagus, lateral view; d. Aedeagus, ventral view; e. Aedeagus, dorsal view; f. Aedeagus apex, lateral view; g. Tignum; h, i. Spermatheca; j. Vaginal palpi.
Figure 13 from: Prathapan KD, Poorani J, Amritha Kumari S, Anuradha C, Padmanaban B, Thanigairaj R (2019) Species composition and diagnoses of leaf- and fruit-scarring beetles (Coleoptera, Chrysomelidae) infesting bananas and plantains (Zingiberales, Musaceae) in the Indian subcontinent. Deutsche Entomologische Zeitschrift 66(2): 179-202. https://doi.org/10.3897/dez.66.47447
Figure 13 Sphaeroderma cruenta sp. nov. Paratype (female) a. Adult, dorsal view; b. Head, dorsal view; c. Pronotum, dorsal view.
Figure 10 from: Prathapan KD, Poorani J, Amritha Kumari S, Anuradha C, Padmanaban B, Thanigairaj R (2019) Species composition and diagnoses of leaf- and fruit-scarring beetles (Coleoptera, Chrysomelidae) infesting bananas and plantains (Zingiberales, Musaceae) in the Indian subcontinent. Deutsche Entomologische Zeitschrift 66(2): 179-202. https://doi.org/10.3897/dez.66.47447
Figure 10 Bhamoina varipes (Jacoby). a, b. Dorsal view; c. Head, dorsal view; d. Pronotum, dorsal view; e. Lateral margin of pronotum.
Figure 12 from: Prathapan KD, Poorani J, Amritha Kumari S, Anuradha C, Padmanaban B, Thanigairaj R (2019) Species composition and diagnoses of leaf- and fruit-scarring beetles (Coleoptera, Chrysomelidae) infesting bananas and plantains (Zingiberales, Musaceae) in the Indian subcontinent. Deutsche Entomologische Zeitschrift 66(2): 179-202. https://doi.org/10.3897/dez.66.47447
Figure 12 Bhamoina varipes (Jacoby). a. Abdominal apex, male; b. Abdominal apex, female; c. Vaginal palpi; d. Tignum; e. Spermatheca; f–h. Male genitalia: f. Aedeagus, lateral view; g. Aedeagus, ventral view; h. Aedeagus, dorsal view.
Figure 1 from: Prathapan KD, Poorani J, Amritha Kumari S, Anuradha C, Padmanaban B, Thanigairaj R (2019) Species composition and diagnoses of leaf- and fruit-scarring beetles (Coleoptera, Chrysomelidae) infesting bananas and plantains (Zingiberales, Musaceae) in the Indian subcontinent. Deutsche Entomologische Zeitschrift 66(2): 179-202. https://doi.org/10.3897/dez.66.47447
Figure 1 Basilepta subcostata (Jacoby). a–c. Habitus, dorsal: a. Nominate form, male; b. Female; c. Rufous form, male; d. Male, lateral view; e. Female, lateral view.
Figure 11 from: Prathapan KD, Poorani J, Amritha Kumari S, Anuradha C, Padmanaban B, Thanigairaj R (2019) Species composition and diagnoses of leaf- and fruit-scarring beetles (Coleoptera, Chrysomelidae) infesting bananas and plantains (Zingiberales, Musaceae) in the Indian subcontinent. Deutsche Entomologische Zeitschrift 66(2): 179-202. https://doi.org/10.3897/dez.66.47447
Figure 11 Type of Sphaeroderma varipennis Jacoby (=B. varipes) (female). a. Dorsal view; b. Pronotum of S. varipennis; c. Anterolateral corners of pronotum (magnified).
Figure 7 from: Prathapan KD, Poorani J, Amritha Kumari S, Anuradha C, Padmanaban B, Thanigairaj R (2019) Species composition and diagnoses of leaf- and fruit-scarring beetles (Coleoptera, Chrysomelidae) infesting bananas and plantains (Zingiberales, Musaceae) in the Indian subcontinent. Deutsche Entomologische Zeitschrift 66(2): 179-202. https://doi.org/10.3897/dez.66.47447
Figure 7 Damage caused by B. subcostata (Jacoby) on banana. a. Leaf whorl showing scarring damage; b. Scars on spindle leaf; c. Scars on leaf; d, e. Scarring on leaf petiole; f. Flower damage; g. Bract damage; h–i. Damage on young fruits and emerging bunch; j–l. Fruit damage.
Data from: The banana (Musa acuminata) genome and the evolution of monocotyledonous plants
Bananas (Musa spp.), including dessert and cooking types, are giant perennial monocotyledonous herbs of the order Zingiberales, a sister group to the well-studied Poales, which include cereals. Bananas are vital for food security in many tropical and subtropical countries and the most popular fruit in industrialized countries1. The Musa domestication process started some 7,000 years ago in Southeast Asia. It involved hybridizations between diverse species and subspecies, fostered by human migrations2, and selection of diploid and triploid seedless, parthenocarpic hybrids thereafter widely dispersed by vegetative propagation. Half of the current production relies on somaclones derived from a single triploid genotype (Cavendish)1. Pests and diseases have gradually become adapted, representing an imminent danger for global banana production3, 4. Here we describe the draft sequence of the 523-megabase genome of a Musa acuminata doubled-haploid genotype, providing a crucial stepping-stone for genetic improvement of banana. We detected three rounds of whole-genome duplications in the Musa lineage, independently of those previously described in the Poales lineage and the one we detected in the Arecales lineage. This first monocotyledon high-continuity whole-genome sequence reported outside Poales represents an essential bridge for comparative genome analysis in plants. As such, it clarifies commelinid-monocotyledon phylogenetic relationships, reveals Poaceae-specific features and has led to the discovery of conserved non-coding sequences predating monocotyledon–eudicotyledon divergence.
