Detecting the most stable and best-performing genotypes by analysing on-farm experiments with ranking data across different environments and management practices
This poster illustrates how tricot data can be leveraged to assess genotype × environment × management (GxExM) interactions, with the aim of identifying more context-responsive crop varieties. It emphasizes the use of simple ranking data and large datasets to uncover complex adaptation patterns. The...
| Autor principal: | |
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| Formato: | Póster |
| Lenguaje: | Inglés |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/179744 |
| _version_ | 1855520834557313024 |
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| author | 1000FARMS Platform |
| author_browse | 1000FARMS Platform |
| author_facet | 1000FARMS Platform |
| author_sort | 1000FARMS Platform |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This poster illustrates how tricot data can be leveraged to assess genotype × environment × management (GxExM) interactions, with the aim of identifying more context-responsive crop varieties. It emphasizes the use of simple ranking data and large datasets to uncover complex adaptation patterns. The study is part of 1000FARMS’ broader effort to make farmer-managed trials a valuable source of scientific insight. |
| format | Poster |
| id | CGSpace179744 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| record_format | dspace |
| spelling | CGSpace1797442026-01-14T02:04:53Z Detecting the most stable and best-performing genotypes by analysing on-farm experiments with ranking data across different environments and management practices 1000FARMS Platform farming systems participatory research on-farm research data collection data analysis citizen science genetic gain-genetic advance This poster illustrates how tricot data can be leveraged to assess genotype × environment × management (GxExM) interactions, with the aim of identifying more context-responsive crop varieties. It emphasizes the use of simple ranking data and large datasets to uncover complex adaptation patterns. The study is part of 1000FARMS’ broader effort to make farmer-managed trials a valuable source of scientific insight. 2025-09 2026-01-13T11:28:02Z 2026-01-13T11:28:02Z Poster https://hdl.handle.net/10568/179744 en Open Access application/pdf 1000FARMS Platform; (2025) Detecting the most stable and best-performing genotypes by analysing on-farm experiments with ranking data across different environments and management practices. 1 p. |
| spellingShingle | farming systems participatory research on-farm research data collection data analysis citizen science genetic gain-genetic advance 1000FARMS Platform Detecting the most stable and best-performing genotypes by analysing on-farm experiments with ranking data across different environments and management practices |
| title | Detecting the most stable and best-performing genotypes by analysing on-farm experiments with ranking data across different environments and management practices |
| title_full | Detecting the most stable and best-performing genotypes by analysing on-farm experiments with ranking data across different environments and management practices |
| title_fullStr | Detecting the most stable and best-performing genotypes by analysing on-farm experiments with ranking data across different environments and management practices |
| title_full_unstemmed | Detecting the most stable and best-performing genotypes by analysing on-farm experiments with ranking data across different environments and management practices |
| title_short | Detecting the most stable and best-performing genotypes by analysing on-farm experiments with ranking data across different environments and management practices |
| title_sort | detecting the most stable and best performing genotypes by analysing on farm experiments with ranking data across different environments and management practices |
| topic | farming systems participatory research on-farm research data collection data analysis citizen science genetic gain-genetic advance |
| url | https://hdl.handle.net/10568/179744 |
| work_keys_str_mv | AT 1000farmsplatform detectingthemoststableandbestperforminggenotypesbyanalysingonfarmexperimentswithrankingdataacrossdifferentenvironmentsandmanagementpractices |