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1,312 datasets found

  • Pathways to sustainable intensification in Eastern and Southern Africa - gene... N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    The Adoption Pathways project was part of a portfolio of projects that has contributed to the broader theme of sustainable intensification research led by the International Maize and Wheat Improvement Center (CIMMYT) and made possible by the contribution of several teams from national and international research groups brought together by funding from the...
    Created January 20, 2025 • Updated January 20, 2025

  • HTMA MPS1 Cycle 1 Genotyping for GEBV estimation N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    Cycle1 formed by inter mating selected S2 families genotypes genotyped with 84 SNPs for GEBV estimation for grain yield
    Created January 20, 2025 • Updated January 20, 2025

  • IWIN-DAP: An Excel macro to analyze CIMMYT International Wheat Trial data N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    This tutorial explains how to use the IWIN-DAP, which is an Add-In to Microsoft Excel 2010, to analyze data from CIMMYT’s International Wheat Information System. IWIN-DAP is an illustration of an alternative, quick and easy approach allowing the use of Excel to analyze multi-location trials from CIMMYT international nurseries. This tutorial explains, step...
    Created January 20, 2025 • Updated January 20, 2025

  • Genome wide association mapping for grain yield and stripe rust resistance ge... N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    Turkish landraces were genotyped using GBS and phenotyped for grain yield and yield component traits and stripe rust resistance at three locations. The data was used for a genome wide association study and important marker-trait associations were identified.
    Created January 20, 2025 • Updated January 20, 2025

  • 48th International Bread Wheat Screening Nursery MAS data N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    The International Bread Wheat Screening Nursery (IBWSN) is designed to rapidly assess a large number of advanced generation (F3-F7) lines of spring bread wheat under Mega-environment 1 (ME1) which represents diversity for a wide range of latitudes, climates, daylengths, fertility conditions, water management, and (most importantly) disease conditions. The...
    Created January 20, 2025 • Updated January 20, 2025

  • 47th International Bread Wheat Screening Nursery MAS data N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    The International Bread Wheat Screening Nursery (IBWSN) is designed to rapidly assess a large number of advanced generation (F3-F7) lines of spring bread wheat under Mega-environment 1 (ME1) which represents diversity for a wide range of latitudes, climates, daylengths, fertility conditions, water management, and (most importantly) disease conditions. The...
    Created January 20, 2025 • Updated January 20, 2025

  • 46th International Bread Wheat Screening Nursery MAS data N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    The International Bread Wheat Screening Nursery (IBWSN) is designed to rapidly assess a large number of advanced generation (F3-F7) lines of spring bread wheat under Mega-environment 1 (ME1) which represents diversity for a wide range of latitudes, climates, daylengths, fertility conditions, water management, and (most importantly) disease conditions. The...
    Created January 20, 2025 • Updated January 20, 2025

  • 45th International Bread Wheat Screening Nursery MAS data N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    The International Bread Wheat Screening Nursery (IBWSN) is designed to rapidly assess a large number of advanced generation (F3-F7) lines of spring bread wheat under Mega-environment 1 (ME1) which represents diversity for a wide range of latitudes, climates, daylengths, fertility conditions, water management, and (most importantly) disease conditions. The...
    Created January 20, 2025 • Updated January 20, 2025

  • Genomic and pedigree prediction with genotype × environment interaction in sp... N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    Increases in genetic gains in grain yield can be accelerated through genomic selection (GS). In the present study seven genomic prediction models under two cross validation scenarios were evaluated on the Wheat Association Mapping Initiative population of 287 advanced elite lines phenotyped for grain yield (GY), thousand grain weight (GW), grain number...
    Created January 20, 2025 • Updated January 20, 2025

  • Bayesian genomic prediction with genotype × environment interaction kernel mo... N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    The phenomenon of genotype × environment (G×E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G×E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G×E are...
    Created January 20, 2025 • Updated January 20, 2025

  • Phenotypic data from trials conducted by the CIMMYT Bread Wheat Breeding Program N3 | TTL | RDF/XML | JSON-LD

    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.
    Created January 20, 2025 • Updated January 20, 2025

  • Genotypic data from CIMMYT bread wheat breeding lines used in the Feed the Fu... N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    Genetic profiling of wheat breeding lines from the CIMMYT bread wheat breeding program was carried out over several years.
    Created January 20, 2025 • Updated January 20, 2025

  • Prediction models for canopy hyperspectral reflectance in wheat breeding data N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    Vegetation indices (VI) generated by using some bands from hyperspectral cameras are used as predictors of primary traits. This study proposes models that use all available bands as predictors of primary traits. The proposed models were ordinal least square (OLS), Bayes B, principal components with Bayes B, functional B-spline, functional Fourier and...
    Created January 20, 2025 • Updated January 20, 2025

  • Genotypic results for heat tolerance marker-assisted selection 1 N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    This study provides the genotypic results for a BC2F1 population screened with seven markers associated with heat tolerance-related QTL.
    Created January 20, 2025 • Updated January 20, 2025

  • International Late Yellow Hybrid - ILYH1231 N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    Summary results and individual trial results from the International Late Yellow Hybrid - ILYH, (Mid-altitude / Subtropical Three Way Crosses Yellow Hybrids, with High Concentrations of Provitamins A (especially beta-carotene) - CHTSPROA) conducted in 2012.
    Created January 20, 2025 • Updated January 20, 2025

  • International Late Yellow Hybrid - ILYH1205 N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    Summary results and individual trial results from the International Late Yellow Hybrid - ILYH, (Elite TropicalLate Yellow Normal and QPM Hybrid Trial Version A - CHTTY-A) conducted in 2012.
    Created January 20, 2025 • Updated January 20, 2025

  • A Genomic Bayesian Multi-trait and Multi-environment Model N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    When plant scientists record information on multiple genotypes evaluated in multiple environments, a multi-environment single trait for assessing genotype × environment interaction (G×E) model is usually employed. Comprehensive models that simultaneously take into account the correlated traits and trait × genotype × environment interaction (T×G×E) are...
    Created January 20, 2025 • Updated January 20, 2025

  • Global Map of Classified Crop Areas N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
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    Created January 20, 2025 • Updated January 20, 2025

  • Global map of wheat mega-environments N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    Global map of wheat mega-environments. The map show twelve different mega-environments around the world. Mega environments mapped according to: Braun et al., Multi-location testing as a tool to identify plant response to global climate change. In M. P. Reynolds, (ed.) Climate change and crop production. CABI Climate Change Series, U.K. pp. 115-138. 2010.
    Created January 20, 2025 • Updated January 20, 2025

  • Global map of maize mega-environments N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    Global map and shape files of maize mega-environments. The map show six different mega-environments around the world.
    Created January 20, 2025 • Updated January 20, 2025
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