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201 results for “Spodoptera”
Fig. 2 in Population variability of Spodoptera frugiperda (Lepidoptera: Noctuidae) in maize (Poales: Poaceae) associated with the use of chemical insecticides
Fig. 2. Dendrogram of genetic distance among Spodoptera frugiperda populations analyzed using ISSR molecular markers.
Figure 2 in A 6-year field monitoring of fall armyworm, Spodoptera frugiperda, in transgenic Bt maize in Brazil
Figure 2 Average number of fall armyworm larvae, Spodoptera frugiperda, collected in Bt hybrids, non-Bt hybrids and non-Bt hybrids sprayed with methomyl in 2015 and 2016 (period II), in Sete Lagoas and Nova Porteirinha. Average followed by the same upper-case letter between municipalities and same lower-case letter in each municipality do not differ statistically (Scott-Knott test at p ≤ 0.05).
Figure 1 in A 6-year field monitoring of fall armyworm, Spodoptera frugiperda, in transgenic Bt maize in Brazil
Figure 1 Average number of fall armyworm larvae, Spodoptera frugiperda collected in Bt hybrids, non-Bt hybrids and non-Bt hybrids sprayed with methomyl from 2011 to 2014 (period I), in Sete Lagoas and Nova Porteirinha. Average followed by the same upper-case letter between municipalities and same lower-case letter in each municipality do not differ statistically (Scott-Knott test at p ≤ 0.05).
Figure 2 in First report of Spodoptera frugiperda (Lepidoptera: Noctuidae) on Onion (Allium cepa L.) in South Kivu, Eastern DR Congo
Figure 2 Mean (±S.E) incidence of Spodoptera frugiperda in onion as a function of season and cropping system. 24 plots were considered in each cropping system. A and B represents the incidence in 2019 and 2020 respectively.
Figure 1 in First report of Spodoptera frugiperda (Lepidoptera: Noctuidae) on Onion (Allium cepa L.) in South Kivu, Eastern DR Congo
Figure 1 Spodoptera frugiperda larvae occurring in the onion crop at the experimental site. A: lesions induced on onion leaf epidermis; B: sixth instar larvae found inside onion leaves; C: severity of damage and faecal pellets in whorl of the onion plant; D: fifth instar larva found on the onion plant.
Figure 4 in First report of Spodoptera frugiperda (Lepidoptera: Noctuidae) on Onion (Allium cepa L.) in South Kivu, Eastern DR Congo
Figure 4 Rates of attack severity of Spodoptera frugiperda according the kind of onion crops. A and B: severity in 2019 and in 2020 respectively. 0: no visible leaf damage; 1: small lesions on leaf epidermis; 2: Small elongated (rectangular shaped) lesions (5) of up to 1.3 cm in length on leaf epidermis; 3: Several small to mid-sized 1.3 to 2.5 cm in length elongated lesions (5-10) on several leaves; 4: Several large elongated lesions (˃10), greater than 2.5 cm in length present on several leaves; 5: leaves almost completely destroyed.
Fig. 3 in Biology and reproductive capacity of Spodoptera eridania (Cramer) (Lepidoptera, Noctuidae) in different soybean cultivars
Fig. 3. Total number of eggs and larvae of Spodoptera eridania during the oviposition period in cultivars TMG Tabarana, BRS/MT Pintado, FMT Tucunaré and Monsoy 8757.
Figura 2 in Quimigación y bio-irrigación con pivote central para el control de Spodoptera frugiperda (J.E. Smith, 1797) (Lepidoptera: Noctuidae) en maíz en el Caribe seco colombiano
Figura 2. Número promedio de larvas vivas de S. frugiperda por metro lineal a lo largo de 43 dÍas de desarrollo del cultivo de maÍz, según los tratamientos evaluados. / Average number of live S. frugiperda larvae per linear meter over 43 days of development of the corn crop, according to the treatments evaluated.
Figura 3 in Quimigación y bio-irrigación con pivote central para el control de Spodoptera frugiperda (J.E. Smith, 1797) (Lepidoptera: Noctuidae) en maíz en el Caribe seco colombiano
Figura 3. Rendimiento de forraje fresco y seco de maÍz (t/ha) entre los diferentes tratamientos evaluados, para el control de S. frugiperda. No se evidenciaron diferencias significativas entre tratamientos usando la prueba de comparación múltiple de Tukey (α = 0,05). / Yield of fresh and dry maize forage (t/ha) between the different treatments evaluated, for the control of S. frugiperda. No significant differences were found between treatments using Tukey's multiple comparison test (α = 0.05).
