Agricultural data for Ethiopia, gathered from research institutes and government sources into one searchable catalogue.
1,111–1,120 of 1,344 datasets
CIMMYT Ethiopia
Genotyping data from marker-assisted introgression of the BNI short arm translocation (T3BL.3NsbS) into CIMMYT elite germplasm (2024 and 2025).
CIMMYT Ethiopia
This database contains grain, biomasss and nutritional yield data from on-farm trials in Kasungu, Mchinji, and Lilongwe districts of central Malawi, conducted over three cropping seasons (2014–15 to 2016-17). The trials tested sustainable and resilient cropping systems, including Conservation Agriculture (CA) with minimum tillage, glyphosate herbicide, and maize-legume rotations, compared to conventional ridge-and-furrow sole maize (True farmer practice). The experiments were conducted on 24 farms, with each farm serving as one replicate. Data collected included grain yield, biomass, protein, and energy yields, providing insights into system performance and sustainability.
CIMMYT Ethiopia
Field survey conducted in Eastern Kenya, in Embu and Kirinyaga counties in March 2024, covering 1175 households.
CIMMYT Ethiopia
This repository contains the data and scripts used in the study titled "Crop diversification in conservation agriculture is critical for climate adaptation"
CIMMYT Ethiopia
Two major and two minor QTL for seedling and adult-plant resistance to Septoria tritici blotch (STB), caused by the fungus Zymoseptoria tritici (Z. tritici) were mapped. The two mayor QTL were located on chromosome 2B, the two minor QTL on chromosomes 1A and 7A, respectively and derived from the Tunisian durum wheat landrace accession ‘Agili39’. QTL were mapped in a recombinant inbred population, phenotyped for STB resistance using a wide array of isolates and genotyped using the high density DArTSeq platform.
FDRE - Ministry of Agriculture (MoA)
The Soil and Terrrain database of Central Africa (SOTERCAF, version 1.0) was compiled at scale 1:2 million for the Democratic Republic of Congo and at scale 1:1 million for Rwanda and Burundi. The SOTERCAF compilation has been a joint collaboration of the Soil Science Laboratory of the University of Ghent, Belgium and ISRIC - World Soil Information, Wageningen under contract with the Food and Agriculture Organisation of the United Nations. Further assistance is provided by the Department BIOT of the Hogeschool Gent, the Royal Museum for Central Africa (Tervuren) and data holders in the Democratic Republic Congo, Burundi and Rwanda. The project started in September 2005 by deriving physiographic units from SRTM grid data based on SOTER landform definitions. The database was completed in July 2006 after combining the physiographic layer with the lithology and soils layer. The border harmonization with the SOTERSAF database was finalized November 2006. SOTERCAF forms a part of the ongoing activities of ISRIC, FAO and UNEP to update the world's baseline information on natural resources.The project involved collaboration with national soil institutes from the countries in the region as well as individual experts.
FDRE - Ministry of Agriculture (MoA)
Model outputs were updated on Dec 20, 2017. This project used a machine learning data-driven model to predict the distribution of soil carbon under mangrove forests globally. Specifically this dataset contains: 1) a compilation of georeferenced and harmonized soil profile data under mangroves compiled from literature, reports and unpublished contributions 2) global mosaics of soil carbon stocks to 1m and 2m depths produced at 100 m resolution 3) tiled predictions of soil carbon stocks produced at 30 m resolution 4) shape file containing the tiling system 5) shape file containing country boundaries used for calculating national level statistics. For detailed methodologies, please see the scientific paper (https://doi.org/10.1088/1748-9326/aabe1c).
FDRE - Ministry of Agriculture (MoA)
Total plant-available water holding capacity (mm) of the soil whole earth fraction (including coarse fragments), summed over rootable depth and the top 30 cm, mapped at 1km resolution