Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
13
datasets available to search
ShareScore release 0.9.0
Dataset results
13 results for “crop interference”
Figure 7 in Interference and management of herbicide-resistant crop volunteers
Figure 7. Individual rows of weedy rice accessions or cultivated rice cultivars 8 d following a post-flood application of benzobicyclon at 371 g ai ha−1. Healthy rows are cultivated rice or resistant weedy rice accessions, whereas chlorotic rows are benzobicyclon-sensitive weedy rice accessions.
Figure 9 in Interference and management of herbicide-resistant crop volunteers
Figure 9. Field-scale evaluation of imidazolinone-resistant (ClearfieldṜ) wheat compared with non–herbicide resistant wheat (including volunteers the following year) in Saskatchewan, Canada, in the early 2000s (adapted from Beckie et al. 2011).
Figure 4 in Interference and management of herbicide-resistant crop volunteers
Figure 4. Symptoms of (A) glufosinate on glyphosate-resistant volunteer corn in glufosinate-resistant soybean and (B) sethoxydim on glyphosate/glufosinate-resistant volunteer corn in dicamba/glyphosate-resistant soybean.
Figure 2 in Interference and management of herbicide-resistant crop volunteers
Figure 2. Soybean after corn is a typical rotation in the midwestern United States. If not controlled, volunteer corn is a problem weed in soybean fields.
Figure 1 in Interference and management of herbicide-resistant crop volunteers
Figure 1. Glyphosate- and glufosinate-resistant canola volunteers in adjacent fields in Saskatchewan, Canada, due to bidirectional pollen-mediated gene flow the previous year.
Figure 3 in Interference and management of herbicide-resistant crop volunteers
Figure 3. Volunteer corn in a cornfield in Nebraska. Highly productive soils and easy access to irrigation have encouraged growers to adopt a corn-on-corn cropping system in south-central Nebraska that results in corn volunteers.
Figure 3 in Rattail fescue (VulpiO myuros) interference and seed production as affected by sowing time and crop density in winter wheat
Figure 3. Relationships between yield components and Vulpia myuros density at two sowing times and crop densities in the growing seasons of 2017–2018 (A and C) and 2018– 2019 (B and D). Number of crop ears per square meter (A and B) and 1,000-kernel weight (C and D) data are shown with fitted curves. Data from the growing seasons of 2017–2018 and 2018–2019 were fit to the linear regression (Equation 2) and asymptotic nonlinear regression (Equation 3) models, respectively.
Figure 4 in Rattail fescue (VulpiO myuros) interference and seed production as affected by sowing time and crop density in winter wheat
Figure 4. Relationships between the per-plant seed production and Vulpia myuros density at two crop densities solely at normal sowing time in the growing season of 2017–2018 (A) and at two sowing times and crop densities in 2018–2019 (B). Data from the growing seasons of 2017–2018 and 2018–2019 were fit to the linear regression (Equation 2) and asymptotic nonlinear regression (Equation 3) models, respectively.
Figure 2 in Rattail fescue (VulpiO myuros) interference and seed production as affected by sowing time and crop density in winter wheat
Figure 2. Relationships between crop grain yield (kg ha−1) and Vulpia myuros density at two sowing times and crop densities in winter wheat in the growing seasons of 2017–2018 (A) and 2018–2019 (B). Data were fit to the rectangular hyperbola model (Equation 1).
Figure 1 in Rattail fescue (VulpiO myuros) interference and seed production as affected by sowing time and crop density in winter wheat
Figure 1. Cumulative emergence dynamics of Vulpia myuros at normal sowing time and late sowing time in relation to thermal time (C) in 2017–2018 (A) and 2018–2019 (B). Regression equation and parameter estimates described in Table 2.
Figure 6 in Interference and management of herbicide-resistant crop volunteers
Figure 6. Stalk regrowth of 2,4-D-resistant cotton after shredding and treatment with duplosan.
Figure 5 in Interference and management of herbicide-resistant crop volunteers
Figure 5. Cotton stalk regrowth in a field in Georgia.
Figure 8 in Interference and management of herbicide-resistant crop volunteers
Figure 8. Volunteer soybean in a cornfield in Nebraska.
ScienceDex guides
Understand access before you commit
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.