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Organizations: CIMMYT Ethiopia Tags: groundnuts

4 datasets found

  • Using a Video-based Product Ranking Tool (VPRT) as a basis for market segment... N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    The groundnut data was collected from small-scale groundnut farmers in the Tanzanian regions of Dodoma, Shinyanga, Mtwara, Lindi, and Songwe in May and November 2023. The sample size consists of 2,200 small-scale farmers. The phase one data responses are from farmers in Dodoma and Shinyanga, collected in May 2023, while the phase two data is from farmers...
    Created January 20, 2025 Updated January 20, 2025
  • Replication Data for: Sparse multi-trait genomic prediction under incomplete ... N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    The efficiency of genomic selection methodologies can be increased by sparse testing where a subset of materials are evaluated in different environments. Seven different multi-environment plant breeding datasets were used to evaluate four different methods for allocating lines to environments in a multi-trait genomic prediction problem. The results of the...
    Created January 20, 2025 Updated January 20, 2025
  • Replication Data for: A comparison between three machine learning methods for... N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    Genomic selection (GS) provides a new way for plant breeders select the best genotype. It draws upon historical phenotypic and genotypic information for training a statistical machine learning model which is used for predicting phenotypic (or breeding) values of new lines for which only genotypic information is available. Many statistical machine learning...
    Created January 20, 2025 Updated January 20, 2025
  • Replication Data for: Multi-trait genome prediction of new environments with ... N3 | TTL | RDF/XML | JSON-LD

    CIMMYT Ethiopia
    The genomic selection (GS) methodology has revolutionized plant breeding. This methodology makes predictions for genotyped candidate lines based on statistical machine learning algorithms that are trained with phenotypic and genotypic data of a reference population. GS can save significant resources in the selection of candidate individuals. However,...
    Created January 20, 2025 Updated January 20, 2025
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