Agricultural data for Ethiopia, gathered from research institutes and government sources into one searchable catalogue.
1,051–1,060 of 1,112 datasets
CIMMYT Ethiopia
The file contains the coordinates for 6338 soil samples taken from 2016 to 2026 in farmer fields in Mexico with the corresponding soil analysis data. These soil samples were analyzed at Fertilab (www.fertilab.com.mx). Coordinates are limited to two digits behind the point. In case that full precision GPS data is needed for research please contact CIMMYT.
CIMMYT Ethiopia
Rainfed maize production in southern Mexico is constrained by climate variability and soil fertility limitations. This dataset contains seven years of data from a long-term field experiment conducted at the San Miguel Tlacamama Research Platform, Oaxaca, Mexico, evaluating the effects of crop diversification (maize monoculture vs. maize–cowpea intercropping), stubble management (remove vs. keep), and fertilization (organic vs. organic–mineral fertilization). The database includes agronomic management data (tillage, residue management, planting density, plant spacing, and fertilization), crop yield data (maize and cowpea grain yield, sowing, emergence, flowering, maturity, harvest, plant height, and lodging), soil fertility data, maize grain nutritional quality data, and economic data (production costs, gross margin, and net profit).
CIMMYT Ethiopia
This dataset was generated as part of the Guiding Acid Soil Management Investments in Africa (GAIA) project, which aims to support evidence-based investments in acid soil management across sub-Saharan Africa. Within this project, researcher-managed on-farm trials were established to quantify crop yield responses to increasing lime application rates. The experimental design followed a randomized complete block design (RCBD) within each participating farm. Sixteen farms were selected to host the trial, and seven lime application rates were tested within each farm. Lime was applied at the onset of the trial (Year 1). There were three blocks per farm. Blocks were relabelled when the former could not be identified in subsequent season or year. Incomplete, isolated or missing blocks in a farm result either from data missingness or farm misidentification. Crop yields measured during the first year capture the direct response to lime application, while yields measured in the second year allow evaluation of the residual effects of the initial lime treatment. This dataset contains plot-level yield measurements for maize, common beans, and potatoes collected during the first and second years after trial establishment in Rwanda. Predicted soil properties associated with the experimental sites are available from external datasets and can be linked through the soil sample unique identifier (SSN). These soil datasets are available at: Predicted Soil Properties Dataset: hdl:11529/10549138 Predicted Soil Properties Dataset: doi:10.71682/10549329 To facilitate interoperability and harmonization of agronomic terminology, a lookup table is provided that maps variable names and terms used in this dataset to the terminology defined in the terminag GitHub repository . Data from the first year are available in the related dataset: https://doi.org/10.71682/10549434 .
CIMMYT Ethiopia
This dataset was generated as part of the Guiding Acid Soil Management Investments in Africa (GAIA) project, which aims to support evidence-based investments in acid soil management across sub-Saharan Africa. Within this project, researcher-managed on-station trials were established to quantify crop yield responses to increasing lime application rates. The experimental design followed a randomized complete block design (RCBD) within each participating farm. Two farms were selected to host the trial, and seven lime application rates were tested within each farm. There were three blocks per farm. Crop yields measured during the first year capture the direct response to lime application, while yields measured in the second year allow evaluation of the residual effects of the initial lime treatment. This dataset contains plot-level yield measurements for maize, wheat, faba bean, and soybean collected during the first and second years after trial establishment in Ethiopia. Predicted soil properties associated with the experimental sites are available from external datasets and can be linked through the soil sample unique identifier (SSN). These soil datasets are available at: Predicted Soil Properties Dataset: hdl:11529/10549136 Predicted Soil Properties Dataset: doi:10.71682/10549328 To facilitate interoperability and harmonization of agronomic terminology, a lookup table is provided that maps variable names and terms used in this dataset to the terminology defined in the terminag GitHub repository . Data from the first year are available in the related dataset: https://doi.org/10.71682/10549433
CIMMYT Ethiopia
This dataset was generated as part of the Guiding Acid Soil Management Investments in Africa (GAIA) project, which aims to support evidence-based investments in acid soil management across sub-Saharan Africa. Within this project, researcher-managed on-farm trials were established to quantify crop yield responses to increasing lime application rates. The experimental design followed a randomized complete block design (RCBD) within each participating farm. Nine farms were selected to host the trial, and seven lime application rates were tested within each farm. Lime was applied at the onset of the trial (Year 1). There were three blocks per farm. Blocks were relabelled when the former could not be identified in subsequent season or year. Incomplete, isolated or missing blocks in a farm result either from data missingness or farm misidentification. Crop yields measured during the first year capture the direct response to lime application. This dataset contains plot-level yield measurements for maize, common beans, and potatoes collected during the first year after trial establishment in Rwanda. Predicted soil properties associated with the experimental sites are available from external datasets and can be linked through the soil sample unique identifier (SSN). These soil datasets are available at: Predicted Soil Properties Dataset: hdl:11529/10549138 Predicted Soil Properties Dataset: doi:10.71682/10549329 To facilitate interoperability and harmonization of agronomic terminology, a lookup table is provided that maps variable names and terms used in this dataset to the terminology defined in the terminag GitHub repository . Data from the second year are available in the related dataset: https://doi.org/10.71682/10549436 .
