Sparse testing designs for optimizing resource allocation in multi-environment cassava breeding trials.

ABSTRACT: 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 objective was to explore the potential of implementing sparse testing in cassava breeding programs to reduce the cost of phenotyping in METs. The population used in this study consisted of 435 cassava genotypes evaluated in five environments in Nigeria for dry matter (dm) and fresh root yield (fyld). Sparse testing designs were developed based on non-overlapping (NOL), completely overlapping (OL), and intermediates between NOL and OL genotypes. Three prediction models were assessed (one based on pheno

SUBMITTER: Lubanga N 

PROVIDER: S-EPMC11800058 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature