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Crop yield, soil data, pest surveillance, livestock, food composition, precision farming
17,884 datasets
A 2026 study by D. Gil calculates predicted no-effect concentrations (PNECs) for 17 antifungal compounds, using Candida albicans as a model organism. The data, derived from a systematic review of 122 articles, aims to inform regulation of antifungal release in wastewater and agricultural settings to mitigate resistance risks.
Martha Lustosa Carvalho's study evaluates 13 soil health indicators across a crop diversity gradient in Carambeí, Southern Brazil. It analyzes physical, chemical, and biological indicators like bulk density, active carbon, and nutrient availability under soybean-oats monoculture, diversified rotations, and cover crop mixtures. The data supports assessing incremental soil health benefits in mature no-till systems practiced for over three decades.
38 years of annual harvest disturbance data for Canada's 650-million-hectare forested ecosystems. The dataset maps the year of greatest harvest disturbance from 1985 to 2022 using a fully automated, consistent methodology within Canada's National Terrestrial Ecosystem Monitoring System. It was produced by researchers from Natural Resources Canada using 30-meter resolution Landsat time series.
A 14.5 KB interview excerpt documents the tradition of pig slaughtering and food practices in the Arbanasi community. The document was authored by Maja Petani and is available under a CC-BY-4.0 license. It was last updated on April 18, 2026.
An interview excerpt documenting the food traditions of the Arbanasi community, authored by Maja Petani. The dataset is a 15.3 KB DOCX file available under a CC-BY-4.0 license and was last updated on April 18, 2026.
A survey dataset from the SSRS Omnibus Poll focusing on public perceptions of food insecurity. It was authored by SSRS and published via the Roper Harvested Dataverse. The record was last updated on June 11, 2026.
138 quadrats measuring 20 m² each were surveyed around twenty-eight stormwater ponds in London, Canada, for macroplastic waste items (≥ 5 mm). Average item concentrations ranged from 1.7 to 40.0 per 20 m², with food packaging, household items, and leisure products being the most common types. The dataset, authored by Dinithi S. De Silva and last updated in March 2026, was analyzed using Poisson regression and hurdle models to investigate relationships with land use and pond-level factors.
138 quadrats surrounding twenty-eight stormwater ponds in London, Canada, were surveyed for macroplastic waste items. Average item concentrations varied from 1.7 to 40.0 per 20 m², with food packaging, household items, and leisure products being the most common types. The dataset, created by Dinithi S. De Silva and last updated in March 2026, uses statistical models to link debris abundance to land use and pond-level factors.
Geospatial data classifies acute food insecurity levels across Malawi for a near-term projection period in 2022. The dataset was produced by FEWS NET (Famine Early Warning Systems Network). It was last updated in April 2026.
2021 geographic data on acute food insecurity classifications across Sudan. The dataset was produced by FEWS NET, the Famine Early Warning Systems Network, and provides spatial delineations of food security conditions for that year.
Geospatial data from FEWS NET provides projected acute food insecurity classifications across Yemen for the year 2020. The dataset includes classifications such as Minimal, Stressed, Crisis, Emergency, and Famine, represented in vector formats. It was produced by the Famine Early Warning Systems Network (FEWS NET) and last updated in April 2026.
Afghanistan's geographic data shows FEWS NET acute food insecurity classifications for near-term projections in 2020 and 2021. The dataset likely contains polygon-level classifications based on the Integrated Food Security Phase Classification (IPC) framework. It is provided under an open license for analysis and humanitarian planning.
Cameroon's geographic data contains FEWS NET medium-term projections for acute food insecurity, classified using the Integrated Food Security Phase Classification (IPC) system. The dataset includes separate files for the years 2020 and 2021. It is intended for analysis of food security conditions and trends across the country.
Burundi's geographic data on acute food insecurity classifications, produced by FEWS NET. The dataset likely contains IPC-compatible phase classifications for administrative areas. It is available for the years 2021 and 2022 in KML and GeoJSON formats.
FEWS NET geographic data projects acute food insecurity classifications across Chad for 2021. The dataset contains polygon-based classifications for administrative units, created by the Famine Early Warning Systems Network. It was last updated on the platform in April 2026.
FEWS NET geographic classifications project acute food insecurity across Somalia for the year 2020. The data provides near-term forecasts of crisis severity levels for administrative regions. It was published by the Famine Early Warning Systems Network and last updated in April 2026.
Geospatial data classifies acute food insecurity levels across Honduras for the year 2021. The dataset was produced by FEWS NET (Famine Early Warning Systems Network). It was last updated in April 2026.
Geoscience Australia Data provides seismic reflection profiles indicating probable Permian to Early Tertiary bedrock outcrops on the lower continental slope off Exmouth, Western Australia. The data covers water depths from 1400 to 4000 meters and describes rock types including fluvial sandstone, shale, and shelf limestone. The dataset was last updated on 2026-03-25.
Geospatial data from FEWS NET classifies acute food insecurity across Ethiopia for the year 2021. The dataset is provided in GEOJSON and KML formats. It was last updated on the platform in April 2026.
Geospatial data classifies acute food insecurity levels across Yemen for the year 2020. The Famine Early Warning Systems Network (FEWS NET) produced this projection. It was last updated in April 2026.