CIMMYT Ethiopia
This dataset was generated as part of the Guiding Acid Soil Management Investments in Africa (GAIA) project, which aims to support evidence-based investments in acid soil management across sub-Saharan Africa. Within this project, researcher-managed on-station trials were established to quantify crop yield responses to increasing lime application rates. The experimental design followed a randomized complete block design (RCBD) within each participating farm. Two farms were selected to host the trial, and seven lime application rates were tested within each farm. There were three blocks per farm. Crop yields measured during the first year capture the direct response to lime application. This dataset contains plot-level yield measurements for maize, wheat, faba bean, and soybean collected during the first year after trial establishment in Ethiopia. Predicted soil properties associated with the experimental sites are available from external datasets and can be linked through the soil sample unique identifier (SSN). These soil datasets are available at: Predicted Soil Properties Dataset: hdl:11529/10549136 Predicted Soil Properties Dataset: doi:10.71682/10549328 To facilitate interoperability and harmonization of agronomic terminology, a lookup table is provided that maps variable names and terms used in this dataset to the terminology defined in the terminag GitHub repository . Data from the second year are available in the related dataset: https://doi.org/10.71682/10549435 .
CIMMYT Ethiopia
Results of agrotechnical evaluation of small-scale farm equipment in the performance of mechanical weed control in maize fields
CIMMYT Ethiopia
Wheat head blast index (%) data for four CIMMYT nurseries (16HLBSN, 16HZAN, 42SAWSN, and 57IBWSN) is presented. Field trials took place in Okinawa (Bolivia) and Jashore (Bangladesh) during the 2025 cycles. Two sowings were made in Jashore while only one was made in Okinawa.
CIMMYT Ethiopia
This research focuses on the development and evaluation of remote sensing approaches for the assessment of wheat grain quality and productivity. Grain yield, grain nitrogen content, and grain protein content are key traits in wheat breeding and crop management; however, their measurement is often labor-intensive, time-consuming, and costly. Advances in precision agriculture and unmanned aerial vehicle (UAV) technologies provide new opportunities to estimate these traits rapidly and non-destructively through spectral information collected during the growing season. Field trials were conducted over four consecutive growing seasons in Northwest Mexico under contrasting agronomic management conditions, including different tillage systems, irrigation regimes, and nitrogen fertilization levels. Hyperspectral and multispectral imagery acquired at multiple growth stages was used to derive spectral and thermal variables associated with crop performance and grain quality attributes. Several modeling strategies combining vegetation indices, spectral bands, and thermal information were investigated using different statistical and machine learning techniques. Their predictive ability was assessed across environments and growth stages to identify robust approaches for trait estimation. The outcomes of this work contribute to the advancement of high-throughput phenotyping methodologies and support more efficient wheat breeding and nitrogen management practices through the integration of UAV-based remote sensing technologies.
CIMMYT Ethiopia
The dataset comprises information from 5,689 wheat fields, capturing crop management from sowing to harvesting, including detailed field-level inputs and production practices. Collected over six years (2016–17 to 2021–22) across Bihar and the eastern part of Uttar Pradesh, it includes yield measurements obtained through physical crop-cutting experiments. Complementing this, field-specific weather data such as temperature and solar radiation were accessed from secondary source (global gridded meteorological product AgERA5 v2.0) to align with the wheat-growing season, providing a comprehensive view of yield performance under varying management and weather conditions.