CIMMYT Ethiopia
Genotype x environment interaction and GWAS in a durum panel under yield potential, drought stress, and heat stress conditions
GWAS identifies common loci under stressed and non-stressed environments.
Agricultural data for Ethiopia, gathered from research institutes and government sources into one searchable catalogue.
1–10 of 30 datasets
CIMMYT Ethiopia
GWAS identifies common loci under stressed and non-stressed environments.
CIMMYT Ethiopia
Genome-wide association study (GWAS) was conducted for grain yield (YLD) and yield components on a wheat association mapping initiative (WAMI) population of 287 elite, spring wheat lines grown under temperate irrigated high-yield potential condition in Ciudad Obregón, Mexico, during four crop cycles (from 2009–2010 to 2012–2013). Raw data for grain yield, yield components and physiological traits are provided.
CIMMYT Ethiopia
The Elite Spring Wheat Yield Trial (ESWYT) is a replicated yield trial that contains spring bread wheat (Triticum aestivum) germplasm adapted to Mega-environment 1 (ME1) which represents the optimally irrigated, low rainfall areas. Major stresses include leaf, stem and yellow rusts, Karnal bunt, and lodging. Representative areas include the Gangetic Valley (India), the Indus Valley (Pakistan), the Nile Valley (Egypt), irrigated river valleys in parts of China (e.g. Chengdu), and the Yaqui Valley (Mexico). This ME encompasses 36 million hectares spread primarily over Asia and Africa between 350S -350N latitudes. White (amber)-grained types are preferred by consumers of wheat in the vast majority of the areas. It is distributed to upto 200 locations and contains 50 entries.
CIMMYT Ethiopia
The Elite Spring Wheat Yield Trial (ESWYT) is a replicated yield trial that contains spring bread wheat (Triticum aestivum) germplasm adapted to Mega-environment 1 (ME1) which represents the optimally irrigated, low rainfall areas. Major stresses include leaf, stem and yellow rusts, Karnal bunt, and lodging. Representative areas include the Gangetic Valley (India), the Indus Valley (Pakistan), the Nile Valley (Egypt), irrigated river valleys in parts of China (e.g. Chengdu), and the Yaqui Valley (Mexico). This ME encompasses 36 million hectares spread primarily over Asia and Africa between 350S -350N latitudes. White (amber)-grained types are preferred by consumers of wheat in the vast majority of the areas. It is distributed to upto 200 locations and contains 50 entries.
CIMMYT Ethiopia
The Semi-Arid Wheat Yield Trial (SAWYT) is a replicated yield trial that contains spring bread wheat (Triticum aestivum) germplasm adapted to low rainfall, drought prone environments typically receiving less than 500 mm of water available during the cropping cycle. The combination of water-use efficiency and water responsive broad adaptation plus yield potential is important in drought environments where rainfall is frequently erratic across and within years. Stripe rust, leaf rust and stem rust, root rots, nematodes, and bunts are the key biotic constraints. Typical target environments include winter rain or Mediterranean-type drought associated with post-flowering moisture stress and heat stress such as those found at Aleppo (Syria), Settat (Morocco) and Marcos Juarez (Argentina), all classified by CIMMYT within Wheat Mega Environment 4 (Low rainfall, semi-arid environment; ME4: SA). It is distributed to 150 locations, and contains 50 entries.
CIMMYT Ethiopia
The Semi-Arid Wheat Yield Trial (SAWYT) is a replicated yield trial that contains spring bread wheat (Triticum aestivum) germplasm adapted to low rainfall, drought prone environments typically receiving less than 500 mm of water available during the cropping cycle. The combination of water-use efficiency and water responsive broad adaptation plus yield potential is important in drought environments where rainfall is frequently erratic across and within years. Stripe rust, leaf rust and stem rust, root rots, nematodes, and bunts are the key biotic constraints. Typical target environments include winter rain or Mediterranean-type drought associated with post-flowering moisture stress and heat stress such as those found at Aleppo (Syria), Settat (Morocco) and Marcos Juarez (Argentina), all classified by CIMMYT within Wheat Mega Environment 4 (Low rainfall, semi-arid environment; ME4: SA). It is distributed to 150 locations, and contains 50 entries.
CIMMYT Ethiopia
The Elite Spring Wheat Yield Trial (ESWYT) is a replicated yield trial that contains spring bread wheat (Triticum aestivum) germplasm adapted to Mega-environment 1 (ME1) which represents the optimally irrigated, low rainfall areas. Major stresses include leaf, stem and yellow rusts, Karnal bunt, and lodging. Representative areas include the Gangetic Valley (India), the Indus Valley (Pakistan), the Nile Valley (Egypt), irrigated river valleys in parts of China (e.g. Chengdu), and the Yaqui Valley (Mexico). This ME encompasses 36 million hectares spread primarily over Asia and Africa between 350S -350N latitudes. White (amber)-grained types are preferred by consumers of wheat in the vast majority of the areas. It is distributed to upto 200 locations and contains 50 entries.
CIMMYT Ethiopia
Phenotypic data were collected in on-station field trials for advanced breeding lines from the CIMMYT Bread Wheat breeding program over several years.
CIMMYT Ethiopia
Genomic prediction methods may be used to enhance efforts to rapidly introgress traits of interest from exotic germplasm into elite materials. This study examined the performance of different genomic prediction models using genotypic and phenotypic data related to 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in germplasm banks. The Mexican and Iranian collections were evaluated under optimal, drought, and heat conditions for several traits including the highly heritable traits, days to heading (DTH), and days to maturity (DTM). The results of the different analyses are reported in the accompanying journal article.
CIMMYT Ethiopia
In plant breeding, sparse testing methods have been suggested to improve the efficiency of the genomic selection methodology. The data provided in this dataset were used to evaluate four methods for allocating lines to environments for sparse testing in multi-environment trials. The analysis was conducted using a multi-trait and uni-trait framework. The accompanying article describes the results of the evaluation as well as a cost-benefit analysis to identify the benefits that can be obtained using sparse testing methods.