Sparse testing designs for optimizing resource allocation in multi-environment cassava breeding trials
The development of improved cultivars requires establishing multi-environment trials (METs) to evaluate their performance under a wide range of environmental conditions. However, the high phenotyping costs often limit the capacity to evaluate genotypes in all the target environments. Our main object...
| Main Authors: | , , , , , |
|---|---|
| Format: | Journal Article |
| Language: | Inglés |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/175311 |
Similar Items: Sparse testing designs for optimizing resource allocation in multi-environment cassava breeding trials
- Optimization of sparse phenotyping strategy in multi-environmental trials in maize
- Optimizing sparse testing for genomic prediction of plant breeding crops
- Using an incomplete block design to allocate lines to environments improves sparse genome-based prediction in plant breeding
- Genetic variability and genotype by environment interaction of two major cassava processed products in multi-environments
- Genomic-assisted sparse multi-location testing to increase genetic gains in barley
- Unraveling the stable green super rice lines across the multi-environment yield trials