FIGURE 14 in Aleurodicus talamancensis, a new whitefly species damaging plantation bananas in Costa Rica, with discussion of a montane orchidfeeding population (Sternorrhyncha, Aleyrodidae)
FIGURE 14. Mature banana leaf completely covered by immature stages of Aleurodicus talamancensis.
Conservation status assessment of banana crop wild relatives using species distribution modelling
<p><strong>Aim: </strong>Crop wild relatives (CWR) are an essential source of genetic material for the improvement of certain traits in related crop species. Despite their importance, increasing public, scientific and political support, large gaps exist in the amount of genetic material collected and conserved of many CWR. Here, we construct a dataset on the distribution of wild banana species (Musa spp.) and assess their risk and conservation status. We deal with the questions (1) what areas are potentially suitable for wild banana species (2) how much of the wild banana diversity is currently at risk or insufficiently conserved ex- and in-situ.</p> <p><span><strong>Location: </strong>Native distribution area of wild banana species, ranging from the northeastern states of India to northeastern Australia.</span></p> <p><span><strong>Methods:</strong> We assessed the potential environmental range of wild species using a species distribution modelling approach with MaxEnt. Extinction risk was evaluated following IUCN criterion B and the <i>ex- </i>and <i>in-situ</i> conservation status was assessed using an indicator for biodiversity and sustainable development targets.</span></p> <p><span><strong>Results:</strong> We found that 11 out of 59 assessed species can be considered as vulnerable and nine as endangered. Highest species richness was found along the border of south China and northern Vietnam, in the northeastern states of India and on the Malayan peninsula. Our distribution modelling approach indicates that the northern Indo-Burmese region has the highest environmental suitability for most wild banana species and that lowland rainforests in general are highly suitable for bananas. Assessment of <i>in</i>- and <i>ex-situ</i> conservation status indicates that 56 out of 59 assessed species are currently insufficiently conserved <i>ex-situ</i> and that 49 are of high priority for further conservation. Additional <i>in-situ</i> conservation is of high priority for six species and of medium priority for 40 species.</span></p> <p><span><strong>Main Conclusions:</strong> To date, little of the banana CWR are sufficiently conserved both <i>in- </i>and <i>ex-situ</i>.</span></p>
Figure 3 from: Le Thi L, Mertens A, Vu DT, Vu TD, Anh Minh PL, Duc HN, de Backer S, Swennen R, Vandelook F, Panis B, Amalfi M, Decock C, Gomes SIF, Merckx VSFT, Janssens SB (2022) Diversity of Fusarium associated banana wilt in northern Viet Nam. MycoKeys 87: 53-76. https://doi.org/10.3897/mycokeys.87.72941
Figure 3 Maximum Likelihood topology obtained via heuristic search algorithm of the combined rpb1, rpb2 and tef1a data matrix. Bootstrap support (ML-BS) values above 50 are indicated with a dot, ML-BS values above 75 are indicated with an asterisk. No indication above the branches indicates a ML-BS value below 50. Newly included accessions are indicated in red. FOSC: Fusarium oxysporum species complex, FFSC: Fusarium fujikuroi species complex.
Figure 2 from: Le Thi L, Mertens A, Vu DT, Vu TD, Anh Minh PL, Duc HN, de Backer S, Swennen R, Vandelook F, Panis B, Amalfi M, Decock C, Gomes SIF, Merckx VSFT, Janssens SB (2022) Diversity of Fusarium associated banana wilt in northern Viet Nam. MycoKeys 87: 53-76. https://doi.org/10.3897/mycokeys.87.72941
Figure 2 A overall view of a banana plant infected by Fusarium wilt B detailed view of wilted plant C radial cutting of Fusarium-infected banana pseudostem D tangential cutting of Fusarium-infected banana pseudostem.
Figure 1 from: Le Thi L, Mertens A, Vu DT, Vu TD, Anh Minh PL, Duc HN, de Backer S, Swennen R, Vandelook F, Panis B, Amalfi M, Decock C, Gomes SIF, Merckx VSFT, Janssens SB (2022) Diversity of Fusarium associated banana wilt in northern Viet Nam. MycoKeys 87: 53-76. https://doi.org/10.3897/mycokeys.87.72941
Figure 1 Distribution map of localities in northern Viet Nam where Fusarium wilt was observed. Colours indicate different Fusarium strains or species. Squares indicate Fusarium infections of wild bananas; circles indicate infections of cultivated bananas.
Supplementary material 1 from: Le Thi L, Mertens A, Vu DT, Vu TD, Anh Minh PL, Duc HN, de Backer S, Swennen R, Vandelook F, Panis B, Amalfi M, Decock C, Gomes SIF, Merckx VSFT, Janssens SB (2022) Diversity of Fusarium associated banana wilt in northern Viet Nam. MycoKeys 87: 53-76. https://doi.org/10.3897/mycokeys.87.72941
Table S1
Sensory analysis of gluten-freee Foods produced with funcional food: green banana flour.
<p>Completion of course work.</p>
Fig. 1 in Meroncidius intermedius (Orthoptera: Tettigoniidae): a threat to Brazilian banana
Fig. 1. Adults (a), nymphs (b) and damage (c, d) of Meroncidius intermedius (Orthoptera: Tettigoniidae) in banana cultivar Pacovan (genotype AAB).
FIGURE 53. Awaous banana, ROM 88830, 105 in Annotated list and key to the stream fishes of Trinidad & Tobago
FIGURE 53. Awaous banana, ROM 88830, 105 mm SL, Matura River, Trinidad.
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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.