Figura 1 in Quimigación y bio-irrigación con pivote central para el control de Spodoptera frugiperda (J.E. Smith, 1797) (Lepidoptera: Noctuidae) en maíz en el Caribe seco colombiano
Figura 1. Nivel de daño visual causado por S. frugiperda en maÍz según la escala de Davis. 1a-1c. Daño foliar leve. 1d-1f. Daño foliar moderado. 1g-1h. Daño foliar severo. 1i. Planta destruida. Adaptado de: MRI - IRAC (2019). / Level of visual damage caused by S. frugiperda in corn according to the Davis scale. 1a-1c. Slight foliar damage. 1d-1f. Moderate leaf damage. 1g-1h. Severe leaf damage. 1i. Destroyed plant. Adapted from: MRI - IRAC (2019).
Figure 3 in Partially purified Glycine max proteinase inhibitors: potential bioactive compounds against tobacco cutworm, Spodoptera litura (Fabricius, 1775) (Lepidoptera: Noctuidae)
Figure 3. Food assimilation (in mg) with respect to control when second-instar larvae of S. litura were given different concentrations of soybean PIs. Columns and bars represent the mean ± SE. Different letters above the columns representing each concentration indicate significant differences with Tukey's test at P ≤ 0.05.
Figure 2 in Partially purified Glycine max proteinase inhibitors: potential bioactive compounds against tobacco cutworm, Spodoptera litura (Fabricius, 1775) (Lepidoptera: Noctuidae)
Figure 2. Percentage survival of adults when second-instar larvae of S. litura were given different concentrations of soybean PIs. Columns and bars represent the mean ± SE. Different letters above the columns representing each concentration indicate significant differences with Tukey's test at P ≤ 0.05.
Figure 1 in Partially purified Glycine max proteinase inhibitors: potential bioactive compounds against tobacco cutworm, Spodoptera litura (Fabricius, 1775) (Lepidoptera: Noctuidae)
Figure 1. (A) Normal S. litura adult, (B–D) abnormality in adults observed at 100 µg/mL concentration of soybean PIs.
Figure 4 in Partially purified Glycine max proteinase inhibitors: potential bioactive compounds against tobacco cutworm, Spodoptera litura (Fabricius, 1775) (Lepidoptera: Noctuidae)
Figure 4. Trypsin activity in larvae of S. litura at different time intervals under the influence of partially purified soybean PIs.
Figure 1 in Resistance of rice genotypes to fall armyworm Spodoptera frugiperda (Lepidoptera: Noctuidae)
Figure 1 Dendrogram resulting from UPGMA multivariate cluster analysis (Euclidian distance), based on the length of larval, pre-pupal, pupal periods and total cycle (days) and total viability (%) and parameters of nutritional indices (Table 4 and Table 5) on rice genotypes for resistance to Spodoptera frugiperda (Lepidoptera: Noctuidae).Urutaí, GO, Brazil.
Figure 1 in Selection and molecular characterization of Bacillus thuringiensis strains efficient against soybean looper (Chrysodeixis includens) and Spodoptera species
Figure 1 Comparison of growth inhibitory symptoms of Spodoptera frugiperda larvae exposed to Bacillus thuringiensis β-exotoxins after eight days of inoculation. a: Positive control (strain HD-125); b: Negative control (water); c: Strain 773.
Figure 5 in Selection and molecular characterization of Bacillus thuringiensis strains efficient against soybean looper (Chrysodeixis includens) and Spodoptera species
Figure 5 Toxicity of Bacillus thuringiensis strains against three Spodoptera species. Means followed by the same letter do not differ statistically from one another by the Scott-Knott test at the 5% probability level.
Figure 4 in Selection and molecular characterization of Bacillus thuringiensis strains efficient against soybean looper (Chrysodeixis includens) and Spodoptera species
Figure 4 Profile of total and digested trypsin proteins produced by Bacillus thuringiensis strains eficiente against Chrysodeixis includens. (D) Proteins digested with trypsin; MM: SeeBlue® Plus2 Pre-Stained Standard Marker (Invitrogen, USA).
Figure 3 in Selection and molecular characterization of Bacillus thuringiensis strains efficient against soybean looper (Chrysodeixis includens) and Spodoptera species
Figure 3 Plasmid profiles of Bacillus thuringiensis efficient strains against Chrysodeixis includens. a: DNA extraction according to Fagundes et al. (2011); b: DNA extraction using QIAGEN kit (Invitrogen, USA).MM:1 Kb DNA ladder plus (Invitrogen, USA.The red rows indicate megaplasmids.
Figure 10 in Spodoptera cosmioides (Lepidoptera: Noctuidae) in Brazil: spatial distribution and relationship in the S. latifascia species group
Figure 10 Pairwise genetic distance (mean and standard error) in the S. latifascia group (S. cosmioides, S. descoinsi, S. evanida, and S. latifascia) based on sequences of the Cytochrome oxidase subunit I (COI) gene fragment, using Kimura-2 parameters (K2P) model. The dashed line highlights a 1% threshold of distance.
ScienceDex guides
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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.